6 years in the making.

One all-nighter in a college library. One viral website. A community of over 400,000 people later. Today, SSQRD is finally available on the App Store.

To everyone who has followed our journey from the beginning, thank you. You’re the first to get access before our public launch.

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What is SSQRD?

SSQRD is a free shopping platform that helps you discover independent brands and products from around the world, all in one place.

I. There’s absolutely no big corporations or fast-fashion in our app.

SSQRD only indexes independent brands from around the world, allowing for a shopping experience without fast-fashion slop taking over search results. We intentionally do not index fast-fashion retailers or large corporations, creating a shopping experience centered around discovering independent businesses instead of algorithmic clutter.

II. Our search and recommendation system does not use AI.

Most shopping platforms rely on AI to generate recommendations. We took a different approach. After months of development, we built our recommendation engine using traditional statistical analysis rather than generative AI. This allows you to search for products, discover visually similar alternatives, and find brands that match your style without AI-generated recommendations shaping your experience.

III. SSQRD is built with users in mind.

We never sell or rent your personal data to third parties. SSQRD is completely free to use, and the consumer app is not monetized through advertising or data sales. Instead, our revenue comes from a separate B2B platform that helps independent brands grow their businesses.

In-Depth App Overview

A tour of the SSQRD app.

1. The Home Page

Whenever you open the SSQRD app, you will first see the home page. On here you’ll find:

• Products you’ve recently viewed

• Brands recommended by your region

• Brands that match your taste

• Trending brands

• Trending products

• Recently added brands

• And more

2. The Explore Feed

Our Pinterest-style discovery feed helps you browse products based on what you’ve saved and interacted with. If you want to browse only brands you follow, switch to the Following tab.

You can also filter by:

• Category

• Price

• Style

• And more

3. Our Core-Search Feature

Search is the heart of SSQRD. Our search indexes millions of data points across independent brands to help you find exactly what you’re looking for.

The more specific your search, the better the results will be. Search by item, material, and budget.

Examples:

• “Polka-dot printed abayas”

• “Black linen trousers”

• “leather shoulder bag under $200”

4. Cross-Brand Recommendations

Every product page also recommends visually similar products from other independent brands, including alternatives at different price points, so you can compare options before deciding.

5. Atlas

Our Atlas feature (my personal favorite) helps you browse brands by country and region. We have brands from the Americas, Africa, Asia, Europe, and Oceania. You can click on any brand to view its catalog.

6. Brand Repository

The Brand Repository lets you browse brands using filters for:

• Country

• Product category

• Brand identity

• And more

It’s one of the easiest ways to discover businesses you likely wouldn’t have found otherwise.

7. Personalized Account Hub

You get the best app experience when you create an account, so you can:

• Save products

• Follow brands

• Create collections

• Build your own shopping archive

Over time, SSQRD also analyzes your activity to give you personalized insights into your shopping habits, like a Spotify Wrapped for your style.

Download SSQRD

After thousands of iterations and countless late nights, we’re incredibly excited to finally put SSQRD in your hands.

SSQRD is now available on the App Store. If you don’t have an Apple device, you can still use SSQRD on the web, and our Android app is coming to Google Play soon.

Thank you for believing in what we’re building. We can’t wait to hear what you think.

Welcome to SSQRD.

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Hi, I’m Nabihah, a Bangladeshi-American living in New York. My family immigrated from Bangladesh in the early 2000s in search of better opportunities, but almost everyone back home still works in the country’s garment industry.

Growing up, I heard stories about how difficult their lives were, but they were always just stories. I had never witnessed their work with my own eyes. I’d read articles about garment workers, and every headline felt deeply personal because my own family worked in garments. Yet I couldn’t honestly speak to the realities they experienced. My understanding of the industry came almost entirely from secondhand accounts and distant anecdotes.

That really bothered me. I was forming opinions about an industry that had shaped my family’s life without ever setting foot inside it myself.

So in June 2026, after more than a decade away from Bangladesh, I booked a flight home to visit garment factories and see the industry for myself. This time, I was returning with a camera and an audience, hoping that if I could understand the reality on the ground, I might help others see Bangladesh’s garment industry through a more complete lens.

I. My uncle

After a 39-hour journey from New York, I landed in Dhaka before taking a short domestic flight to Chittagong, the heart of Bangladesh’s ready-made garment industry. The first person I saw was my uncle, who works for a garment manufacturer in Chittagong.

My uncle is a brilliant man. He studied cybersecurity and information technology, spends his free time reading about startups, and dreams of building a software company in the United States. He’s been trying to obtain a green card for nearly fifteen years, so he hasn’t been able to fulfill that dream.

Every morning while I was in Chittagong, he would leave for work before I woke up and return late in the evening, working seven days a week. When I asked if he ever had a day off, he told me that sometimes he gets part of a Friday, but most weeks he works every single day.

He is someone with the talent and ambition to build technology, yet the circumstances around him had left him with few opportunities to pursue that dream. In countries like Bangladesh, countless brilliant people have ideas capable of changing the world, but many spend their lives working relentlessly simply because the pathways available to them are narrower than those afforded elsewhere.

II. Leading up to the visit at the factory

When I arrived in Bangladesh, I had no plan for how I was going to get inside a garment factory and wanted to leave my family out for precautionary reasons.

So I posted a vlog traveling to Bangladesh and explained that I wanted to learn about the garment industry from the ground hoping it would reach the target audience.

It did. Within two days, the video had been viewed more than 1.6 million times. My DMs quickly filled with messages from factory owners and workers inviting me to visit their facilities. I responded to those located near where I was staying and was able to arrange meetings with two factory owners.

Before I go any further, it’s important to acknowledge that this is not an investigative report or a comprehensive study of Bangladesh’s garment industry. I’m not a journalist, and I don’t claim that two meetings can represent an industry that employs millions of people. This is simply my experience and my observations from the conversations I had, and the perspectives shared with me by the people who welcomed me into their work.

III. Meeting a Factory Owner

The first person I met was a factory owner who had discovered my videos online, and after seeing my post about traveling to Bangladesh, he invited me to his office.

The city was experiencing severe flooding that day, so I suggested we reschedule. I was far more interested in touring the factory than sitting in an office. But he insisted we meet first. When I told him our car had become stranded in the floodwater, he offered to send one of his company’s trucks to pick us up. A few minutes later, a large car arrived, I hopped into the back and made our way through flooded streets to his headquarters.

The office caught me off guard. It was modern, newly renovated, and sharply contrasted with the surrounding neighborhood. An employee escorted me through office cubicles to a conference room where the owner was waiting. As I walked through the office, I couldn’t help but notice how quiet it was. The employees were mostly IT and administrative staff rather than garment workers, but they looked exhausted. They weren’t speaking much, and the atmosphere felt noticeably heavy.

Then the owner walked in. He was much younger than I expected. For the next forty-five minutes, we spoke about his business. He explained that he had inherited the company from his father, who founded it years earlier. The factory manufactures ready-made garments for both domestic and international buyers, and he hoped to eventually launch his own direct-to-consumer clothing brand using his existing manufacturing capabilities.

When describing the factory, he told me it was “one of the better ones.” We spoke at length about entrepreneurship, and much of the conversation shifted toward my own startup. He was particularly interested in the American technology ecosystem and wanted to know how it might help him expand his business.

After our meeting, I spent time speaking privately with several employees. Several employees told me they experienced delayed or inconsistent pay, unexpected salary deductions, and long working hours that extended beyond the official end of the workday. Some also described being contacted outside of working hours and expected to remain available whenever needed. I was not able to independently verify these claims, but I kept hearing similar concerns from multiple employees…

Interestingly, many of those same employees also described the factory as being better than many others they were familiar with. Before I left, I asked if I could tour the production facility. The owner advised against it because of the flooding, warning that the roads were nearly impassable.

I decided to go anyway.

IV. Inside the Factory

The factory was about thirty-five minutes from the office. By the time we arrived, I realized the owner was right. The entire area was flooded and as we approached the entrance, our car stalled in the water. We had no choice but to turn around and find another route. A nearby factory had an open entrance where the road was just passable enough for us to stop.

I stepped out of the car and asked the men standing outside if I could come in to film. They said yes and allowed me to go inside.

There was no way to reach the building without walking through the floodwater. I hesitated for a moment before stepping in. The water was murky, carrying dirt and debris from the surrounding streets. By the time I reached the entrance, my shoes were completely soaked but I tried to ignore it.

Then a smell hit me immediately. It was a dense mix of humidity, sour sweat, machine, and damp fabric that clung to the air. The floor was scattered with scraps of cloth and debris, and the building itself felt worn. Inside, rows of sewing machines stretched across a crowded room. There was no air conditioning. Most of the operators I saw were women, many of whom appeared remarkably young. The room was loud with the constant rhythm of sewing machines, yet strangely calm. One male supervisor moved between the rows, checking production as work continued uninterrupted.

What surprised me most wasn’t the factory itself, it was how the people responded to my presence. As I walked through filming, many of the workers smiled at me. Some looked directly into the camera. No one appeared startled by my presence, and no one stopped working. The supervisor I observed wasn’t shouting or creating a scene. From what I could see, this was simply another ordinary workday.

After filming what I could, I thanked the workers and quietly walked back out into the floodwater. If you’re interested in seeing the footage, check out this reel.

V. Dinner with an Industry Executive

The next day, I returned to Dhaka because the flooding in Chittagong was getting so severe, and scheduled a last-minute meeting with an executive at one of Bangladesh’s ready-made garment manufacturers. His company produces for both luxury fashion houses and large American retailers, and he has spent more than three decades in the industry.

We met over dinner in Banani, one of Dhaka’s wealthiest neighborhoods. After I explained why I had come to Bangladesh and what I had seen so far, he told me to be careful about how I tell this story.

He explained that, in his view, reducing Bangladesh’s garment industry to a single sweatshop narrative has consequences far beyond public perception. Bangladesh is one of the world’s largest exporters of ready-made garments, and millions of people depend on the industry for their livelihoods. He argued that when buyers lose confidence in Bangladesh as a manufacturing destination, whether because of political instability, negative publicity, or other factors, orders often shift to competing manufacturing hubs in countries such as Vietnam or India.

Then he told me something I hadn’t known before about any manufacturers. His company has invested years into meeting more than a dozen international certifications and compliance standards, making its factories among the most rigorously audited in the country. Every day, he personally visits his factories in Dhaka.

Then I asked him a question that had been lingering in my mind since visiting Chittagong: if his factories meet such high standards, are they really expensive compared to lower-compliance factories?

He said just a few dollars, and that honestly surprised me. If the difference was only a few dollars per order, why would foreign buyers willingly choose factories with weaker labor or compliance standards?

As dinner continued, I asked how he found customers and he told me he goes door-to-door to meet buyers. For more than thirty years, he has traveled the world meeting potential clients face-to-face. He told me he has visited dozens of countries because, in an industry built on trust, he believes relationships are still the most effective way to earn business.

Before we parted, he invited me to tour his factories in Dhaka. Unfortunately, my flight to Malaysia was leaving the following morning, so I couldn’t accept. But I will be returning again soon to tour.

VI. What Changed My Mind

I’ll admit I arrived in Bangladesh expecting to confirm what I already believed. I thought I would document the harsh realities of garment workers and expose an industry I had spent years associating with exploitation. Instead, I left realizing the story was far more complicated than I had imagined.

What I learned is that “Made in Bangladesh” is not a standard, but a country of thousands of factories, each operating differently. Some factories invest heavily in compliance, worker safety, and international certifications. Others cut corners, lumping them together under a single narrative, doing a disservice to everyone involved, especially the manufacturers that have spent years trying to do things the right way.

That realization fundamentally changed the way I think about accountability because the question isn’t whether a garment made in Bangladesh is unethical, it’s which factory made it, and who chose that factory.

Throughout my conversations, I kept returning to something the executive had told me. That the difference between producing with a highly compliant manufacturer and a lower-compliance one could be surprisingly small. If that’s true, then the conversation shouldn’t end with where a product was made, it should also include why a particular manufacturer was chosen in the first place.

VII. Now What?

As with every problem I encounter, my mind immediately started thinking about potential solutions. That night, I returned to my hotel room replaying the entire trip in my head. Out of everything I had seen, one detail I kept lingering on was the executive spending decades traveling from country to country, knocking on doors just to introduce buyers to his factories. What if one of the biggest barriers wasn’t quality, but rather, visibility?

Finding manufacturers is still remarkably opaque. It depends on industry connections, trade shows, and years of insider knowledge. For many emerging brands, the easiest manufacturer to find isn’t necessarily the best one, but the one they happen to know exists. Sitting alone in my hotel room that night, I realized that this was a problem SSQRD could actually help solve.

We’ve been helping people discover better brands. Why couldn’t we help brands discover better manufacturers?

If we could connect founders directly with ethical, high-compliance manufacturers, we could improve the beginning of the fashion supply chain, not just the end of it. It would make it easier for brands to build responsibly from day one, while giving world-class manufacturers the visibility they deserve.

We're now exploring this as the next chapter of SSQRD. If you're a founder searching for manufacturing partners, or a manufacturer that believes your work deserves greater visibility reach out. I'd love to learn from you as we build this.

VIII. Closing Thoughts

Bangladesh is my motherland. It’s heartbreaking to see a country filled with extraordinarily hardworking and talented people be reduced to a narrative that rarely captures its full complexity. Bangladesh has been one of the foundations of the global fashion industry for decades. It deserves to be known not only for the challenges it has faced, but also for the manufacturers, workers, and innovators working every day to raise the standard.

And I hope SSQRD can play a part in telling that story. When I started SSQRD, the vision was never just to help people discover better brands. It was to make global commerce more accessible to everyone who participates in it, like the consumer searching beyond algorithmically promoted products, the independent designer trying to share their work with the world, and the manufacturer producing exceptional products without the visibility to reach global buyers.

The more I travel, the more convinced I become that commerce doesn’t have to be extractive. It can be reciprocal. It can create opportunity at every step of the supply chain instead of concentrating it in the hands of a few.

That’s the future I want SSQRD to help build. A fashion industry that is symbiotic instead of parasitic, where discovery creates opportunity not just for the brands we wear, but for the people who make them.

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On July 10, 2026, SSQRD founder Nabihah Ahmad visited garment factories in Chittagong, Bangladesh, capturing footage of workers and documenting conditions that contradict the story Western fashion brands tell about their supply chains. What she found was a country whose garment manufacturing infrastructure is considerably more sophisticated, more regulated, and more invested in worker welfare than the brands sourcing from it are willing to pay for. The “sweatshop” narrative that attaches to “Made in Bangladesh” clothing in Western consumer culture isn’t invented. The conditions she documented exist and they’re real. But the narrative is incomplete in a way that misplaces the accountability almost entirely, and that misplacement is commercially convenient for the Western brands responsible for it.

She walked through contaminated floodwater to enter one factory. What she found inside, the smell, the overcrowding, the absence of ventilation, the workers who smiled at her camera with a familiarity that suggested they’d long since stopped expecting anyone to be disturbed by what surrounded them, was real and it was documented. And then she sat in her hotel that evening and processed something that reframed the entire experience: Bangladesh now hosts 280 LEED-certified green garment factories, more than any other nation on earth, with 52 of the world’s top 100 highest-scoring LEED-rated factories located in the same country. In 2025 alone, 38 new factories achieved LEED certification, the highest number in any single year in the country’s history, with 22 of them achieving Platinum status. The problem isn’t that ethical production doesn’t exist in Bangladesh. It’s that Western brands are choosing not to pay for it, and then allowing the resulting conditions to be understood as a Bangladesh problem rather than a sourcing problem.

*LEED stands for “Leadership in Energy and Environmental Design”, it’s the world’s most widely used green building rating system

Bangladesh’s RMG Industry: What It Actually Is

Bangladesh is the world’s second-largest exporter of ready-made garments, with the sector generating $50 billion in export earnings by the end of 2024, representing approximately 84% of the country’s total merchandise exports. The industry employs approximately 5 million workers, 55% of whom are women, making it the primary source of formal employment for Bangladeshi women and a foundational pillar of the country’s economic development since the 1980s. The scale of the industry’s contribution to Bangladesh’s GDP and to global fashion supply is significant enough that the decisions Western brands make about which factories they source from have direct and measurable consequences for millions of people.

Chittagong, the country’s second-largest city and primary port, anchors the EPZ-based wovens and outerwear segment of the industry, with approximately 600 export factories concentrated in the area and Chittagong port handling nearly all of the country’s ocean freight. The city’s Export Processing Zones contain some of the most sophisticated garment manufacturing facilities in the world, established specifically to attract foreign investment and meet international compliance standards. What Nabihah found there wasn’t a uniform picture of exploitation, but rather a two-tier system whose existence Western fashion media has almost entirely failed to report.

The industry’s compliance infrastructure is genuinely impressive. Over 2,400 factories have been remediated under the Accord and the RMG Sustainability Council since 2014. International certifications including BSCI, WRAP, SMETA, ICS, GOTS, and the Higg Index are maintained across the highest-tier factories. Nine of the world’s top ten LEED-certified green factories are located in Bangladesh, a fact that receives essentially no coverage in the Western press despite being a more accurate representation of what the country’s garment industry is capable of producing when it’s resourced to do so. Bangladesh isn’t a country without the infrastructure for ethical production. It’s a country in which that infrastructure is unevenly distributed, and in which Western brands’ sourcing decisions determine which part of the distribution receives their orders.

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The Factory Class System: What Nabihah Found in Chittagong

What the standard Western narrative about Bangladeshi garment manufacturing misses, and what Nabihah found when she spoke to two factory owners in Chittagong, is that the industry has an internal hierarchy that’s poorly understood outside the country and that directly determines the conditions experienced by workers on the floor. The hierarchy isn’t a secret. It’s a feature of how the industry operates, and it’s one that Western brands navigate deliberately when they make sourcing decisions.

The highest-ranked factories operating at full international compliance standards maintain proper ventilation, pay workers on time and at the correct rate, adhere to regulated working hours, and hold certifications from multiple international bodies. They’re more expensive to produce in than their non-compliant counterparts, but still considerably cheaper than comparable facilities in Europe or North America. These factories actively court international clients, fly door-to-door to find new buyers, and invest in the client relationships that make compliance economically sustainable. Their business model depends on being chosen specifically for their standards, and they’re competing against factories whose business model depends on being chosen specifically for their price

The second factory Nabihah spoke to operated on an entirely different model. The owner didn’t pay employees on time or in the correct amounts, and reserved the right to slash pay whenever he chose. Workers were expected to remain beyond their scheduled hours without additional compensation, and leaving at the contracted time was treated as a disciplinary infraction. The owner would call workers during their private time and require them to return to the factory at will. Some workers were scheduled seven days a week for twelve hours a day. The factory she toured had no ventilation and no drainage system. When it rained the day she visited, the water flooded the entire floor space, and she had to walk through contaminated water to enter. Inside, there was garbage throughout the production area, and the smell was acute. Every worker she observed was either a woman or a young person. They smiled at her camera, a familiarity that read less like warmth than like complete desensitization to an environment that should have disturbed any visitor

What the compliant factory owner told Nabihah stays with the piece as its central observation: the non-compliant factory’s garments are lower quality, because overworked workers under pressure to meet mass production quotas produce less precise work. The stitching is worse. The finishing is worse. The consistency across a large order is worse. And yet major Western corporations consistently prefer to work with factories like the second one, because the unit price is lower. Compliance costs money and brands are choosing not to pay it, they’re doing so with full knowledge of what that choice produces

Rana Plaza and the Compliance Infrastructure That Followed

The Rana Plaza collapse on April 24, 2013, killed 1,138 workers and injured more than 2,000. It remains the deadliest disaster in the history of the modern garment industry. The building housed five garment factories producing clothing for Western brands including Walmart, JCPenney, The Children’s Place, and Inditex. Virtually all of these companies had supplier standards and employed auditing firms to inspect their factories on a regular basis. None of them identified the structural failures that caused the collapse, because the auditing systems they were relying on weren’t designed to identify them and because the brands hadn’t required anything more rigorous.

Three weeks after the disaster, a group of major brands signed the Accord on Fire and Building Safety in Bangladesh, a legally binding agreement between clothing brands and global unions that established an independent inspection program covering fire, electrical, and building safety. Inspection findings were made publicly available, and improvement plans for underperforming factories were implemented using funds committed by participating brands. The Accord brought crucial improvements to 1,600 factories and is widely credited with preventing mass casualty incidents in Bangladesh since 2013. The nine-story building’s collapse had been preceded by visible cracks in the walls the day before, and workers who flagged the danger were forced into the factories anyway under threat of losing wages. The Accord was the industry’s acknowledgment that self-regulation had failed catastrophically and that legally binding external oversight was the only framework that had any prospect of producing consistent results.

Yet a decade after Rana Plaza, major American brands including Levi’s, Walmart, Amazon, and Columbia Sportswear still hadn’t signed the International Accord, continuing to rely on the same category of corporate-led audits that failed to prevent the original disaster. About one-fifth of Bangladesh’s garment factories still haven’t completed the safety remediation required in the aftermath of Rana Plaza, more than a decade later, and the RSC has reported that the pace of improvement has slowed significantly. The brands that haven’t signed the Accord are the brands whose factories are most likely to be in that non-compliant fifth, and the brands whose workers are most likely to be in conditions similar to what Nabihah documented.

In November 2025, the Bangladesh Garment Manufacturers and Exporters Association publicly urged its members not to comply with newly proposed labor rights monitoring requirements set by the RMG Sustainability Council, which would have expanded oversight beyond physical safety to cover wages, discrimination, and forced labor. The industry body’s resistance to expanded monitoring reflects the same structural incentive the non-compliant factory owner operates on: accountability costs money, and the brands currently sourcing from those factories haven’t made accountability a condition of their orders. Until they do, the incentive to resist monitoring will remain stronger than the incentive to comply with it.

The Feedback Loop: How Western Brands Drive Non-Compliance

The problem Nabihah documented in Chittagong isn’t that Bangladesh lacks the capacity or infrastructure for ethical garment production. It’s that Western companies are consistently choosing the cheaper, less ethical option, and that choice creates a feedback loop that actively undermines the compliance infrastructure that does exist alongside the non-compliant one.

When a major brand places a large order with a non-compliant factory because the unit price is lower, that order finances the factory’s continued operation, subsidizes the owner’s ability to underpay and overwork his workforce, and makes it economically rational for him to continue avoiding the compliance investments that would raise his costs. The compliant factory, which has invested in ventilation, drainage, fair wages, regulated hours, and international certification, gets passed over precisely because of those investments. The market rewards the factory that cuts corners and penalizes the one that doesn’t, and it does so because Western brands are making a deliberate decision to prioritize margin over conditions. That decision is made in sourcing offices in New York, London, and Paris, and its consequences are experienced on factory floors in Chittagong.

The feedback loop extends further: as the compliant factory owner explained to Nabihah, non-compliant factories produce lower-quality garments because overworked and underpaid workers can’t maintain the precision and consistency that good production requires. Brands that choose non-compliant factories aren’t just choosing worse conditions for workers, they’re also, in many cases, choosing a worse product. But the cost difference is significant enough in the short term that the quality trade-off is accepted, and the worker welfare trade-off doesn’t factor into the calculation at all because there’s no mechanism requiring it to.

BGMEA reported that Bangladesh’s RMG exports reached $50 billion in 2024, generating enormous commercial value for the Western brands sourcing from the country. The portion of that value that flows back to the workers producing the garments is determined by which factories get the orders, and which factories get the orders is determined by which brands are willing to pay for compliance. The brands that aren’t are making a specific and documented choice about whose wellbeing they’re willing to trade for their margin, and they’re doing it while allowing the resulting conditions to be understood by Western consumers as a Bangladesh problem rather than a brand problem.

What “Made in Bangladesh” Should Mean

Bangladesh has built, largely without acknowledgment in Western fashion media, a manufacturing infrastructure that includes the world’s largest concentration of LEED-certified green factories, a post-Rana Plaza safety compliance system that has demonstrably prevented mass casualty disasters, and a workforce that’s among the most skilled in global garment production. Meher Garments Ltd. in Pahartali, Chittagong, holds a LEED Platinum certification with a score of 89 points, awarded for exceptional efficiency in energy and water usage alongside eco-friendly production systems. That factory is in the same city where Nabihah walked through contaminated floodwater to enter a factory with no drainage system and no ventilation. Those two realities coexist in Chittagong, and which one a garment passes through on its way to a Western retailer’s shelf is determined almost entirely by what the Western brand sourcing it was willing to pay.

The stigma that attaches to “Made in Bangladesh” in Western consumer culture isn’t without basis, but it misplaces the accountability in a way that serves the brands responsible for the conditions. The label doesn’t tell you which kind of factory made the garment. It doesn’t tell you whether the brand chose the compliant option or the cheaper one. It doesn’t tell you whether the workers who made it were paid on time, allowed to leave at a reasonable hour, or working in a building with adequate ventilation. Those distinctions are determined entirely by the sourcing decisions of Western brands, and Western brands have no structural incentive to disclose them because disclosure would make their choices visible in a way that’s commercially inconvenient.

Bangladesh is an incredible manufacturing hub with some of the best materials and most skilled workers in the garment industry. The ethical production infrastructure exists and it’s operating at a world-class level in factories across the country. The problem isn’t having ethical production: it exists in plenty across Chittagong and the rest of the RMG sector. The problem is which factories the foreign clients are choosing to work with, and why. That’s a Western brand decision, made for Western commercial reasons, and it produces conditions that Western consumers then associate with Bangladesh rather than with the brands whose logos appear on the finished garment.

SSQRD’s platform surfaces brands whose supply chain claims are independently verifiable, a standard that matters considerably more when the alternative is a “Made in Bangladesh” label that could mean almost anything depending on which factory the brand chose and why. The infrastructure for ethical production in Bangladesh is real and it’s extensive. What’s missing isn’t the factories, but the brands willing to pay for them.

OPEN SOURCE by SSQRD

Every 4th of July, the same ritual plays out across American fashion retail; Ralph Lauren drops a red, white, and blue capsule collection, Tommy Hilfiger runs a patriotic campaign, and Levi’s leans into its gold rush origin story. The campaigns always look the same with open fields, American flags, and people who look like they’ve never had a care in the world. The imagery is consistent enough across brands and decades that it functions less like individual marketing and more like a shared national mythology that the fashion industry has agreed to maintain collectively, regardless of what any individual brand’s supply chain actually looks like.

The clothes in those campaigns are manufactured in Vietnam, China, India, and Cambodia. The workers making them aren’t the people in the ads. The American identity being sold is a story, and like most good stories, it requires you not to look too carefully at who wrote it or where it was produced. This piece is about the gap between the American mythology fashion brands sell and the supply chains they actually operate, the legal infrastructure that makes “Made in USA” one of the most regulated and most violated claims in consumer marketing, and what it means that the brands most aggressively performing American identity are often the ones with the least American manufacturing footprint.

What “Made in USA” Actually Means

The FTC’s “all or virtually all” standard for Made in USA claims requires that a product’s final assembly or processing occur in the United States, that all significant processing occur in the United States, and that all or virtually all ingredients or components be made and sourced in the United States. It’s a high bar, and the majority of American fashion brands can’t clear it for the vast majority of their products. The standard has existed for decades, but it’s become significantly more consequential in the past five years.

The FTC finalized its Made in USA Labeling Rule in August 2021, making companies subject to civil penalties if they use an unqualified Made in USA label on a product that isn’t “all or virtually all” made in the US. Prior to 2021, the standard existed but civil penalties weren’t available, which significantly limited enforcement and allowed brands to make origin claims with relatively low legal risk. The 2021 rule changed that calculus in ways the fashion industry is still adjusting to.

In April 2026, the FTC announced a “Made in the USA” sweep including three law enforcement actions, following a July 2025 warning letter campaign to companies selling American flags and patriotic products that were made entirely in China. One of those actions targeted a company selling American flags with claims including “All-American Made Tough” and “Built by Americans for Americans” whose products were, according to the FTC complaint, wholly imported from China. The specific irony of American flags manufactured in China being sold with aggressive patriotic origin claims is an unusually transparent version of a dynamic that operates throughout the fashion industry with considerably more sophisticated branding to obscure it.

As of December 2025, at least 20 “Made in USA” consumer class actions had been filed, nearly three times the seven filed in all of 2024, indicating that legal scrutiny of American origin claims is accelerating significantly on both the regulatory and civil litigation fronts. The brands most exposed to this scrutiny aren’t the fringe operators. They’re the companies that have built their entire brand identity around American mythology while manufacturing almost nothing in America!!!

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Ralph Lauren: “The American Dream” Manufactured Abroad

Ralph Lauren is the most studied case of American brand mythology in fashion, and for good reason. The brand’s identity is built on a version of America that never quite existed: Hamptons estates, polo matches, Western ranches, all of it wrapped in a visual language that suggests inherited wealth, leisure, and a relationship to the land that’s entirely aspirational. As one analysis of the brand’s strategy puts it, Ralph Lauren sells “as much as it sells clothing and home accessories; the mythology is a key to the company’s success,” and that mythology has proven remarkably durable across five decades and multiple economic cycles.

Ralph Lauren has manufacturing facilities on five continents, with a high concentration in China, Vietnam, India, Italy, and Cambodia. The brand has diversified its sourcing footprint over the past seven-plus years so that no single country accounts for more than 20% of production, a supply chain strategy designed to manage tariff risk rather than to support domestic manufacturing. This diversification happened in direct response to trade policy uncertainty, not out of any commitment to the American production values its marketing imagery implies.

The brand’s own CEO described its global sourcing and supply chain as “agile and well-positioned,” noting that Ralph Lauren has “navigated tariffs successfully before”, which is an accurate description of a sophisticated global manufacturing operation and a notable distance from the imagery of American craftspeople and domestic production that the brand’s marketing has always implied. The language of supply chain agility and tariff navigation belongs to a different conversation than the language of polo players and Hamptons summers, and the brand has been careful never to let those two conversations intersect publicly.

The founder’s own story is American in the meaningful sense: Ralph Lifshitz was born in 1939 in the Bronx to Polish Jewish immigrants, worked out of a drawer in the Empire State Building, and built a multi-billion dollar company from nothing. The irony is that the actual American story, an immigrant’s son building something from scratch, is considerably less visible in the brand’s marketing than the WASPy mythology of polo clubs and East Coast estates that the clothes are used to sell. The real rags-to-riches narrative is less aspirational to the target consumer than the inherited-wealth fantasy, so it gets minimized.

Tommy Hilfiger: The All-American Brand That Went Entirely Overseas

Tommy Hilfiger has evolved over the last 20 years from an all-American brand to one that now manufactures almost exclusively in foreign countries, especially China and India. The brand’s aesthetic identity, which was built explicitly around American preppy culture and remains so, hasn’t shifted meaningfully even as its manufacturing footprint has moved almost entirely offshore. The flag imagery is still there. The red, white, and blue color palette is still the primary visual identity. The clothes are made somewhere else.

The timeline of that shift is interesting, Tommy Hilfiger’s 1990s peak coincided with the brand becoming a significant part of hip-hop and streetwear culture, embraced by communities whose relationship to the “all-American” identity the brand was selling was considerably more complicated than the preppy imagery implied. The brand’s adoption by Black communities in particular involved a cultural remixing of its imagery that the brand subsequently commercialized, building marketing campaigns around a cultural resonance it hadn’t created and didn’t fully understand. The brand’s cultural credibility in that period came from communities whose relationship to American national mythology was defined by exclusion rather than aspiration, a dynamic that the patriotic branding was never designed to acknowledge.

The shift to overseas manufacturing happened quietly, without the patriotic branding changing in any corresponding way. The stars and stripes still appear on the website. The “American” in the brand’s cultural identity is still the primary selling proposition, and the factories are in China and India. Most consumers who buy Tommy Hilfiger for its American identity aren’t aware of that disjunction, and the brand has no particular incentive to make them aware of it.

Levi’s and the “American Original” Claim

Levi’s occupies a particular place in this conversation because its origin story is specifically American in ways that Ralph Lauren’s and Tommy Hilfiger’s aren’t. The Levi’s 501 was invented in 1873 as workwear for California miners and ranchers, and the brand’s association with American working-class labor history isn’t invented mythology. It’s a documented fact rooted in a specific historical moment in American economic history. That foundation makes the gap between the origin story and the current manufacturing reality particularly significant.

Levi’s produces the overwhelming majority of its garments outside the United States, primarily in countries including Bangladesh, Cambodia, Vietnam, Pakistan, and Sri Lanka. The “American original” framing in its marketing is historically accurate about the 501’s invention and culturally misleading about who’s making the jeans being sold today and under what conditions. The brand that was created as workwear for American laborers is now produced by laborers in countries where wage and safety standards bear no resemblance to what American workers are entitled to, and the marketing doesn’t engage with that gap in any substantive way.

Levi’s has faced documented labor concerns in its overseas supply chain, including reports of wage violations and unsafe working conditions in contracted factories, which exist in tension with the brand’s longstanding association with American workers and labor rights. The brand’s current marketing leans heavily into its heritage and its association with American counterculture and working-class identity, while the supply chain producing those garments operates under conditions that the brand’s own historical values would not endorse.

The Legal Architecture of Patriotic Branding

The difference between what brands say and what they do isn’t primarily a moral failure. It’s a legal architecture, and understanding how that architecture works explains why the difference persists despite being publicly visible and extensively documented. The FTC’s Made in USA standard applies to unqualified claims. A brand can use American flags, frontier imagery, and overtly patriotic marketing without making a specific “Made in USA” claim, and the FTC has no jurisdiction over the cultural associations those choices create. Patriotism is legal, but a flag on the label is not, unless the product actually qualifies.

This means a brand can run a 4th of July campaign featuring the American flag, American landscapes, and American cultural imagery, manufacture all of the products in that campaign in Vietnam and China, and be in complete legal compliance, as long as it doesn’t put “Made in USA” on the label of a product that isn’t. The cultural claim and the legal claim operate in entirely separate regulatory spaces, and the fashion industry has spent decades taking full advantage of that separation.

Williams-Sonoma paid a record $3.17 million civil penalty in April 2024 for violating a prior FTC order related to false Made in USA claims, representing the most significant enforcement action in the apparel and home goods space in recent years. The penalty is substantial in absolute terms and negligible relative to the revenue generated by the misleading claims over the period they were made. A company that spent years selling products at a premium on the basis of American origin claims it couldn’t substantiate, and then settles for $3.17 million, has still run a commercially profitable operation.

What “American” Actually Means in 2026

The 4th of July is a useful moment to examine what American identity in fashion is actually selling and to whom. The version of America that Ralph Lauren, Tommy Hilfiger, and Levi’s market is one of aspiration, leisure, and a relationship to the landscape that’s available to a relatively narrow demographic. Academic analysis of Ralph Lauren’s advertising has consistently noted that the brand’s American Dream imagery centers white affluence, with communities of color appearing as peripheral figures in a narrative whose protagonist is implicitly the wealthy white American male. The “American” being sold is a specific and exclusive version of the country, and it’s one that has remained remarkably consistent across decades of demographic change in the actual United States.

The workers manufacturing the clothes in those campaigns are in Cambodia, Vietnam, and Bangladesh, countries whose relationship to American foreign policy and economic history is complex and rarely examined in the context of fashion brand patriotism. The American flag on a polo shirt made in a Vietnamese factory carries a specific kind of historical weight that the brand’s marketing isn’t designed to engage with. The 4th of July campaign exists to sell clothes and the supply chain that produced those clothes exists to minimize cost. The American mythology connecting the two exists to make consumers feel that buying the shirt is a participation in something meaningful rather than a transaction that benefits a global manufacturing operation with no particular relationship to the identity being sold.

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Fashion has always borrowed from screen culture, but something changed when streaming platforms replaced broadcast television and algorithmic recommendation replaced the programming schedule. The relationship between what people watch and what they buy is no longer being observed by fashion brands after the fact. It’s being engineered in advance, and the platform doing most of that engineering is one most people still think of primarily as a place to watch TV.

Netflix reaches over 300 million subscribers globally, generating behavioral data at a scale and granularity that no predecessor media format could match. Members watched over 94 billion hours on Netflix in the second half of 2024 alone, and the platform knows not just what they watched but when, for how long, what they rewatched, where they paused, and which thumbnails drew them in initially. That behavioral dataset is now being connected directly to fashion retail infrastructure in ways that fashion press coverage has been ignoring.

The argument of this piece is as follows: Netflix is no longer simply a platform that influences fashion trends as a cultural byproduct of popular storytelling. They’ve built commercial infrastructure that converts viewing behavior into targeted fashion commerce, with costume departments functioning as de facto trend forecasting operations and viewing data functioning as the market research that tells brands which aesthetics will convert before those aesthetics surface anywhere else.

The Netflix Effect

The Netflix Effect, the documented phenomenon by which a show’s costumes generate measurable spikes in retail search and purchase behavior, has been visible since at least 2020. Bridgerton’s first season caused searches for “floral print dresses” to rise 146% and searches for “regency dresses” to rise 84%, according to e-commerce aggregator Love the Sales. Wednesday caused Depop searches for Wednesday-inspired outfits to increase by 1,000% in December 2022. Emily in Paris caused searches for “Jacquemus cardigans” to rise 18% and “Ganni bags” to rise 15% month-on-month following its fourth season in 2024. The pattern has been consistent enough across enough shows and enough years that describing it as coincidence stopped being credible.

What the press has largely treated as an interesting cultural phenomenon, audiences buying clothing inspired by characters they love, is from Netflix’s perspective a commercial signal with significant monetization potential. The platform has spent the years since Wednesday and Bridgerton building the substructure to capture that signal directly, rather than watching it flow to retailers who weren’t paying for it. The Google Lens partnership is the most visible expression of that strategy, but it’s not the beginning of it, and definitely not the end.

From Cultural Influence to Commerce Infrastructure

In August 2024, Netflix and Google announced a shoppable integration built around the fourth season of Emily in Paris. The partnership allowed viewers on all Netflix plans to use Google Lens technology to scan looks worn by the show’s characters directly on their screens, with the scan directing them to similar items available for purchase. For viewers on Netflix’s ad-supported tier, the integration went further: shoppable pause ads encouraged members to scan the paused image on screen using Google Lens, routing them to a shopping page without leaving the viewing experience.

This was the first time Netflix built a direct transactional bridge between a specific show’s costumes and the purchase infrastructure of a major retail platform. The Emily in Paris wardrobe, curated by costume designer Marylin Fitoussi, was no longer simply influencing what viewers searched for after an episode ended. It was a shoppable catalog available in real time, mid-viewing, requiring nothing more than a phone scan. The fiction and the fitting room, which had always been adjacent in fashion culture, were collapsed into a single interface.

The partnership also marked the first time Netflix executed title sponsorships on existing library content, with Google serving as title sponsor for not just season four but the previous three seasons retroactively. Google’s shopping infrastructure is now attached to content that was produced years before the partnership existed, converting an entire show’s archive into a commerce channel without changing a single frame of the original. A viewer who discovered Emily in Paris through Netflix’s recommendation algorithm in 2023 and decided to rewatch it in 2025 is now navigating a show that has been commercially instrumented in ways it wasn’t when they first saw it.

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The Ad Tier and the Data Behind It

Netflix launched its ad-supported subscription tier in late 2022 and has since grown it to more than 190 million monthly active viewers globally as of late 2025. The significance of this growth for fashion brands is not primarily the audience size, though 190 million is a substantial number. The significance is the data infrastructure that the ad tier required Netflix to build, and what that infrastructure now makes possible for advertisers with the budget and sophistication to use it.

At its May 2025 Upfront presentation, Netflix unveiled the Netflix Ads Suite, its in-house advertising platform, and announced that advertisers could now incorporate their own first-party data through LiveRamp or directly with Netflix to match datasets for behavioral insights and targeting against Netflix’s audience. Netflix also opened third-party data access to partners including Experian and Acxiom, and announced a clean room strategy for data collaboration and partnerships. A fashion brand can now bring its own customer data to Netflix, match it against Netflix’s viewing behavioral data, and build targeting strategies around the resulting combined profile in an environment where neither party has to share raw data with the other directly.

In September 2025, Netflix made its inventory available programmatically through Amazon’s demand-side platform, giving buyers access to Amazon Audiences, which are segments built from Amazon’s shopping, streaming, and browsing signals. A fashion brand advertising on Netflix can now layer Amazon’s purchase history data on top of Netflix’s viewing behavioral data to identify and reach consumers whose watching habits align with their purchasing patterns. Categories in which Amazon’s purchase data is particularly relevant, including apparel, are specifically identified as well positioned to benefit from this integration. The viewer who binged three seasons of Emily in Paris and purchased a Ganni bag on Amazon is now a targetable profile that a fashion advertiser can reach with a campaign specifically designed for someone whose viewing and purchasing behavior fit that pattern.

The Costume Department as Trend Forecaster

The commercial infrastructure Netflix has built around its content changes the role of the costume department in ways the industry has not yet fully articulated in its coverage of either fashion or media. Costume designers have always influenced fashion, but historically that influence was indirect and unquantifiable. A costume became a trend when audiences responded to it emotionally and then expressed that response through purchasing behavior, a process that played out over months and was observable only in retrospect, through retail data and social media trend reporting that lagged significantly behind the actual moment of cultural resonance.

What Netflix’s viewing data does is make that process visible in real time and in advance. The platform knows which scenes viewers rewatch, which character’s wardrobe generates the most pause-and-search behavior, and which aesthetic directions are resonating with which demographic segments before any of that data surfaces in retail search terms or social media trend reporting. A costume designer working on a Netflix show whose aesthetic choices are generating unusually high engagement signals in early viewing data is, in practical terms, a trend forecaster with access to market research that no independent forecasting agency, including WGSN or Heuritech, can replicate from the outside.

Netflix spent approximately $17 billion on content in 2024, and every production decision, including costume budget and aesthetic direction, is informed by behavioral data from previous content. The shows that get greenlit, the characters that get costumed in specific ways, and the aesthetic worlds that get built with significant production investment are all downstream of what the data shows about audience engagement and conversion potential. When Bridgerton’s corseted silhouettes generated the retail response they did, that signal fed back into decisions about which shows to commission next and how to costume them. The trend forecasting and the content production have become mutually reinforcing, with viewing data connecting the two in a feedback loop that operates at a speed and scale the traditional fashion industry’s forecasting infrastructure was not designed to compete with.

What This Means for Independent Designers and Smaller Brands

The infrastructure Netflix has built systematically advantages the brands with the largest advertising budgets and the most sophisticated data operations. Categories in which Amazon’s purchase data is particularly relevant, including apparel, are well positioned to benefit from the Amazon Audiences integration with Netflix’s ad tier, which in practice means the brands already selling at scale on Amazon are the ones best positioned to convert the viewing behavioral data Netflix is generating into targeted fashion commerce. The brands that can afford to participate in Netflix’s data clean room partnerships are the brands that already have the customer data infrastructure to bring to those partnerships.

An independent designer whose aesthetic is resonating with viewers of a Netflix show has no access to the data showing that resonance, no mechanism to be surfaced in the Google Lens shopping results that the show’s pause ads direct viewers toward, and no budget to participate in the data partnerships that would allow them to match their customer profiles against Netflix’s audience. They will observe the trend their aesthetic helped inspire showing up in retail search data weeks or months after the fact, by which point the brands with the infrastructure to act on early signals have already produced and marketed their version of it. The pattern documented in Open Source’s earlier piece on the clean girl aesthetic and quiet luxury, in which cultural practices originate in communities without capital and are later commercialized by brands with the resources to move quickly, now has a new and considerably more technically sophisticated accelerant operating inside it.

Netflix’s ad-supported tier now accounts for over 45% of sign-ups in all markets that carry the offering, meaning the majority of new Netflix subscribers are entering an environment where the content they watch is directly connected to commerce infrastructure they have no particular reason to be aware of. The platform that most intimately captures what people find aspirational, through sustained emotional engagement with characters and narrative worlds built with the explicit goal of generating that engagement, has built a monetization layer that converts that aspiration into targeted retail transactions. The shows themselves are not changing, it’s the foundation running underneath them, and the brands best positioned to benefit from it are the ones with the most capital to invest in the data partnerships that make the infrastructure useful.

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Fast fashion’s environmental damage in the Global South is extensively documented. Every week, 15 million secondhand garments arrive at Ghana’s Kantamanto Market from the Global North, and 40% of those imports, roughly 6 million items weekly, are immediately discarded as waste. According to the UN Environment Programme, Africa receives an estimated 4 million tons of used clothing annually, with significant portions ending up in landfills or clogging waterways. The communities managing this waste are the same communities these brands are now actively recruiting as micro-influencers through affiliate programs requiring as few as 300 followers to join. The argument of this piece is specific: fast fashion brands, most prominently Shein, have built influencer recruitment infrastructure deliberately designed to penetrate markets in the Global South, converting local creators into paid brand advocates in the same regions where their overproduction is creating an environmental and public health crisis.

How the Influencer Infrastructure Is Built

Shein’s influencer program is available in 150+ countries, with the application process accessible through its mobile app to anyone with a social media presence. The entry bar is deliberately low: Temu requires applicants to have as few as 300 followers to qualify, while Shein offers tiered affiliate rates of 10% to 20% on sales generated, with monthly bonus incentives for high performers and early access to sales for top campaign contributors. The compensation structure is designed to motivate sustained, recurring content production rather than one-off promotional posts, because what Shein is building is not a campaign but a persistent presence in the feeds of consumers across global markets.

Shein mainly partners with micro-influencers, often individuals with a modest following on Instagram, YouTube, or TikTok. In exchange for their posts, these influencers receive complimentary product deliveries every month alongside their commission earnings, creating an ongoing material relationship between the creator and the brand that makes sustained promotion financially rational even for creators who would otherwise be unlikely to endorse a company with Shein’s documented record. Storyclash data shows that 27% of Shein’s Instagram collaborations are long-term, meaning the brand is building sustained relationships rather than one-off promotions, and that those relationships create ongoing reputational cover that compounds over time rather than dissipating after a single campaign cycle.

The geographic distribution of this influencer network is an undiscovered dimension of Shein’s marketing strategy. The program’s availability across 150 countries means it is actively recruiting creators in the same African, South Asian, and Southeast Asian markets where the brand’s textile waste and labor practices are most acutely felt by local communities. The brand is not simply expanding its marketing reach globally. It is specifically penetrating the markets where its reputation is most at risk and where its environmental and labor practices have the most direct local consequence.

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The Guangzhou Factory Trip: The Most Documented Example of the Strategy

In June 2023, Shein flew out a group of American influencers to its manufacturing facilities in Guangzhou, China, on an all-expenses-paid trip. The influencers posted videos praising the working conditions, with one, Dani Carbonari, describing herself as an “investigative journalist” and saying she was “excited and impressed to see the working conditions.” Their videos on TikTok and Instagram attempted to debunk what some of them called “rumors” about forced labor and low pay at Chinese factories, with one creator noting that workers “weren’t even sweating” at the facility she toured.

The timing is important contex: Channel 4’s 2022 documentary “Inside the Shein Machine: UNTOLD” had brought hidden cameras into Shein’s Guangzhou factories and exposed workers working up to 18-hour days, paid around two cents per item, with one day off per month. A Wired investigation had found that 12% of Shein’s audited suppliers had committed “zero tolerance violations” including underage labor, forced labor, or severe health and safety issues. Public Eye, a Swiss human rights watchdog, had found that several Shein factories lacked safe working conditions and subjected workers to 75-hour work weeks. The influencer trip was not a spontaneous gesture of transparency. It was a deliberate response to a documented and mounting reputational crisis.

Experts noted the trip marked a significant departure from standard influencer marketing practice: rather than simply promoting products, the influencers were being asked to attest to the company’s labor practices and ethical standing, effectively functioning as PR consultants for the brand’s response to documented human rights allegations without the expertise, access, or independence that credible assessment of those allegations would require. The backlash was substantial and immediate. Bloomberg described the trip as “a case study in the sort of audience engagement that’s best avoided”, and the influencers involved faced significant criticism from their own audiences.

The Guangzhou trip targeted a Western audience that was already skeptical and already engaging with the investigative coverage that had preceded it. The micro-influencer affiliate network Shein has built across developing markets targets something categorically different: audiences in the communities directly experiencing the consequences of the brand’s production model, reached through creators whose local credibility and modest following size makes their content read as organic rather than sponsored.

Waste Colonialism: What’s Actually Happening in the Markets Being Targeted

Ghana’s Kantamanto Market, the largest secondhand clothing hub in West Africa, receives 15 million items of clothing weekly from the Global North. On January 1, 2025, a catastrophic fire tore through the market, devastating nearly 75% of it and leaving over 10,000 traders without their businesses, merchandise, or tools. The fire compounded a crisis that was already severe: the market’s traders had been managing an escalating volume of unsellable, low-quality garments from the Global North for years, with a growing proportion arriving from Chinese fast fashion manufacturers whose overproduction has accelerated the scale of the problem.

In Kenya, Nigeria, Tanzania, and South Africa, similar dynamics are playing out. Illegal dumping occurs along water sources near secondhand textile markets including the banks of Korle Lagoon in Ghana and Nairobi River in Kenya, creating public health consequences for communities that had no role in generating the waste they are managing. Researchers and advocacy organizations have named this dynamic waste colonialism: the environmental and social costs of waste driven by consumption habits in wealthier nations are disproportionately borne by communities in the Global South who did not produce it and have no meaningful mechanism to refuse it.

The brands whose overproduction is fueling this crisis are the same brands whose affiliate programs are now recruiting micro-influencers in Accra, Nairobi, Lagos, and Manila to promote their products to local audiences. The communities bearing the environmental cost of fast fashion’s excess are being enrolled as its marketing infrastructure, generating content that promotes the same consumption model producing the waste.

The India Expansion: A Case Study in Simultaneous Exploitation and Recruitment

Shein’s plan to increase its Indian supplier base from 150 to 1,000 factories within a year has raised significant concerns among human rights advocates, particularly given the conditions that have been documented in its existing supply chain in China. BBC and Public Eye investigations found that many workers in Shein-contracted factories endure shifts of 10 to 12 hours a day, paid per piece, earning less than a dollar per garment, with base wages falling well below the recommended living wage. Those are the conditions documented in China. The expansion into Indian manufacturing raises the reasonable question of whether the same pressures that produced those conditions will accompany the new supplier relationships.

At the same time as expanding its Indian supplier base, Shein has been actively building its influencer presence among Indian creators, recruiting micro-influencers to promote its products to Indian consumers who may be entirely unaware of the labor conditions in the factories supplying those same products. The sequence is consistent with what the Guangzhou trip made visible: Shein expands production in a country, creating documented labor conditions that generate reputational risk, and simultaneously recruits local influencers to generate positive brand content that reaches local audiences before investigative coverage of those conditions achieves comparable reach.

Shein’s 2023 sustainability report itself acknowledged two cases of child labor in its supply chain, a disclosure that received considerably less press coverage than its influencer campaigns in the same period.

What “Disclosure” Looks Like When It Exists at All

Influencer marketing disclosure requirements vary significantly by jurisdiction, and enforcement in many developing countries is either absent or not practically meaningful. A micro-influencer in Ghana or the Philippines promoting Shein products is subject to whatever local advertising standards exist in their market, which in most cases do not require disclosure of paid partnerships in a form that most consumers would recognize as an indication of commercial relationship. The content reaches its audience with the visual and tonal register of a recommendation rather than an advertisement, which is precisely its commercial value to the brand paying for it.

The FTC’s influencer disclosure requirements apply to US-based creators but have no jurisdiction over the global network of micro-influencers Shein has recruited in developing markets. The brand’s affiliate program terms require creators to disclose partnerships, but the enforcement mechanism is the creator’s own compliance, and the brand benefits commercially from content that reaches audiences who don’t register it as advertising regardless of whether the creator has technically complied. The incentive structure does not reward disclosure that diminishes engagement.

The asymmetry compounds across markets. Consumers in Western markets have developed some degree of fluency in recognizing sponsored content, partly due to years of regulatory pressure and media coverage of influencer marketing practices. Consumers in markets where Shein’s affiliate program is newer, where the regulatory framework is weaker, and where investigative coverage of the brand’s supply chain is less accessible are considerably more likely to receive that content without the interpretive context that would allow them to evaluate it critically.

The communities in the Global South who are managing the environmental consequences of fast fashion’s overproduction are, in many cases, the same communities being recruited to extend the commercial reach of the brands responsible for that overproduction, through a marketing model that is designed to look like peer recommendation, operates in regulatory environments that cannot meaningfully govern it, and serves the brand’s interests most effectively precisely when it is least recognizable as advertising.

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I’m the daughter of Afghan immigrants who left Kabul in the 1980s, before the Taliban’s first rise to power. My parents left a country that had been building something: women in universities, girls in schools, a generation of educated Afghans who believed knowledge was the foundation of the future. They also left a country that had been destabilized by decades of superpower interference. A Cold War proxy conflict in which the United States funded, armed, and trained the Mujahideen to fight the Soviet Union, and then walked away when the war was over, leaving behind a collapsed state, a traumatized population, and the conditions that allowed the Taliban to fill the vacuum. Afghanistan’s destruction was not incidental to American foreign policy. It was a foreseeable consequence of it, and the people left behind paid the price for a strategy that was never designed with their well being in mind.

Since seizing power in August 2021, the Taliban have implemented more than 70 decrees targeting the rights of girls and women. Afghanistan is now the only country in the world where girls are banned from secondary and higher education. 2.2 million girls are currently barred from attending school beyond the primary level. I’ve been thinking about this alongside Elizabeth Spiers’ recent piece in The Nation on Silicon Valley’s anti-intellectualism, and the comparison I keep returning to is one that will make some readers uncomfortable: the structural logic propelling Silicon Valley’s war on education is not categorically different from the logic driving the Taliban’s. Both are projects of powerful men who understand, whether consciously or not, that an educated population is a population that asks questions, organizes, and becomes harder to control. The methods may be different, but the underlying fear is the same.

What the Taliban’s Education Ban Is Actually About

The Taliban’s justification for banning girls from school has shifted repeatedly since 2021, citing dress codes, Islamic law, culture, and administrative readiness as the rationale at various points. One senior official insisted the Taliban had not reneged on promises to reopen schools but needed more time to decide on a school uniform for teenage girls, a justification so transparently inadequate that it functions as evidence of the pretextual nature of the entire project. The stated reasons keep changing because they were never real.

Of the total 80 edicts issued by the Taliban until January 2023, 54 specifically target women. The education ban is not an isolated policy. It’s one component of a comprehensive project to remove women from public life, from economic participation, and from the ability to accumulate the knowledge that makes civic engagement and organized resistance possible. An educated woman is a woman with options. She can evaluate the conditions of her own life, understand her legal rights, participate in professional and civic institutions, and articulate demands. The Taliban’s education ban is not primarily about religion or culture. It’s about eliminating the conditions under which women can contest their own subordination, dressed in the language of religious obligation because that framing is the most politically durable one available to the men imposing it.

Before the Taliban’s return to power in 2021, from 2002 to 2021, 3.8 million girls enrolled in grades one through twelve, and over 100,000 Afghan women were enrolled in universities. The Taliban didn’t close schools through gradual policy reform. They dismantled two decades of educational progress in a matter of months, because that progress represented the most direct and credible threat to their authority. An educated Afghan woman in 2021 was someone who had spent twenty years accumulating exactly the kind of knowledge and institutional access that makes authoritarian control difficult to sustain.

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Silicon Valley’s Parallel Project

The Silicon Valley version of this project arrives with considerably better branding, but the underlying structure is recognizable to anyone who has spent time thinking about who benefits when large portions of the population become less educated, less analytically capable, and less able to evaluate the conditions of their own lives critically. Peter Thiel has built a program that subsidizes high school students who want to forgo college. Marc Andreessen has publicly boasted that he actively avoids introspection. Palantir CEO Alex Karp has made the prediction that AI will hurt educated women the most, framing a structural displacement of women from the workforce not as a problem requiring remedy but as an outcome with a certain satisfaction.

As Spiers notes in The Nation, the irony of this posture is that all of these figures are themselves beneficiaries of elite education. Thiel attended Stanford, Andreessen attended the University of Illinois, and Karp holds a doctorate in social theory from Goethe University Frankfurt. The credential they received is one they now work to deny to everyone else, framed as a service to the people being denied it, a concern for the economic burden of student debt that conveniently aligns with their interest in a less analytically equipped general population.

The argument that higher education is overpriced and overvalued is not wrong in every particular. Tuition costs are genuinely unsustainable and the credential market has real structural distortions. But the tech oligarchs making this argument are not primarily interested in reforming higher education or making it more accessible to the people being priced out of it. They are interested in delegitimizing it as a path to social mobility and critical thinking, because both of those outcomes threaten the concentration of authority they benefit from. As Spiers writes, “an informed populace is a civically active populace. You can’t preach automatic deference before a caste of tech savants to a group of workers schooled in understanding their own role as agents of social progress.” The Taliban arrived at the same conclusion through a different ideological route, but the destination it points toward, a population kept strategically limited in its analytical capacity to serve the interests of those holding power, is a bit obvious across the two contexts.

Why Educated Women Specifically Are the Target

Both the Taliban and Silicon Valley’s tech oligarchs have a specific and documented hostility toward educated women that exceeds their general skepticism of education broadly. The Taliban’s education ban targets girls and women specifically. Boys’ schools reopened in the weeks immediately following the Taliban takeover. The ban on girls’ secondary education was maintained for years, and the justifications for the asymmetry were never coherent on their own terms because they weren’t designed to be.

In Silicon Valley, gender targeting is less legally formalized but structurally present in the pattern of who gets identified as the threat to be neutralized. Alex Karp’s prediction that AI will hurt educated women the most was not framed as a warning or an expression of concern about a regrettable outcome. It was delivered as a statement about the natural order of things reasserting itself, with a register that signals approval rather than alarm. Now that women are getting more master’s degrees than men, it has suddenly become a consensus position in certain tech quarters that graduate education is essentially useless. Right?

The tech oligarchs’ consistent emphasis on physical strength as a meaningful vector for masculine credibility, their dismissal of emotional intelligence and humanistic disciplines as feminine and therefore not serious, and their framing of meritocracy as a system that naturally produces male dominance all draw on the same foundational assumption the Taliban relies on. Which is that women’s subordination is a natural condition rather than a political one, and that education represents a threat to that natural order because it gives women the tools to demonstrate that the entire premise is false.

The Sycophantic Bubble

Both systems ultimately depend on an information environment that insulates the men at the top from meaningful challenges. The Taliban enforces this through law, violence, and the systematic elimination of any institution capable of producing organized dissent. Silicon Valley’s version of this insulation operates through the social dynamics of extreme wealth and the professional incentive structures it creates.

As Spiers writes, tech oligarchs “proceed to surround themselves with yes men and peers who affirm everything they say; the beta version of the cringy displays of great-leader sycophancy that break out in every Trump cabinet meeting was perfected in the boardrooms of Silicon Valley.” The Taliban’s version of this is more physically coercive: dissent is not tolerated, and the information environment is controlled through the elimination of free press, civil society organizations, and educational institutions that could serve as sites of organized opposition.

What makes the Silicon Valley version interesting is that it’s now being exported outward through the tools tech oligarchs are building and deploying to the general population. An MIT Media Lab study titled “Your Brain on ChatGPT” found that LLM users “consistently underperformed at neural, linguistic, and behavioral levels,” and researchers found that nearly a dozen leading AI models were highly sycophantic, taking the users’ side in interpersonal conflicts 49 percent more often than humans did, even when the user described situations in which they broke the law, hurt someone, or lied. The tools designed to replicate the sycophantic bubble the tech oligarchs have constructed around themselves are now being distributed at scale to a population that is simultaneously being told that the educational institutions which might provide a framework for critically evaluating those tools are not worth attending.

A population that is less capable of rigorous independent thought is a population less capable of identifying and articulating its own interests in opposition to those of the people controlling the information environment. This isn’t some sort of conspiracy theory, but rather a description of a structural incentive that applies to both the Taliban and tech oligarchs.

What This Looks Like From Inside

I am writing this as the daughter of people who fled a country that the Taliban and decades of American intervention destroyed not once but twice. The first time, my parents left. The second time, millions of people had nowhere to go, and the international community that had spent twenty years in Afghanistan departed with a speed that made clear how conditional its investment in Afghan futures had always been.

The comparison I’m drawing here is not an equivalence in terms of violence or legal coercion. The Taliban’s methods are brutal in ways that Silicon Valley’s are not, at least within the domestic context where most of the tech oligarchs’ influence is currently exercised. The comparison is about a shared pattern of reasoning: both are projects led by men who have identified education, and specifically women’s education, as the primary threat to their authority, and who are using the levers of power available to them to undermine it while framing that project as something else entirely.

What watching Afghanistan after August 2021 reinforced, is that the dismantling of educational infrastructure does not require decades to accomplish. It happened in Afghanistan within months, and it happened after years in which the conditions for it, the concentration of authority, the elimination of accountability structures, and the cultivation of a population without the institutional access to organize against it, had been developing quietly. The Taliban did not announce in advance that they intended to ban girls from school. They announced the opposite, made promises about reopening schools, and then reversed those promises after girls had already shown up at the gates, having believed the promises because there was no information environment available to them that would have suggested otherwise.

The tech oligarchs are not announcing that they intend to produce a less educated, less civically capable population. They’re framing the process as innovation, as disruption, as concern for working-class people who were failed by elite institutions that charged too much and delivered too little. Those concerns are not entirely invented, but the people most affected by concentrated power have historically depended on access to education and information to identify that power for what it is and to contest it. Anything that systematically reduces that access, regardless of the ideological justification offered for doing so, serves the interests of the people holding the power. It’s true in Kabul and it’s true in Silicon Valley.

OPEN SOURCE by SSQRD

Most people think of Spotify as a music platform. A place to listen, to discover, to build playlists that reflect who you are or who you want to be in a particular moment. That’s exactly what it is, but it’s also, simultaneously, one of the most sophisticated behavioral data operations in the consumer technology industry. And fashion brands have been quietly building their trend forecasting and targeting strategies around it in ways that fashion press coverage has almost entirely ignored.

The data Spotify collects doesn’t require you to see an ad for it to be commercially valuable. Whether you’re a free user or a Premium subscriber, every song you play, skip, save, or add to a playlist generates a data point that feeds into a behavioral profile Spotify maintains and monetizes. The question isn’t whether you hear ads. It’s whether you understand what your listening behavior is being used for, and by whom, before you’ve made a single purchase decision. This piece is about the machinery underneath the platform: how listening data gets converted into aesthetic identity profiles, how fashion brands are using those profiles to test trend viability before anything surfaces on social media, and what it means that the platform most associated with personal musical taste has become one of the industry’s most powerful market research tools.

The Platform That Knows You Better Than Your Friends Do

Spotify collects more first-party behavioral data than almost any consumer app on the planet. Every song played, skipped, saved, or shared generates a data point. The platform knows what users listen to at 6 AM versus 10 PM, whether they prefer discovery or repetition, which moods correlate with which genres, and which life events trigger listening pattern changes. With over 675 million monthly active users across 180+ markets, the behavioral dataset Spotify is generating dwarfs what social media platforms collect through engagement metrics, for a specific reason: unlike a scroll or a like, a listening session is sustained, intentional, and deeply revealing of psychological state. You don’t accidentally listen to a forty-minute playlist the way you accidentally double-tap a photo.

The fashion industry has understood for a long time that music and clothing function as proxies for the same underlying identity signals. Someone’s music taste and their aesthetic sensibility tend to travel together, a relationship that cultural observers have noted qualitatively for decades. What’s new is that Spotify has built an advertising and data infrastructure that makes that relationship quantifiable, targetable, and commercially exploitable at scale. Fashion brands have been quietly building their strategies around it, and the mechanism is considerably more sophisticated than most coverage of fashion marketing has acknowledged.

The Science Behind Why Music and Fashion Are the Same Signal

The intuition that music preference and aesthetic preference are connected isn’t just cultural observation. Research established as early as 2013 found that consumers who share similar music tastes also have similar aesthetic views and emotions, a finding that has been replicated and expanded in subsequent studies examining the relationship between genre preference and consumer identity. The relationship is robust enough that it functions as a predictive tool: knowing someone’s music preferences gives you meaningful information about their aesthetic preferences before they’ve expressed those preferences through any purchasing behavior.

Research into music listening behavior in fashion spaces specifically found that genre, mood, and music agency all significantly affect garment self-association, meaning that the music playing while someone considers a purchase actively shapes how they relate to the clothing and whether they feel it reflects who they are. This finding has direct implications for how fashion advertising on Spotify works: the context created by what someone is listening to when they receive an ad is not neutral. It is actively influencing their receptiveness to the aesthetic being presented.

A Greenbook analysis of Latin American music and fashion trends noted explicitly that “history shows us that by looking at trends in the music industry, we can predict trends in the fashion industry”, a principle that fashion forecasters have applied qualitatively for decades. What Spotify has done is make that principle quantitatively precise. If music preference predicts aesthetic preference, and Spotify has granular data on the music preferences of 675 million users organized by genre, mood, playlist behavior, listening time, and life context, then Spotify has what is effectively a real-time map of aesthetic identity across a significant portion of the global consumer population. That is an extraordinarily valuable asset, and it is one that fashion brands are paying to access.

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What Spotify’s “Streaming Intelligence” Actually Is

Spotify’s advertising infrastructure is built on what the company calls streaming intelligence: first-party, contextual data that reveals listeners’ context in real time, including what they’re doing, how they’re feeling, and what they’re likely to respond to. The term is Spotify’s own branding for what is, in more technical terms, a continuously updated behavioral profile derived from listening activity and cross-referenced with demographic and contextual data.

The technical foundation of this infrastructure traces back to Spotify’s 2014 acquisition of The Echo Nest, a music intelligence startup, for $100 million. The Echo Nest’s AI analyzed audio signals including tempo, key, and mood, alongside user behavior like playlist construction and skip patterns, and cultural metadata drawn from music blogs and reviews. That acquisition gave Spotify not just a recommendation engine but a framework for understanding what listening behavior means about the person doing the listening, which is the conceptual foundation on which everything Spotify’s advertising business does with behavioral data is built.

In practical terms, the platform offers targeting based on listening behavior, demographics, and contextual signals including workout playlists, study sessions, and commute times. For fashion advertisers, this means the ability to reach a user who is listening to a “getting ready” playlist on a Saturday morning, a moment Spotify’s data identifies as high-intent for fashion and beauty purchase consideration, as distinct from the same user on a commute or during a workout. The platform knows the difference, and it sells access to that distinction.

Spotify’s own research found that 71% of listeners surveyed said Spotify helped their purchasing journey, and that fashion buyers specifically displayed the least confidence of any consumer category during the early stages of purchase consideration, making them unusually receptive to external influence during their listening sessions. That specific insight, that fashion consumers are more undecided than any other category of buyer and more susceptible to influence at the point of listening, is the commercial proposition Spotify has been selling to fashion brands for years.

AUX: Spotify’s In-House Music Advisory Agency for Brands

In February 2024, Spotify announced the launch of AUX, its in-house music advisory agency for brands seeking to use music to enrich their campaigns and connect with emerging artists to reach new audiences. For its inaugural campaign, AUX connected Coca-Cola with DJ-producer Peggy Gou, building a long-term partnership spanning live concerts, social media content, branded playlists, and on-platform promotional support. The announcement was covered primarily as a music industry story. Its implications for fashion trend forecasting received no attention.

AUX is the most explicit articulation of what Spotify has been doing implicitly for years: positioning itself as the infrastructure connecting brand identity to musical identity, and charging brands for the privilege of being placed at that intersection. For fashion brands specifically, what AUX represents is a formalized version of the trend-testing function. A brand working with Spotify’s advisory team can identify which emerging artists, genres, or playlist contexts are indexing strongly with the consumer demographic they’re trying to reach and build campaign and collection strategy around those signals before they surface publicly on TikTok or Instagram.

The reason this gives fashion brands a genuine informational advantage is structural. Spotify’s streaming intelligence means the platform is “constantly learning about how people listen in real-time”, which gives AUX clients access to trend signals that are, by definition, ahead of social media. Social media captures what people share publicly, which is already a processed and curated version of their identity. Spotify captures what people listen to privately, which is a leading rather than lagging indicator of cultural shift. A genre cluster that is experiencing unusual growth in private listening on Spotify will typically surface as a visible aesthetic trend on TikTok weeks or months later. Fashion brands paying for AUX access are operating with that lead time built into their planning cycle.

Testing Trends Before They Surface

Spotify’s own advertising case study documentation explicitly describes how a jewelry brand promoting a wedding collection could target users listening to “wedding planning” or “romantic moments” playlists, tapping into a time-sensitive life stage where purchase intent is already high. The same logic, applied to aesthetic trends rather than life events, describes how fashion brands are using playlist data to identify emerging aesthetics before they achieve mainstream visibility.

EasyJet’s “Listen and Book” campaign used Spotify’s streaming intelligence to match listeners with travel destinations based on their music preferences, demonstrating that the infrastructure for matching product recommendations to listening behavior is operational and being actively deployed across consumer categories. Fashion brands are using an identical model to match aesthetic categories to listener profiles, identifying which playlist contexts correlate with which purchasing behaviors and designing collection and campaign strategy around those correlations.

The mechanism works as follows: a brand identifies a playlist category or genre cluster that is experiencing unusual growth in streaming volume among a target demographic. It cross-references that cluster with the behavioral and demographic data Spotify provides to advertisers, identifying which aesthetic directions are gaining traction before that traction becomes visible on social platforms. It then builds product and campaign decisions around those signals with a lead time that independent brands and smaller competitors, who lack the advertising budget to access Spotify’s full data offering, don’t have. Spotify’s machine learning models prioritize ad delivery to listeners who have shown behavior patterns most aligned with completing a transaction, which means the platform is not just a trend signal tool but an active conversion infrastructure: the same data that identifies an emerging aesthetic can be used immediately to target the specific listeners most likely to purchase it.

The Culture Next Report: Spotify Selling Its Data as a Fashion Forecast

Every year since 2019, Spotify has published its Culture Next report, which it explicitly describes as a tool for advertisers to understand how Gen Z is shaping streaming, online culture, and the world at large, and to connect with them in meaningful ways. The report is built directly from Spotify’s streaming data and distributed to its advertising clients. It is, in plain terms, Spotify packaging its users’ collective listening behavior as a cultural forecasting product and selling it to brands.

The 2024 Culture Next report found that Gen Z uses music taste to define how they judge themselves and each other, with Mindshare NeuroLab research noting that “if taste classifies the classifier, my assertion is that music taste more strongly classifies because there’s just so much of it around, in terms of the raw number of songs and the frequency of consumer indulgence.” This is the insight that makes Spotify’s data particularly valuable for fashion trend forecasting: music taste is a stronger and more granular identity signal than almost any other behavioral data point, precisely because it is so abundant and so frequently updated. Every listening session refreshes the profile.

The report is collected from Spotify’s streaming data alongside interviews with Gen Z individuals across the globe and is described by industry analysts as “a powerful and large predictor of culture” for the brands advertising on the platform. What it represents structurally is Spotify operating simultaneously as a consumer platform and as a market intelligence firm, using the data generated by its consumer business to power a B2B forecasting product that its users have no direct awareness of and no meaningful mechanism to opt out of.

The fashion industry has its own trend forecasting infrastructure, including agencies like WGSN and Heuritech, that charge significant fees for early trend signals derived from social media scraping, runway analysis, and consumer surveys. What Spotify offers is a more granular, more current, and more behaviorally grounded version of the same product, derived from what 675 million people are actually listening to rather than what forecasters think they will listen to. The gap between those two sources of insight is the informational advantage that Spotify’s fashion advertising clients are paying to maintain.

What This Means for Users and for the Industry

The data Spotify collects and sells to fashion advertisers is not data that users explicitly provide. It is data generated by the act of listening, classified and packaged into behavioral profiles that users have no direct visibility into and no granular mechanism to opt out of. Spotify’s privacy policy discloses that it collects data including listening history, playlist creation, and inferred user characteristics, and that this data is used to personalize advertising. The disclosure exists. The commercial use of that data as a fashion trend forecasting and targeting tool is not something most users would recognize from reading it, because the privacy policy describes a data use that is functionally much broader and more commercially sophisticated than the language of “personalized advertising” implies.

For the fashion industry, the implications are structural and compound the existing inequities in how the industry operates. The brands with the largest Spotify advertising budgets have access to trend signals that smaller, independent brands do not. Fast fashion companies in particular have the budgets to run ongoing Spotify campaigns, which means they are also receiving ongoing access to the behavioral data that informs what to produce next. An independent designer working without that data infrastructure is, by definition, operating with a later and less precise read on where consumer aesthetic appetite is moving. The platform that most intimately captures the identity formation of its users has structured its commercial offering in a way that systematically advantages the brands with the most capital to spend on it.

The trend cycle that Open Source documented in its piece on the clean girl aesthetic and quiet luxury, in which cultural practices originate in communities without capital and are later commercialized by brands with the infrastructure to move quickly, has a new and underexamined accelerant. It isn’t just that large brands can produce faster. It’s that they have access to a real-time map of where aesthetic appetite is moving before it becomes publicly legible, derived from the private listening behavior of the same communities whose cultural production they’re monetizing. The playlist is a focus group. Most of the people in it don’t know they’re there.

SSQRD’s platform is built on the premise that discovery should surface brands based on their values and product quality rather than on who has the largest advertising budget on a streaming platform. The infrastructure this piece describes is one of the reasons that premise matters more than it might otherwise appear to.

I. The Crisis

We live in an age of permanent crisis.

Housing is increasingly unaffordable, healthcare has become a billing nightmare, we’re entering wars we never chose, and it seems that only big corporations persist in our neighborhoods. Governments around the world are pouring unprecedented amounts into defense technology, while surveillance systems are becoming ordinary features of daily life. Yet the deeper you dig into each issue, the harder it becomes to treat them as independent phenomena.

For decades, venture capitalists and private equity executives have cultivated an image of themselves as builders of the future. Their firms are celebrated for identifying talented founders and accelerating technological progress. But capital does not merely fund innovation. It determines which innovations receive resources and which do not. Every investment is a decision about what kind of world deserves to exist.

In recent years, a striking pattern has emerged across some of the most influential investors in America. The largest checks are increasingly flowing toward systems of extraction and control. A small number of extraordinarily wealthy people have gained enormous influence over the institutions shaping modern life. Their investments help determine where people live, how much they pay for healthcare, which technologies police departments deploy, and what kinds of weapons governments purchase. The consequences of those decisions are often experienced as disconnected frustrations.

But viewed together, they reveal a network of investors whose influence extends far beyond Silicon Valley and into nearly every major institution shaping modern life.

II. The Extraction Billionaires

If there is a single figure who embodies the transformation of everyday life into an asset class, it is Stephen Schwarzman. Through Blackstone, the private equity giant he co-founded, Schwarzman helped build one of the most powerful investment firms in modern history. Following the 2008 housing crisis, Blackstone began buying thousands of single-family homes across the United States, eventually creating Invitation Homes, now the country’s largest owner of single-family rental properties. What was once a cornerstone of middle-class wealth became, in part, another institutional investment strategy.

Housing was only one opportunity. In 2016, Blackstone acquired TeamHealth for roughly $6.1 billion, placing the firm at the center of the American healthcare system. In the years that followed, TeamHealth became a frequent target of scrutiny from lawmakers investigating surprise medical billing and the growing influence of private equity in healthcare. Housing and healthcare are typically discussed as separate crises, but Blackstone’s portfolio illustrates how closely intertwined they have become.

Henry Kravis: Profiting From Captive Markets

Stephen Schwarzman was not alone in recognizing the investment potential of life’s necessities. As the co-founder of KKR, Henry Kravis helped pioneer the modern private equity industry, transforming leveraged buyouts from a niche financial strategy into one of the dominant forces in the global economy. Over the decades, KKR acquired companies across virtually every sector imaginable, but some of its most controversial investments shared a common characteristic: they operated in markets where consumers had little choice but to participate.

One of the clearest examples was Envision Healthcare. In 2018, KKR took the physician staffing giant private in a deal valued at roughly $9.9 billion. At the time, Envision was deeply embedded in the American healthcare system, providing doctors and staffing services to hospitals and emergency rooms across the country. The company would later become a focal point in congressional investigations into surprise medical billing, a practice that left patients facing enormous charges from out-of-network providers despite having little or no ability to choose who treated them during a medical emergency. Lawmakers repeatedly scrutinized Envision’s business model and KKR’s ownership of the company as concerns mounted over the role private equity was playing in healthcare.

Healthcare was not the only sector where KKR’s ambitions collided with public concerns. In 2024, a group of U.S. senators publicly questioned the firm’s acquisition of a massive apartment portfolio, warning that further consolidation of housing under large investment firms could place additional pressure on renters already struggling with affordability. While the circumstances differed from Envision, the underlying dynamic felt familiar. Once again, private capital was flowing toward an essential need with a captive customer base. People can delay buying a new car. They can postpone a vacation. They cannot simply stop needing housing or medical care.

What makes Kravis significant is not any single acquisition. It is the worldview reflected across them. The modern private equity industry has often justified itself as a source of efficiency, arguing that sophisticated investors can improve operations and create value. Yet KKR’s most controversial investments reveal another reality. Some of the safest returns in the economy come from industries where demand is effectively guaranteed. Housing, healthcare, and other necessities offer something every investor desires: customers who cannot walk away.

Orlando Bravo: The Algorithmic Landlord

As the founder and managing partner of Thoma Bravo, one of the world’s largest software-focused private equity firms, Bravo built his fortune by acquiring technology companies rather than apartment buildings or hospitals. On paper, RealPage looked like another software investment. In practice, it became one of the most controversial companies in the American housing market.

In 2021, Thoma Bravo acquired RealPage in a deal valued at roughly $10.2 billion. RealPage provides software used by landlords and property managers across the country, helping them manage everything from leases to pricing decisions. For years, it operated largely outside public attention. That changed when critics, journalists, and eventually federal regulators began scrutinizing the company’s rent-setting products, which allegedly allowed landlords to use shared market data and algorithmic recommendations to determine rental prices. The Department of Justice later took action against RealPage, arguing that aspects of its business facilitated anti-competitive behavior in housing markets. RealPage denied wrongdoing, but the case transformed the company into a national symbol of a growing fear: that software was quietly reshaping the cost of living for millions of renters.

What makes Bravo’s story distinct is that it represents a newer form of power. The company did not need to own housing to influence housing. It only needed to become the infrastructure through which housing was managed. If Schwarzman helped financialize the home and Kravis helped monetize essential services, Bravo’s legacy may be demonstrating how software itself can become a mechanism for shaping markets, extracting value, and influencing the price of everyday life without ever appearing on a lease or mortgage.

Masayoshi Son: Scaling Controversy

Unlike Schwarzman or Kravis, Masayoshi Son did not build his reputation through private equity. As the founder and CEO of SoftBank, Son became famous for deploying unprecedented amounts of capital through the Vision Fund.

Among the fund’s investments was Forward Health, a healthcare startup criticized for prioritizing technology-driven growth over sustainable patient care, and several data-intensive technology companies operating at the intersection of artificial intelligence, surveillance, and consumer information. While SoftBank often framed these investments as bets on the future, critics have argued that the firm’s approach frequently rewarded scale over social impact.

Son’s significance lies less in any individual company than in his willingness to flood capital into sectors before society has fully reckoned with their consequences. When investors can write billion-dollar checks, they don’t just participate in markets. They shape them.

Nigel Morris: Financializing the Housing Crisis

Nigel Morris became one of the prominent backers of EasyKnock, a company that promised homeowners access to their home equity without taking on traditional debt.

The pitch was homeowners facing financial pressure could sell their property to EasyKnock, remain in the home as renters, and potentially buy it back later. Supporters viewed the model as a creative alternative to conventional lending. Consumer advocates accused the company of targeting financially vulnerable homeowners with complex agreements that frequently left them worse off than before. Several lawsuits and regulatory complaints questioned whether customers fully understood the consequences of the transactions they were entering.

EasyKnock emerged during a period when housing was increasingly being treated less as shelter and more as a financial product. Homes became collateral and sources of liquidity to be engineered and monetized. The search for profit increasingly extends beyond owning homes and into creating entirely new financial mechanisms around them.

Modern finance continually searches for ways to extract value from assets people depend on most. For millions of Americans, a home represents stability. For investors, it increasingly represents opportunity.

III. The Surveillance Billionaires

Today’s defense ecosystem increasingly runs through venture capital firms who move seamlessly between Silicon Valley and Washington. Investors speak about innovation, disruption, autonomy, artificial intelligence, and national competitiveness. Yet the result is private capital flowing into technologies designed for surveillance, security, and war.

The transformation has happened remarkably quickly. A decade ago, many Silicon Valley founders viewed defense contracting as an industry to avoid. Today, some of the most prestigious venture firms in the world openly compete to fund the next generation of military and surveillance technology. The industry’s moral center has shifted alongside its capital. And Silicon Valley is no longer the only place where this ecosystem operates.

Peter Thiel: Monetizing Surveillance

Peter Thiel helped create a different vision built around surveillance, intelligence gathering, and state power. As a co-founder and chairman of Palantir, Thiel became one of the earliest and most influential advocates for technologies designed to analyze enormous quantities of data on behalf of governments, intelligence agencies, law enforcement, and military organizations. Palantir’s software has been used by institutions ranging from the CIA to the Department of Defense, placing the company at the center of debates about privacy, civil liberties, immigration enforcement, and modern warfare. For critics, Palantir represented a future in which surveillance was no longer a government function alone, but a highly profitable private industry.

Palantir was only the beginning. Through Founders Fund, Thiel’s venture capital firm, he helped finance a new generation of companies operating at the intersection of surveillance, defense, and security. Among them were Anduril, a defense contractor building autonomous military systems and border surveillance technologies, and Clearview AI, the facial recognition company that became notorious for scraping billions of images from the internet to create one of the world’s largest facial recognition databases. While previous generations of venture capitalists chased social networks and consumer apps, Thiel increasingly directed capital toward technologies designed to monitor, identify, and secure.

Across Palantir, Anduril, Clearview AI, and dozens of related companies, a consistent pattern emerges: the belief that society’s most important problems are best solved through more data, more surveillance, and stronger security infrastructure. In the process, Thiel helped transform technologies that once sat at the fringes of Silicon Valley into one of the venture industry’s fastest-growing and most influential sectors.

Marc Andreessen: Making Defense Tech Mainstream

For years, venture capital preferred to invest in software that promised convenience. Social networks, productivity tools, food delivery apps, and consumer platforms dominated the industry’s imagination. Defense contractors were viewed as relics of an older economy, far removed from the culture of Silicon Valley. That attitude began to change as Andreessen Horowitz emerged as one of the most influential firms in technology investing.

Under Andreessen’s leadership, the firm aggressively expanded into defense, security, and public-sector technology. Andreessen Horowitz backed companies such as Anduril, Shield AI, and Flock Safety, while launching its American Dynamism strategy, an investment thesis built around national security, manufacturing, infrastructure, and government technology. Defense startups became symbols of innovation.

The significance of Andreessen’s role extends beyond any individual company. Unlike Thiel, whose investments often reflected a distinct ideological vision, Andreessen helped institutionalize defense technology across Silicon Valley’s mainstream establishment. His firm did not merely fund companies building military systems or surveillance infrastructure. It helped convince an entire generation of founders and investors that these businesses represented the future of technology itself. As billions of dollars flowed into autonomous weapons systems, predictive surveillance tools, and security platforms, the question was no longer whether Silicon Valley would participate in the defense industry. The question became how deeply it would embed itself within it.

Joe Lonsdale: Building the Defense Startup Ecosystem

As co-founder of Palantir and managing partner of 8VC, Joe Lonsdale occupies a central position within Silicon Valley’s defense technology network. Through 8VC, he has invested heavily in military, logistics, border security, and government technology companies, helping build an ecosystem where venture capital and national security increasingly overlap.

David Ulevitch: Normalizing Surveillance

As a partner at Andreessen Horowitz and one of the architects of its American Dynamism strategy, David Ulevitch has helped direct capital toward companies focused on defense, law enforcement, and surveillance infrastructure.

Trae Stephens: Selling War Like Software

As a partner at Peter Thiel’s Founders Fund and co-founder of Anduril Industries, Stephens built autonomous surveillance towers, military drones, border monitoring systems, and AI-powered defense platforms. His company has secured billions in government contracts and rapidly become one of the most valuable defense startups in the world.

Stephens’ significance lies in how effectively he helped rebrand the defense industry for a new generation of investors. For decades, venture capital largely avoided military technology. Under Stephens and his peers, defense became fashionable again. The result is a venture ecosystem increasingly comfortable treating war, border enforcement, and surveillance not as exceptional government functions, but as growth markets capable of generating venture-scale returns.

IV. The Foreign “Security” Pipeline

If Silicon Valley helped normalize defense and surveillance investing, Israel became one of its most productive talent pipelines.

Over the last two decades, Israel has built one of the world’s most influential cybersecurity ecosystems, producing startups focused on intelligence, threat detection, surveillance, defense, and security infrastructure. Many of these companies were founded by veterans of military and intelligence units, creating an unusually direct relationship between national security institutions and venture-backed technology.

Investors quickly recognized the opportunity. Firms such as Insight Partners, Cyberstarts, Team8, Sequoia Capital, Lightspeed, and Accel poured billions into Israeli-founded cybersecurity companies, helping transform a local startup ecosystem into a global industry. Companies such as Wiz, Cyera, Armis, Checkmarx, Aqua Security, Island, and Recorded Future became some of the most valuable security businesses in the world, attracting enormous amounts of venture capital along the way.

Investors increasingly viewed geopolitical instability as growth opportunities. Entire portfolios were built around the assumption that the world would become more insecure, more monitored, and more dependent on security technologies. In many ways, this represents the logical endpoint of the trends reshaping the broader economy. The same financial system that learned how to monetize housing and healthcare eventually learned how to monetize fear itself.

Gili Raanan: Financing Israeli Defense

Few investors have played a larger role in Israel’s cybersecurity boom than Gili Raanan. Through Cyberstarts, he has backed many of the most valuable security startups of the past decade, helping transform cybersecurity from a specialized industry into one of venture capital’s most lucrative sectors. The more organizations fear cyber threats, the larger the market for companies promising protection. Raanan's portfolio illustrates a broader shift explored throughout this article: security has become not only a public necessity, but a highly profitable investment category.

Jeff Horing: Betting on Cyber Conflict

As a managing director at Insight Partners, Jeff Horing helped oversee investments in some of the most valuable Israeli cybersecurity companies in the world. Insight became one of the dominant financial forces behind the modern cyber-defense industry, backing firms that benefited from rising concerns about cyber warfare, digital espionage, and infrastructure attacks. The success of these companies reflects a reality that appears throughout this investigation: instability can be extraordinarily profitable when your business is selling protection. As cyber conflict becomes a permanent feature of modern life, the market for security continues to expand alongside it.

What makes this ecosystem particularly significant is that some of the largest American venture capital firms have increasingly directed capital toward Israeli cybersecurity and defense-adjacent startups, viewing them as among the most attractive opportunities in technology. Insight Partners, Sequoia Capital, Andreessen Horowitz, Lightspeed, Accel, and others have collectively poured billions into companies founded by veterans of Israeli military and intelligence units.

The relationship is mutually reinforcing. Israeli startups gain access to American capital, customers, and public markets. American investors gain access to technologies developed in one of the world’s most sophisticated security environments. The result is a transnational network connecting venture capital, cybersecurity, intelligence expertise, and defense technology in ways that would have been difficult to imagine a generation ago.

The same financial system that learned how to profit from people’s need for shelter and medical care has discovered another dependable market: foreign relations. As geopolitical tensions rise and digital threats become more pervasive, security itself has become one of venture capital’s most valuable products.

V. The Allocation of Power.

Over time this capital concentration has produced a shift in how power operates. Increasingly, some of the most important decisions shaping daily life are not being made by voters or public institutions. They are being made through capital allocation. Which companies receive funding. Which technologies scale. Which industries attract billions of dollars.

And when enough money flows in the same direction for long enough, it begins to shape the future itself. Perhaps that is the clearest reflection of our current moment. The future is still being funded. The question is what kind of future investors believe is worth betting on.

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OPEN SOURCE by SSQRD

Reformation has built one of the most powerful sustainability brands in fashion. It’s B Corp certified, Climate Neutral certified, beloved by conscious consumers, and priced accordingly, with dresses routinely retailing between $150 and $350. The brand reached $350 million in revenue in 2023 and has been profitable every year since 2016, a commercial success story that is almost always told alongside its sustainability credentials as though the two are inseparable. The brand’s own motto, printed on the wall of its Los Angeles factory, reads: “Being naked is the No. 1 most sustainable option. We’re No. 2.” It’s the kind of line that’s simultaneously charming and doing enormous amounts of brand work, because it positions Reformation not just as a better option but as the best one available while still wearing clothes.

The brand’s own executives describe it as “a walking contradiction” that combines rapid creation with an industry-leading phaseout of virgin synthetics, and they’re right that the contradiction exists. What they’re less forthcoming about is how wide it actually is. This piece isn’t arguing that Reformation is equivalent to Shein. It’s arguing something more specific: that the gap between Reformation’s public positioning and its actual supply chain practices is considerably larger than the price premium it charges consumers to believe there isn’t one, and that the materials, certifications, and factory transparency it points to as evidence of its sustainability credentials don’t fully support the story it’s telling.

The Viscose Problem Nobody Is Talking About

Approximately 50% of Reformation’s garments are made from Tencel and viscose, materials the brand markets as sustainable alternatives to conventional synthetics. This framing does a significant amount of work that the underlying chemistry doesn’t entirely support, and the distinction between Tencel Lyocell and standard viscose is one that Reformation’s marketing consistently blurs.

Tencel Lyocell, produced by Lenzing AG, is made in a closed-loop process that recaptures the solvents used in production, making it a genuinely more sustainable choice than conventional fabrics. Standard viscose, also called rayon, is a different material with a significantly more harmful production process, one that Reformation also uses and which its own fiber rating system grades as a “C” on a scale from A to E. That rating is published on Reformation’s website, buried in its materials glossary. It does not appear on the product pages of the dresses made from it.

Viscose production relies on carbon disulfide, a toxic solvent with a documented occupational health record that is difficult to reconcile with the brand’s stated values around worker welfare. Carbon disulfide is a powerful solvent that has been historically linked to causing serious health conditions in factory workers. There is scientific evidence linking occupational exposure to this chemical to detrimental health impacts from coronary heart disease to leukemia to Parkinson’s and stroke. Not only does the chemical pose an immediate health threat to workers, but it also pollutes surrounding communities, which is part of why viscose production has been consistently relocated to lower-income countries with weaker environmental enforcement. Carbon disulfide has been found to cause severe health impacts in 30% of garment workers, including elevated risk for heart attacks and strokes, and emissions also harm communities around rayon mills, which is why the US decided to move production to the developing world.

Reformation grades viscose as a “C” on its own internal fiber rating scale, which it describes as meaning the material has “some positive attributes but significant concerns.” The positive attribute is that the wood source is sustainably harvested. The significant concerns include the chemical processing, the worker health impacts, and the wastewater pollution associated with production. The brand acknowledges this on a page most consumers will never read, and then sells the garments made from it at prices that imply a materially different supply chain.

The price margin issue is as follows: A viscose dress like Reformation’s Lacey Dress, which retails for $248, would cost somewhere in the ballpark of $8-20 to make, meaning the sustainable brand premium is being applied to a material that shares its production chemistry and worker health profile with the cheapest garments on the market. The markup is not primarily funding better materials, it’s just funding the brand story attached to them.

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The Shared Supply Chain: Reformation and Fast Fashion Are Sourcing From the Same Place

Reformation’s primary sustainable fiber supplier is Lenzing AG, the Austrian company that produces both Tencel Lyocell and LENZING ECOVERO viscose. Lenzing is the correct fiber choice compared to generic viscose mills with no environmental standards, and that distinction is real. But Lenzing is not exclusively a sustainable brand supplier, and the identity Reformation has built around Tencel sourcing is complicated by who else is sourcing from the same place.

Lenzing has run campaigns in partnership with both Reformation and Zara’s Join Life Collection, which incorporated LENZING ECOVERO fibers. Both the TENCEL and LENZING ECOVERO brands stand for environmental responsibility, transparency and quality. The primary material Reformation uses to distinguish itself from fast fashion is sourced from the same fiber supplier as Zara’s sustainability line. The Lenzing certification that Reformation points to as evidence of its material standards is the same certification appearing on Zara garments retailing at a quarter of the price.

Fast fashion brands like Zara and C&A use entry-level TENCEL products at $20-60, while contemporary brands like Reformation and Madewell use TENCEL garments typically priced at $60-150. The same fiber from the same mill is being sold at dramatically different price points based primarily on brand positioning rather than material differentiation. This is not an argument that Reformation’s sourcing is fraudulent. It’s an argument that the sustainability premium consumers are paying is not primarily a material premium. It’s a brand premium attached to a material that Zara is also using, at a fraction of the price, in its own sustainability-labeled collections.

Reformation’s 2023 sustainability report claimed that 97% of its materials were “recycled, regenerative, or renewable,” a figure that requires the brand’s definition of those categories to do considerable work. Standard viscose, a petrochemical-adjacent material with documented worker health impacts, appears to be counted within it. The 97% figure is the number most likely to appear in press coverage of the brand, but the methodology behind it is not.

The Factory List That Keeps Changing

Reformation publishes a facilities list updated on a biannual basis, listing the finished goods factories and subcontractors authorized to produce its garments. The July 2023 version is publicly available, as is an earlier Q4 version, and comparing them shows movement that the brand has not explained. Factories appear and disappear between updates without any accompanying disclosure of why a supplier was removed, whether it failed an audit, whether labor conditions were found to be inadequate, or whether the relationship ended for purely commercial reasons. The list creates the appearance of transparency without providing the substance of it.

Just 3 out of around 30 of Reformation’s suppliers have social compliance certifications such as SA8000 and Fair Trade, which verify fair labor practices, clashing with the brand’s original locally-focused and sustainable identity. SA8000 and Fair Trade certifications require independent verification of wages, working conditions, and labor rights. Without them, a factory’s presence on a brand’s published list is not evidence that the factory meets the standards the brand publicly espouses. It’s evidence that the brand has chosen to work with them.

The California plant produces 19% of Reformation’s products. Operations in China make 53%. The brand’s founding narrative centered on local production in Los Angeles as a distinguishing feature of its ethical manufacturing model. That narrative has been quietly superseded by the reality of its current production footprint, without prominent acknowledgment in its sustainability communications. Reformation has pivoted to a more typical fast fashion model relying heavily on overseas production, often in facilities with concerning labor and environmental issues that go against its supposed values, with the emphasis on local, ethical manufacturing having taken a back seat to costs and scalability.

The B Corp Problem

Reformation holds B Corp certification, which it prominently uses in its marketing and which carries significant weight with the consumers paying its price premium. B Corp is administered by B Lab, a nonprofit that assesses companies across environmental, social, governance, and community impact categories. The certification is widely understood by consumers as a meaningful third-party endorsement of a company’s practices. The recent history of B Corp certification in fashion suggests that understanding may need to be revised.

Fast fashion brand Princess Polly was recently certified as a B Corp, fueling criticism that the model has weak standards that allow for greenwashing, prompting B Lab to update its standards with mandatory minimum requirements across seven impact areas. The certification of an ultrafast fashion brand under the same standard as genuinely sustainable labels prompted one of B Corp’s most prominent members to leave the organization entirely. Dr. Bronner’s, the top-scoring natural soap brand in North America, walked away from B Corp certification last year, citing standards it considered too easy to game: “Sharing the same logo and messaging regarding being of ‘benefit’ to the world with large multinational CPG companies with a history of serious ecological and labor issues, and no comprehensive or credible eco-social certification of supply chains, is unacceptable to us.”

Reformation lacks Fair Trade certification, which would provide independent verification of fair wages and safe conditions for workers across its supply chain. The brand’s own sustainability reports acknowledge this gap. The B Corp certification it holds does not fill it. New B Corp standards are being implemented in direct response to the Princess Polly controversy, and recertification, required every three years, will put compliance to the test. Whether Reformation’s certification holds under the updated standards, given that 53% of its production now takes place in China with only 3 of its 30-plus suppliers holding independent labor certifications, will be a meaningful data point.

The Consumption Model Contradiction

The most fundamental tension in Reformation’s sustainability positioning is one the brand itself has named but not resolved. Releasing new styles weekly, operating on a one-month concept-to-production timeline, and running a business model built on repeat purchases is structurally incompatible with the kind of reduced consumption that genuine environmental sustainability requires. The brand is not slow fashion. It has never claimed to be. But the sustainability premium it charges implies a relationship between price and impact that its production model cannot sustain.

Reformation’s collaboration with ThredUp, in which customers receive shopping credit for returning pre-loved Reformation items, gained a net benefit of 1.2 million USD through the partnership, which encourages repeat purchases and revenue growth as customers return to the platform to buy new items. A take-back program that generates new purchase incentives is a circularity initiative and a customer acquisition tool simultaneously, and it’s worth being honest about which function is driving the economics of the partnership. The garments being returned to ThredUp are, in many cases, viscose dresses with a limited lifespan that required dry cleaning throughout their use, an energy-intensive process that Reformation’s own sustainability documentation acknowledges but does not factor into its RefScale product footprint calculations.

One Harvard Business School analysis concluded that Reformation’s entire angle is “simply to try and offset their company positioning of consumable goods” and that the brand is producing items “that are not meant to be kept for a lifetime” and is “a slightly better version of Zara.” Critics argue that promoting products as fully “sustainable” while operating a business model that releases new collections every few weeks knowingly fuels overconsumption, fundamentally undermining sustainability’s core principles. Reformation is a better version of fast fashion. That is meaningfully different from being sustainable fashion, and the price premium it charges positions it as the latter.

What Honest Sustainability Reporting Would Look Like

What Reformation is doing with RefScale, its per-product carbon and water tracking system, is more than most brands in its category offer, and that’s worth saying plainly. Publishing a factory list, however incomplete, is more than Zara does. Committing to Lenzing-certified fibers over generic viscose mills is a real choice with real supply chain implications. None of that is nothing.

The problem is that Reformation’s public positioning has consistently outpaced what the underlying data can support, and the price premium consumers pay is calibrated to the positioning rather than the data. A brand that grades its most-used fabric a “C” on its own scale should not be marketing that fabric as a sustainable alternative without prominent disclosure of that grade. A brand that produces 53% of its garments in China, with only 3 of 30-plus suppliers holding independent labor certifications, should not be centering local ethical production in its founding narrative without updating that narrative. A brand whose factories appear and disappear from its published list without explanation is not offering transparency. It’s offering the structure of transparency, which is a different thing.

Meaningful sustainability reporting would require brand-level rather than aggregate disclosure, independent verification of fiber and factory claims, transparent explanation of supplier changes with substantive reasons rather than quarterly document updates, and a consumption model that doesn’t structurally depend on new purchases to fund its circularity programs. Reformation is better than most. It is not what it says it is. Those two things can be true at the same time, and the price premium it charges consumers suggests it has a significant financial interest in making sure only the first one gets discussed.

SSQRD surfaces brands whose sustainability claims are independently verifiable and whose business models don’t depend on the consumer buying more to fund their sustainability programs. If you’re looking for brands whose practices more closely match their positioning, that’s a reasonable place to start.

OPEN SOURCE by SSQRD

Fashion brands publish annual sustainability reports, launch recycled collections, and announce net-zero commitments with considerable press coverage. The language is consistent across the industry: circularity, conscious consumption, responsible sourcing, science-based targets. It arrives in beautifully designed PDF documents, in press releases timed to coincide with Earth Day or Fashion Revolution Week, and in campaign imagery that tends to feature natural light and linen. It’s a communications category as developed and strategically managed as any other.

The apparel industry remains the world’s least regulated major industry, and that condition is not accidental. The European Commission found that 53% of green claims in consumer goods provide ambiguous, misleading, or unsubstantiated information, and that 50% of all green labels lack robust verification processes. The industry producing the most sustainability content is also the industry least accountable for whether any of it is true.

The argument here isn’t that every sustainability initiative in fashion is fraudulent. Some brands are doing meaningful work. The argument is more specific: the infrastructure of sustainability communication in fashion has been deliberately constructed to satisfy public expectation without triggering regulatory obligation. It’s worth understanding who built that infrastructure, and who benefits from it staying exactly as it is.

What a Shell Initiative Actually Looks Like

A shell sustainability initiative follows a recognizable pattern. It’s real enough to generate press, vague enough to avoid accountability, and structured to report at the group level rather than the brand level, which makes independent verification nearly impossible. It announces targets set far enough in the future that the executives who set them won’t be in their roles when the deadline arrives. It produces annual reports that show directional progress without disclosing the methodology used to calculate it.

Academic research examining the environmental reports of LVMH and Kering found inconsistencies due to a lack of brand-level reporting, with reporting quality falling short of comparable sustainability standards both within each conglomerate and between them. The study concluded that selective and unbalanced reporting along with symbolic management undermines the legitimacy of sustainability efforts by both organizations. Neither LVMH nor Kering are fringe players. Together they control dozens of the most recognizable luxury brands in the world and set the standard for how sustainability is communicated at the top of the market.

LVMH’s LIFE programme, which stands for Luxury and Innovative Fashion for the Environment, has been running since 2012 with nine stated strategic environmental challenges and a series of long-term targets. It’s the kind of initiative that gets cited in press coverage as evidence that LVMH takes sustainability seriously. In 2023, LVMH’s own environmental deputy director acknowledged that “we have a gap in every maison” when discussing the company’s supply chain traceability compliance. Over a decade of the LIFE programme, and there’s a gap in every single brand. That’s not a technical problem in need of more time. It’s a structural choice about what gets resourced and what doesn’t.

The Higg Index: An Industry Tool That Served the Industry

The Sustainable Apparel Coalition was founded in 2009 by Walmart and Patagonia and developed the Higg Index as the fashion industry’s standardized sustainability measurement tool. The premise was reasonable: if the industry could agree on a common methodology for measuring environmental impact, brands could make credible, comparable claims about their products. What follows is a case study in what happens when an industry is allowed to design its own accountability system.

The SAC’s research funding came in part from the synthetic fibre industry, creating a structural incentive to produce methodology that favored synthetic materials over natural ones. This matters because synthetic fibres, primarily polyester derived from fossil fuels, are the dominant material in fast fashion and a significant source of microplastic pollution. A measurement tool that systematically underweights those impacts is not a neutral instrument.

H&M used Higg Index data to display sustainability scorecards on over 600 garments on its website. A Quartz investigation found errors in more than half of those scorecards, with H&M having hard-coded terms like “less” and “reduction” into its platform so the profiles only ever showed a positive environmental picture regardless of what the underlying data actually said. One scorecard claimed a dress was made with 20% less water than average when it was actually made with 20% more.

Norway’s Consumer Authority ruled the Higg data was “oversimplified, inaccurate and imprecise” and sent formal warning letters to both H&M and the SAC. The SAC suspended the transparency program in 2022 following the ruling. In early 2024, it rebranded entirely as Cascale, a new name, a new logo, and the same membership base of over 300 brands, retailers, and manufacturers who had been using the discredited tool.

The rebranding is worth noting plainly. The organization at the center of fashion’s most significant greenwashing scandal didn’t dissolve, didn’t overhaul its methodology under independent oversight, and didn’t face regulatory consequences. It got a new name and continued operating.

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H&M’s Conscious Collection: A Case Study in Legal Architecture

H&M’s Conscious Collection became the most documented greenwashing case in fashion retail, and the legal outcome tells you more about the system than the facts of the case do.

A 2022 class action filed in a New York federal court alleged H&M had falsified sustainability profiles, hard-coding positive language into its systems so that even products made with more water than conventional alternatives were displayed as using less. Consumers who purchased items from the Conscious Collection paid a premium specifically because they believed the sustainability claims attached to those products. The lawsuit argued those claims were not just misleading but structurally engineered to mislead.

H&M’s legal defense was precise: the company argued in federal court that saying products contain “more sustainable materials” is not the same as calling them “sustainable” or “environmentally friendly,” and therefore no reasonable consumer was misled. The court agreed and dismissed the case in May 2023, finding that H&M’s language choices did not constitute misrepresentation because the company had technically never used the word “sustainable” as an absolute claim.

This is the legal architecture that large fashion companies have built over years of careful communications strategy: language calibrated not to communicate honestly with consumers, but to stay just inside the legal definition of non-deception. The precision is deliberate. The vagueness is deliberate. The gap between what consumers understand and what the company has technically committed to is not an oversight. It’s the product.

Dutch authorities subsequently required H&M and Decathlon to dial back their sustainability claims and donate to environmental initiatives to avoid sanctions, a consequence that illustrates how differently the same conduct is treated depending on which jurisdiction a consumer happens to be in. The US federal court dismissed the case. Dutch regulators found a breach. Same company, same practices, very different outcomes.

The Lobbying Operation

While publishing sustainability reports and launching conscious collections, major fashion industry bodies have been simultaneously lobbying to weaken the regulations that would require those claims to be independently verified.

The European Fashion Alliance, a coalition that includes France’s Fédération de la Haute Couture et de la Mode, Italy’s Camera Nazionale Della Moda Italiana, and the UK’s British Fashion Council, published a position paper warning that proposed EU eco-design and disclosure requirements could “dent the industry’s competitiveness and stifle creativity”. The organizations signing that paper represent the same conglomerates whose sustainability reports are being described in this piece.

The EU Green Claims Directive, originally proposed in March 2023, would have required companies to have their green claims independently verified before communicating them to consumers. It was the most substantive proposed regulatory intervention in fashion sustainability in the EU’s history. As of June 2025, the European Commission announced its intention to withdraw the proposal following political pressure. The Commission’s formal justification cited concerns about administrative burden on small businesses, though it’s large conglomerates with expansive sustainability communications operations, not small businesses, that have the most to lose from mandatory independent verification.

The SAC is itself registered as a lobbying entity with the EU Commission, with documented participation in meetings related to the Product Environmental Footprint methodology, the EU Textiles Strategy, and the Circular Economy package. These are precisely the regulatory frameworks that its member brands were simultaneously lobbying to shape in their favor. The same organization that produced the discredited Higg Index was in the room when regulators were designing the rules that would govern how sustainability claims get made and verified.

The full pattern is worth stating clearly: publish voluntary commitments, fund the measurement tool, participate in shaping the regulatory framework, lobby against the regulations that would impose independent verification, then cite the voluntary commitments as evidence of progress. It’s a closed loop, and it’s been running for over a decade.

The Regulatory Patchwork and Who Benefits From It

The US has no federal law setting standards for environmental claims on consumer products. The FTC’s Green Guides, the primary guidance document for environmental marketing claims, haven’t been updated since 2012. FTC enforcement actions related to green claims were zero in both 2023 and 2024. The SEC disbanded its Climate and ESG Task Force in September 2024, removing one of the few institutional mechanisms for holding public companies accountable for sustainability misrepresentation in their investor-facing communications.

In Europe, enforcement exists but is fragmented across jurisdictions. The UK, France, Italy, the Netherlands, and Norway have all taken action against fashion brands for misleading green claims in recent years, but the remedies vary significantly and rarely result in consequences proportionate to the commercial benefit the brands derived from the misleading claims. A company that spent years selling products at a premium on the basis of sustainability credentials it couldn’t substantiate, and then settles by donating a fraction of that revenue to environmental causes, has still run a profitable operation.

What a genuinely regulated environment would require is straightforward: independent verification before any environmental claim is made, mandatory brand-level rather than group-level reporting, and penalties calibrated to the revenue generated by the misleading claim, not just the fine structure of whichever jurisdiction happened to enforce first. None of those requirements are technically difficult to design. They're politically difficult to pass, because the industry has spent considerable resources ensuring they remain so.

The Culture That Made This Possible

It’s worth being honest about the demand side of this equation, because the industry didn’t build this system in isolation. Fashion’s sustainability problem exists inside a broader cultural condition: the expectation that consumption can be frictionless, cheap, fast, and virtuous simultaneously. The Conscious Collection worked as a marketing strategy not because consumers are uniquely gullible, but because the desire to shop more and feel worse about it less is genuinely widespread, and the industry understood that desire better than most.

We’ve built a culture that moves faster than it can think. A trend cycles through TikTok in two weeks. A collection drops, sells out, and gets replaced before most people have worn what they bought. The premium placed on newness, on volume, on the next thing, is structurally incompatible with the kind of patience that genuine sustainability requires, because real sustainability is slow. Sourcing ethical materials takes time. Building transparent supply chains takes time. Paying people fairly across a complex global production network takes time and costs more money.

The brands covered in this piece understood that gap and filled it with language. They gave consumers a way to feel like they were making a better choice without actually changing what they were purchasing or how often. That’s what a conscious collection is, in practice: a permission structure for continued consumption, dressed in green hangtags.

What’s actually needed, from consumers and from the regulatory bodies that are supposed to represent them, is something considerably less comfortable than a new collection: patience, the willingness to pay prices that reflect what ethical production actually costs, and the acceptance that buying less is not a sacrifice of personal expression but a precondition for an industry that functions at a human scale. The brands that are doing that work exist. They’re smaller, less visible, and less algorithmically favored than the conglomerates whose sustainability reports have been discussed here. That’s not a coincidence either.

For years, the mainstream conversation around women’s bodies seemed to be moving toward acceptance and body neutrality. But the culture we subscribe to is cyclical and rarely abandons its old obsessions. It simply waits until it can reintroduce them in a more socially acceptable form, and one persistent fixation for decades has been thinness. This time, it has returned from heroin chic with better branding…arriving through the language of medicine.

What makes this moment unsettling is that the new thinness did not emerge from fashion alone. It emerged from the convergence of pharmaceutical innovation, venture capital, telehealth platforms, celebrity culture, and an economy that has always found ways to profit from women disappearing.

GLP-1s are legitimate medical innovations.

Any serious critique of the GLP-1 era has to begin with the distinction that these drugs are not fake medicine. For many people with diabetes, obesity, cardiovascular risk, or other metabolic conditions, GLP-1 medications are actual solutions to target these medical problems.

Ozempic, a semaglutide injection, was approved by the FDA in December 2017 as an adjunct to diet and exercise to improve glycemic control in adults with type 2 diabetes. Wegovy, a higher-dose semaglutide injection, was approved in 2021 for chronic weight management in adults with obesity or overweight with at least one weight-related condition (the FDA described it as the first drug approved for chronic weight management in adults with general obesity or overweight since 2014).

Then came the next wave. Mounjaro, Eli Lilly’s tirzepatide, was approved in 2022 for type 2 diabetes. In 2023, the FDA approved Zepbound, also tirzepatide, for chronic weight management in adults with obesity or overweight with at least one weight-related condition.

Obesity is a complex chronic condition and the “just eat less and workout more” framework has been both clinically insufficient and socially cruel. The problem is not that better treatment exists. The problem begins when treatment becomes aesthetic aspiration. A drug can be scientifically valid and culturally destabilizing at the same time.

A treatment became a growth category.

The GLP-1 boom did not happen overnight. The FDA approvals created medical legitimacy, then the clinical results created demand, the platforms created access, and the algorithm turned medical prescriptions into a public fad.

Wall Street noticed this quickly. Goldman Sachs Research projected in 2023 that the global market for anti-obesity medications could reach $100 billion by 2030, growing more than sixteenfold from an annualized market of about $6 billion earlier that year. The bank also identified Novo Nordisk and Eli Lilly as likely dominant players in the category. This forecast changed the perception around GLP-1 medications, indicating that the science has become investable. Once a treatment category is understood as a massive market, every surrounding industry begins to reorganize itself around capture: patient acquisition, advertising, subscriptions, insurance navigation, coaching, data, recurring revenue.

This is where venture capital enters the story.

In 2021, Calibrate, a telehealth startup focused on metabolic health and weight loss, raised a $100 million Series B co-led by Tiger Global and Founders Fund. The company described a model that combined remote medical care, coaching, and access to FDA-approved medication, including Wegovy. That same year, Found, another weight-care platform, raised $100 million in Series B funding led by WestCap, with participation from firms including IVP, The Chernin Group, G9 Ventures, Able Partners, GV, Define Ventures, and Atomic.

Big Pharma did the research, ran the trials, secured the approvals, and venture-backed healthcare companies helped build the consumer-facing layer that made these drugs feel less like specialist medical interventions and more like a new category of lifestyle infrastructure. The cultural meaning of a drug changes when access is packaged like e-commerce.

The consumer funnel was programmed before the culture was prepared for it.

By 2023, GLP-1 access was no longer confined to endocrinologists or traditional doctor-patient pathways. It had entered the world of direct-to-consumer healthcare.

Ro launched its Body Program in January 2023, describing it as a comprehensive weight-loss program providing access to GLP-1 medications, diagnostic testing with at-home sample collection, provider care, and coaching. Two months later, WeightWatchers announced it would acquire Sequence, a subscription telehealth platform offering access to clinicians specializing in chronic weight management. The company framed the acquisition as a way to pair WeightWatchers’ behavioral program with clinical medication management. The old diet industry understood the ground had moved, the future of weight loss would be medicalized, digitized, and recurring.

Many people cannot easily find doctors who understand obesity medicine, so a platform that helps patients navigate treatment can be genuinely useful and intriguing for many. A treatment category with enormous demand, recurring use, visible results, and deep emotional vulnerability is almost perfectly suited to the logic of consumer growth. It offers the promise of transformation and the revenue profile of a subscription.

Then the prescription became content.

The cultural acceleration happened online, where medical nuance goes to die and visual transformation travels fastest.

A 2023 study analyzing the first 100 TikTok videos under the hashtag #Ozempic found that the videos were primarily uploaded by consumers and had been viewed about 70 million times. More than one-third of the sample encouraged or enticed others to try Ozempic and very few videos mentioned off-label use or medication shortages.

The early celebrity phase did not require formal coordination. In fact, the absence of clarity made it more potent. Every sudden transformation could be explained, denied, or speculated upon. Were celebrities paid to endorse GLP-1s? Some were, eventually, in formal campaigns. Novo Nordisk’s 2025 “My Ozempic Era” campaign disclosed paid spokespeople, including musician Michael Trotter Jr., chef Franklin Becker, and others, in a campaign focused on type 2 diabetes. In 2026, Novo introduced an Ozempic campaign featuring Justin Long and John Hodgman, also identified as paid spokespeople.

But the more important cultural point is subtler. The early Ozempic frenzy did not need paid celebrity endorsement to spread. It ran on suspicion, where the public did the marketing labor itself. By the time official campaigns arrived, the word “Ozempic” had become shorthand for an entire visual phenomenon.

Scarcity made the drug more desirable.

The shortage phase gave the craze another kind of ammunition. Wegovy was first added to the FDA’s drug shortage list in March 2022, and Ozempic followed in August 2022. The FDA later determined in 2025 that the semaglutide injection product shortage had been resolved.

Scarcity makes a medical product feel exclusive even when the underlying condition it treats is widespread.

It also opened the door to a sprawling compounded market. The FDA warned in 2024 that it had received reports of adverse events, including some requiring hospitalization, associated with dosing errors involving compounded semaglutide injectable products. Some patients reportedly administered five to twenty times more than the intended dose, showing what happens when demand outruns supply, regulation, and comprehension. People are not merely seeking treatment. They are dangerously trying to participate in a cultural shift while it is still happening.

Fashion knows what to do with a shrinking body.

Fashion did not create the GLP-1 boom. But fashion has always been skilled at translating social anxiety into silhouette.

Once the visible signs of GLP-1-era weight loss became culturally legible, the aesthetic apparatus around them began to adjust. This is not exactly the return of heroin chic, because the 1990s version was more tied to nihilism. It had a visual tied to smudged makeup, undone hair, cigarettes, nightclubs, and vacant glamour. Its danger was nothing short of obvious.

The current version is more disciplined. That is why it is harder to challenge. A culture can reject visible self-destruction while embracing depletion when it is presented as optimization (venture capital’s favorite word).

Many of the women and influencers who shape this aesthetic have access to the best food, trainers, healthcare, rest, and lifestyle infrastructure available. They could make nourishment aspirational. They could make strength beautiful. Instead, the culture is again gravitating toward a body that looks underfed.

The danger is not the medication.

The backlash to GLP-1 culture often fails because it collapses too many things into one argument. It shames people who use the drugs and ignores the reality that many patients have suffered for years inside a healthcare system that moralized their bodies instead of treating them.

The danger is not that GLP-1 medications exist. The danger is that a legitimate medical intervention is being absorbed into a culture already fluent in disordered body ideals.

The National Eating Disorders Association has warned that GLP-1 medications are of particular concern for people with active eating disorders, histories of eating disorders, or high susceptibility to developing one. NEDA also notes that significant and sometimes rapid weight loss occurs in many users, and lists concerns including the potential worsening of body-image preoccupation, weight obsession, drive for thinness, skipped meals, over-exercise, and intensified thin idealization.

This medication did not enter a neutral society. It entered a culture already obsessed with thinness. It tells women that hunger is a problem to solve.

This is where the GLP-1 era becomes culturally dangerous. Not because every user is misusing medication. But because the visual results of some users are being generalized into a new standard for everyone else. A treatment becomes coercive when the people who do not medically need it begin to feel they are falling behind.

Did we forget the body is meant to function?

The body has become so visualized that it is easy to forget its function. A body is supposed to have muscle, bone density, hormones, digestion, immune response, cardiovascular capacity, blood sugar regulation, mental clarity, and the ability to move through the world without collapse.

Rapid weight loss can be destabilizing when pursued for aesthetic reasons. The FDA’s warning about compounded semaglutide dosing errors is a reminder that the consumerized version of medicine can blur the seriousness of what is being administered. The current aesthetic conversation often skips this. It sees the smaller body and assumes success. It does not ask what was lost with the weight. It does not ask about muscle, energy, menstruation, or bone health.

Fashion is especially guilty of this, turning the body into an image. But a body cannot survive indefinitely as an aesthetic project.

That is the sentence I keep returning to. A body must be fed and strengthened. Any culture that treats appetite as vulgar and fragility as refinement is not actually promoting health.

Who profits when women disappear?

No single actor needed to orchestrate the craze. Pharmaceutical companies had powerful drugs and a vast potential market. Telehealth startups had a consumer access problem to solve and investors to satisfy. Social platforms had visual transformation content that could travel. Fashion had a silhouette ready to revive. Consumers had decades of body anxiety and a new tool that seemed to bypass the humiliations of dieting. This is how cultural trends are manufactured now. It is capitalism doing what capitalism does: finding demand, amplifying insecurity, smoothing the path to purchase, and aestheticizing the result.

The female body has always been one of its most reliable markets.

The disturbing thing is how quickly the culture adapted. In only a few years, GLP-1s moved from clinical treatment to aesthetic pressure. The same drug can be liberating in a medical context and coercive in an aesthetic one. We should be able to hold both truths. What we should not do is pretend the current body ideal appeared naturally. It did not. It was shaped by pharmaceutical innovation and venture-backed distribution.

And once again, women are being asked to call disappearance aspirational.

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OPEN SOURCE by SSQRD

The utility of virtual try-on platforms is great: try on a lipstick shade without leaving your couch, see how a jacket drapes on your body before clicking buy, find your foundation match without a sales associate. Virtual try-on technology entered the mainstream as a convenience play, and by most commercial measures it has worked. The virtual fitting room market was valued at $6.86 billion in 2025 and is projected to reach $30.41 billion by 2034. Major players including Snap, Google, Zara, H&M, and ASOS have all integrated some version of it, and the technology now covers clothing, makeup, skincare, eyewear, and accessories. The question the industry would prefer you not ask is a simple one: once you hand over a scan of your face or body, where does it go?

More Than a Mirror: What the Technology Is Actually Capturing

There’s a meaningful distinction between a photo filter and a body measurement tool that most users don’t think about when they tap “try on.” A filter captures appearance, but a virtual try-on tool captures biometric data. This includes facial geometry, skin tone analysis, and body dimensions. But the data collection frequently extends beyond the obvious. These tools also gather location data, device information, behavioral and interaction data, and what privacy researchers call “inferred data”: AI-generated insights about a particular individual derived from the session, covering things like skin tone category, body size, and product fit suitability. Photographic and video data captured during a session can inadvertently pick up sensitive information as well, including religious attire, disability markers, or background details that reveal health or political context.

Most companies classify all of this under “usage data” in their privacy policies rather than biometric data, a distinction that carries significant legal weight and is, in most US states, entirely self-determined.

The legal precedent that most directly exposes this gap is the 2024 Charlotte Tilbury settlement. According to the class action lawsuit filed in Cook County, Illinois, Charlotte Tilbury had been collecting facial geometry scans from website visitors through its virtual try-on tools without obtaining consent or providing the disclosures required under Illinois law. The tools in question included not just the virtual try-on feature but also the Foundation Shade Finder, Pro Skin Analysis, Blush Finder, and Skin Reader. The company settled for $2.925 million without admitting wrongdoing, and as part of the agreement committed to publishing a biometric privacy notice, establishing a data retention policy, and implementing a written consent mechanism going forward. The settlement received final approval in early 2025. It established a clear legal precedent: virtual try-on tools constitute biometric data collection under BIPA. The industry has largely continued operating as before.

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The Company Behind the Company Behind the Try-On Tool

Most fashion and beauty brands aren’t building this technology themselves. They’re licensing it from a small group of B2B startups: Snap’s AR try-on platform, Bodify, Fit:Match, and most significantly, Zeekit, which was acquired by Walmart in 2021 for an estimated $200 million. When you try on a garment on a retailer’s app, you’re frequently interacting with a third party’s infrastructure. That third party has its own privacy policy, its own data retention practices, and in some cases its own monetization strategy. The data doesn’t stay with the brand you were shopping.

The Zeekit story is worth examining in detail, and not only because of Walmart’s scale. Zeekit was founded by Yael Vizel, a former Israeli Air Force commander, and Nir Appleboim, who had previously worked together at Elbit Systems, one of Israel’s largest defense electronics companies, where they developed computerized vision systems for fighter planes and helicopters. The core technology that powers Walmart’s virtual try-on for over 270,000 items, and that previously powered try-on features for ASOS, Adidas, Amazon, Macy’s, and Tommy Hilfiger, was directly adapted from military topographical mapping technology. Vizel has said this explicitly in interviews: the company extracted topographical structure from radar images and overlaid it on three-dimensional surfaces for military intelligence purposes, then applied the same methodology to the human body. The angle here isn’t that any fashion retailer knowingly partnered with a defense operation. It’s that the body mapping infrastructure most consumers interact with daily was built on military imaging technology, by founders who came directly out of Israel’s defense industry, and fashion coverage has never connected those dots.

The L’Oréal and ModiFace situation presents a different but equally underexamined set of questions. L’Oréal acquired ModiFace in 2018, its first-ever technology acquisition. Before the deal, ModiFace had powered AR try-on tools for a wide range of brands including MAC, Bobbi Brown, Cover Girl, and Sephora, many of which are direct L’Oréal competitors. When the acquisition was announced, analysts flagged the obvious concern immediately: “Why would I, as a brand competitor, want L’Oréal to get my data on my users?” The question was never fully answered. ModiFace’s AI was trained on a dataset that included scans of 1.6 million photos across 364,012 users, collected before many of those users had any interaction with a L’Oréal product. L’Oréal now controls that dataset, and ModiFace now powers virtual try-on at scale across Amazon, WeChat, and dozens of retail partners worldwide.

How the Industry Is Designed to Stay Just Outside the Law

Only three US states, Illinois, Texas, and Washington, have passed specific biometric privacy legislation. Federal law is completely silent on the matter. This means the protections available to a user in Chicago are not available to the same user in Miami or Phoenix, and companies operating nationally are only legally obligated to meet the highest standard in the states where those laws exist, if they choose to comply at all.

The core legal question is whether a virtual try-on tool is “collecting” biometric data or simply “processing” a photo in real time without storing it. Many companies argue the latter, designing their tools to process images on-device or within a session without retaining them, which places them outside BIPA’s legal definition of “collection.” The problem is that this distinction is entirely self-reported. There’s no independent verification mechanism, and the line between processing and collecting becomes considerably less meaningful when session data feeds into AI model training pipelines, which it frequently does.

Estée Lauder was sued by an Illinois woman after she uploaded a photo to their virtual makeup tool, and the court ruled that BIPA applied even though Estée Lauder had no offices or employees in Illinois. The jurisdictional reach of BIPA has therefore been established: if a user in Illinois accesses a try-on tool, the company is subject to the law regardless of where it operates. Christian Dior, facing a similar BIPA claim over its virtual sunglass try-on, won dismissal by arguing the feature qualified as a “health care setting” under FDA device classification rules. That argument succeeded in court, it also illustrates how much legal creativity is being applied to staying outside the boundaries of what limited consumer protection exists.

In Europe, the GDPR requires explicit, granular consent for biometric processing. Bundled or implied consent, the kind typically embedded in a terms of service agreement, doesn’t meet the standard. A user in France or Germany interacting with the same try-on tool as a user in Texas has meaningfully different legal protections. The US has no federal equivalent to the GDPR, and given the pace of federal privacy legislation, there’s no indication one is coming soon.

The Market for Your Body

Body composition and physical profile data has established commercial value well beyond fashion retail. The health and fitness industry has a documented interest in body dimension data, and insurance and pharmaceutical companies have historically paid for population-level physical profiling. A body scan combined with a detailed shopping history creates a targeting asset that goes significantly beyond what standard behavioral advertising data can offer. It connects physical characteristics to purchasing behavior, brand affinity, and lifestyle signals.

AI training is perhaps the most immediate and least discussed downstream use. Body scan data is actively used to train the next generation of sizing, fit, and avatar models. ModiFace’s own website describes this process directly: experts label thousands of images, the AI learns from them to identify characteristics including skin concerns and face shape, and validation studies are conducted on thousands of individuals globally. The users whose faces trained those models didn’t interact with a training dataset, they used a try-on tool.

This pattern is consistent with what Open Source documented in its first piece. Phia, a fashion shopping app, was found to have been quietly logging the complete HTML of every page its users visited, including Gmail inboxes and bank statements, through its Chrome extension. It removed the feature without notifying users. The virtual try-on industry is operating with the same basic logic: collect more than the user understands, classify it in ways that minimize legal exposure, and treat disclosure as a last resort rather than a default.

The Case for Regulation and What You Can Do Until Then

When reviewing a privacy policy for body data disclosures specifically, look for explicit language around biometric data rather than the broader “usage data” category. Look for a published data retention policy that specifies how long body or facial scan data is stored and when it’s destroyed. Look for an opt-out mechanism that applies specifically to biometric collection rather than general marketing preferences. Most tools currently don’t offer any of the above outside of states where BIPA mandates them.

What meaningful protection would actually require at a federal level is the BIPA standard applied nationally: written informed consent before any biometric data is collected, a publicly accessible retention policy, and a prohibition on selling or profiting from that data. As the Charlotte Tilbury settlement demonstrates, the legal framework to enforce these standards exists and works when it’s applied. The problem is that it currently applies to roughly 8% of the US population.

The virtual fitting room is becoming a standard feature of online retail. The infrastructure running underneath it, who built it, where the data goes, and who profits from it, is almost entirely invisible to the people using it.

OPEN SOURCE by SSQRD

There was a time when fashion trends moved through a predictable chain: runway, editorial, celebrity, retail, mass market. That cycle took seasons. A look debuted at Paris Fashion Week in February and arrived at your local mall by October, if it arrived at all. The gatekeepers were editors, buyers, and stylists, people who made deliberate decisions about what would be amplified and what wouldn’t. That system had its own inequities, but it was at least legible. You could trace a trend back to its origin.

TikTok collapsed that timeline into weeks, and in doing so changed not just how fast trends move but who controls them and who profits from them. The platform replaced the editor-in-chief with a recommendation algorithm, and that substitution has consequences that fashion coverage has been largely unwilling to examine. The clean girl aesthetic and quiet luxury aren’t just two trends that happened to go viral. They’re case studies in how algorithmic platforms manufacture cultural desire at scale, who benefits from that process, and who gets credited versus who gets erased.

How the Algorithm Manufactures a Trend

TikTok’s recommendation algorithm can personalize a user’s feed in as little as 40 minutes, creating feedback loops that push certain aesthetics to critical mass faster than any editor or brand ever could. Here’s how the mechanism works: content that generates engagement gets shown to more people, which generates more engagement, which triggers broader distribution. What looks like organic cultural emergence is frequently a product of that amplification cycle running at scale.

The algorithm doesn’t surface trends neutrally, it surfaces content that generates engagement, and engagement on TikTok has a well-documented racial and class bias toward content that reflects Eurocentric and affluent aesthetics. This isn’t a peripheral observation, it often shapes which creators build audiences, which aesthetics get named and codified, and ultimately which communities get to profit from cultural moments they didn’t originate.

The commercial stakes are significant; a striking 55% of impulse purchases in 2022 were influenced by TikTok content, which means the platform isn’t just reflecting consumer desire, it’s generating it. The trend cycle on TikTok now follows five compressed stages: onset, rise, peak, decline, and obsolescence, each playing out in weeks rather than seasons, with brands racing to produce inventory before the peak passes and the algorithm moves on.

Clean Girl: The Aesthetic That Already Existed, Just Not on White Women

The clean girl aesthetic emerged on TikTok in late 2021 and dominated feeds through 2022 and 2023. It was defined by slicked back hair, gold hoops, dewy skin, minimal makeup, and neutral clothing, marketed as effortless, natural, and aspirationally low-maintenance. The hashtag generated over 750 million views on TikTok, and the aesthetic quickly expanded from a beauty trend into a full lifestyle category covering food, exercise, home organization, and daily routine.

The foundational problem is one the trend cycle moved past without addressing. Slicked back buns, gold hoops, glazed skin, and the cultural emphasis on gel, hair oil, cocoa butter, and dewy complexion were not new. They were Black, South Asian, and Latina cultural practices that had existed for decades. South Asian women who practiced hair oiling were frequently mocked for it. The same slicked back bun that got coded as unhygienic or unprofessional on a Black or Latina woman in a professional setting became a signifier of effortless cool when it arrived on white influencers’ TikTok feeds with a trending sound underneath it.

Creator Via (@fabulousvia) put it directly: “Brown and Black women are notorious for rocking hoops, gelled back buns, no makeup. Now white women are celebrated for the aesthetic. It’s disappointing.” i-D Magazine noted at the time, “a heritage of slicked-back buns, gold hoops, and buttery skin have now been co-opted and reduced to a mere trend, now represented by white women.”

The algorithm’s role in this dynamic wasn’t incidental. The same styles, on different bodies, received different distribution. The aesthetic didn’t change, what changed was which version of it the platform decided was worth amplifying, and to whom it chose to attribute the moment.

Who Profited from the “Clean Girl” Aesthetic

Hailey Bieber launched Rhode on June 15, 2022, at the peak of the clean girl moment. The brand opened with three products priced under $30, built entirely around the “glazed donut skin” aesthetic she had been seeding on her social media accounts for months before launch. This wasn’t coincidental timing, it was a deliberate pre-launch content strategy that used the clean girl aesthetic as the product context before there was a product to sell.

Rhode hit $10 million in sales in its first 11 days. By 2024 it ranked number one globally in Earned Media Value with 367% year over year growth. In May 2025, e.l.f. Beauty acquired Rhode for $1 billion, making it one of the fastest beauty brand exits in history. Bieber generated $400 million in earned media value in 2024 alone, a figure that reflects how effectively she had built the aesthetic into a persistent cultural reference point rather than a trend with an expiry date.

The analysis is this: Bieber didn’t invent the look, she codified it, branded it, and sold it back to the audience the algorithm had already primed to want it. The clean girl aesthetic was the product, Rhode was simply the monetization vehicle. Cosmetics chemistry researchers noted that what made Rhode so commercially effective was precisely the clean girl positioning, described as “unique to celebrity-backed lines” for its emphasis on skin over glam. The brand succeeded because the cultural context for it had been built, distributed, and absorbed before a single unit was sold.

The communities whose practices seeded that context received no credit, no attribution, and no share of the $1 billion exit.

Quiet Luxury: The Algorithm Discovers Old Money

The quiet luxury aesthetic gained mainstream traction through HBO’s Succession, where costume designer Michelle Matland dressed the Roy family exclusively in Loro Piana, Brunello Cucinelli, and The Row. The TikTok hashtag #oldmoney has since accumulated 4.7 billion views. The aesthetic is defined by logo-free, high quality, understated pieces in neutral palettes and was widely framed as an antidote to the logo-heavy maximalism of the post-pandemic luxury boom.

North American retailers sold 40% fewer heavily-logoed products in 2023 than the year before, a shift analysts directly attributed to the quiet luxury trend. The aesthetic also arrived at a convenient cultural moment. As a Mytheresa executive told Business of Fashion, “There are times when everything is going great and people want to show off, but right now everyone is a little uncertain.” Quiet luxury offered a way to signal taste without appearing to try, which is itself a very specific kind of status performance.

The critical distinction is one that most coverage glossed over. Quiet luxury wasn’t created by TikTok, and it wasn’t created by Succession either; Old money families have always dressed this way, with quality and discretion passed through generations rather than acquired. What TikTok did was surface it, name it, codify it, and democratize the aspiration around it, turning a deeply class-specific set of consumption habits into a content category that anyone with a smartphone could engage with and most people couldn’t actually afford.

Who Profited from Quiet Luxury

Brunello Cucinelli reported a 31.9% jump in profits in the first half of 2023, and the company’s executive chairman explicitly credited the quiet luxury movement as a key driver during an investor call. Zegna reported 20% organic growth in Q4 2023, beating estimates and pushing full year revenues to €1.9 billion, with the trend named as a direct contributor. Loro Piana, Toteme, The Row, and Max Mara all saw elevated search traffic and sales during the peak of the cycle.

The downstream effect followed a familiar pattern; fast fashion moved immediately to capture the aesthetic. Shein, Zara, and Mango released quiet luxury adjacent collections within months. The aspiration was democratized, however, the actual product was not. A consumer on TikTok absorbing the #oldmoney aesthetic and purchasing a $40 beige blazer from Zara to approximate it was participating in the cultural moment while funding fast fashion, not the heritage brands whose identity had been borrowed to create the trend in the first place.

The structural irony is that an aesthetic defined by its resistance to mass market trends became one of the most efficiently mass marketed trends of the decade. The brands that profited most from that process were the ones who’d spent decades building the real thing. The consumers who engaged with it on TikTok largely bought approximations. And the platform that manufactured the aspiration took a percentage of every transaction through TikTok Shop, which reached $33.2 billion in global GMV in 2024, more than double the prior year.

The Pattern and What It Means

Both aesthetics followed the same arc; a cultural practice or class signifier exists, and the algorithm surfaces and amplifies a specific, often whitened or wealth-adjacent version of it. Content creators build audiences around the aesthetic. Brands identify the cultural moment and build products or campaigns around it. The aspiration gets monetized, leaving the originators to receive no credit or compensation.

The algorithm isn’t neutral; it makes editorial decisions about what gets amplified and what doesn’t, which creators get distribution and which don’t, and by extension which communities get credited and which get erased. Those decisions have commercial consequences. When a billion dollar brand exit is built on an aesthetic that was seeded by Black, South Asian, and Latina communities without attribution, that’s not a cultural oversight, it’s an economic one.

TikTok Shop is no longer just a trend incubator, it’s a sales engine, and the trends it manufactures are inseparable from the commerce they drive. The question worth asking isn’t whether “clean girl” or “quiet luxury” were good or bad trends. It’s who decided they would be trends, who built the infrastructure to profit from that decision, and who was present at the beginning but absent from the credits.

This Is What SSQRD Is Built to Counter

SSQRD was built on a different premise; the platform is specifically designed to surface small, minority-owned, ethical, and sustainable brands, the exact category of business that the algorithm consistently underserves and the trend cycle consistently extracts from without attribution. Where TikTok’s infrastructure rewards scale, speed, and aspiration, SSQRD’s is designed to reward quality, story, and accountability.

On SSQRD you can filter by material, aesthetic, and values, which means shopping quiet luxury without buying a fast fashion approximation of it. It means finding a heritage brand whose cashmere is actually what it says it is, made by people who are paid fairly. SSQRD doesn’t promote fads, it’s built for the kind of wardrobe that doesn’t need a hashtag to justify it, one built on quality, intention, and the actual stories behind what you’re wearing.

The communities whose aesthetics seeded clean girl and quiet luxury deserved to profit from those moments, but most of them didn’t. What SSQRD is trying to build is a platform where that dynamic works differently, where the brands closest to the culture are the ones with the most visibility, not the least.

OPEN SOURCE by SSQRD

There’s a specific kind of content that’s been impossible to avoid for the past two years: a tech founder, usually male, usually wealthy, usually photographed in natural light, explaining his morning routine. The format is consistent across platforms; there’s a cold plunge, a supplement stack, a carefully curated relationship with sunlight, and language about optimization, longevity, and “science-backed protocols.” And underneath all of it, there’s a set of practices that women have been doing, and getting dismissed for, for a very long time.

The global wellness economy was valued at $5.6 trillion in 2022 and is projected to hit $8.5 trillion by 2027. But, the fastest-growing segment isn’t women’s health, it’s men’s longevity. The biohacking market alone was valued at $24.81 billion in 2024 and is projected to reach $69.09 billion by 2030, fueled in large part by Silicon Valley investors and founders who’ve decided that the body is the next frontier to optimize. The practices at the center of this moment; skincare routines, sleep tracking, cold plunges, red light therapy, hormone optimization, journaling, breathwork, sunlight exposure, anti-inflammatory diets, are not new. They have a much longer history that tech bros are not acknowledging.

The Industry That Forgot Women Existed

Before tech bros discovered their skin, Silicon Valley spent roughly two decades building a culture that was structurally hostile to women. Starting around 2010, the dominant aesthetic of the industry was aggressively masculine and deliberately anti-fashion: gray Patagonia vests, Allbirds sneakers, hoodies, a uniform that signaled productivity over appearance and implicitly coded self-care as either a distraction or a feminine concern. The look was a statement; it said that serious people don’t think about how they look, and serious people, in this framing, were men.

The culture that produced that uniform also produced one of the most gender-imbalanced industries in the economy. The tech sector’s treatment of women, from pay gaps to harassment to the systematic exclusion from venture funding, is extensively documented and not particularly contested. Women-led startups receive a fraction of VC funding relative to male-led ones. Women in technical roles report environments that actively discourage their participation. The structural hostility isn’t a bug of the culture. It’s a feature of how the industry was designed and who it was designed for.

The same platforms built during this period extracted enormous commercial value from women’s self-expression, health content, and beauty practices while doing essentially nothing to compensate or credit the communities generating that content. TikTok, Instagram, and YouTube were built on the labor of women creating wellness, beauty, and lifestyle content, content that drove engagement, sold ads, and generated platform revenue. The creators of that content were paid in exposure and brand deals. The platforms were valued in the billions.

It’s worth holding all of that context before examining what happened next, which is that the same demographic discovered wellness and immediately built a $69 billion industry around it.

Bryan Johnson and the Most Expensive Moisturizer in History

Bryan Johnson sold his software company, Braintree, for $800 million and now spends an estimated $2 million annually on Project Blueprint, a protocol designed to reverse the biological age of all 70 of his organs, including his skin. His skincare routine includes face wash, moisturizer, vitamin C, retinol, exfoliation, and sunscreen, supplemented by medical treatments including Sofwave ultrasound therapy, Tixel laser treatments, and collagen injections. He tracks hundreds of biomarkers and he’s made a documentary about it. He has a supplement line, a podcast, and posts his results online with the enthusiasm of someone who’s just discovered something new.

This is, functionally, a skincare routine. Women have had skincare routines for centuries. The difference is that Johnson’s version comes with biomarker tracking, a documentary, a supplement line, a podcast, and the framing of “science-backed longevity research” rather than vanity. His own website describes his skin protocol as a new approach to anti-aging science, as though moisturizing and wearing SPF is a novel intervention requiring a $2 million annual budget to legitimize.

The rebranding is doing considerable work here. A woman spending $200 on a retinol and SPF routine is practicing basic skincare. A tech founder spending $2 million on the same category of intervention is conducting a longevity experiment. The practices are adjacent, but the cultural reception is not. Johnson isn’t being mocked for caring about his skin, instead he’s being profiled in major publications as a visionary.

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Andrew Huberman and the Science of What Women Already Knew

Andrew Huberman built a podcast with millions of listeners around protocols for sleep, sunlight exposure, cold plunges, breathwork, and supplement stacking, all framed as “neuroscience-backed” and “science-based.” He was a Stanford professor. He had the credentials, the audience, and the language of optimization (which is the language Silicon Valley already spoke fluently).

Women’s wellness practices, from cycle syncing to herbal supplementation to intuitive eating to mindfulness, have been dismissed as pseudoscience, woo, or irrationality by the same mainstream culture that now treats a three-hour morning routine as intellectual rigor. The practices themselves are often not substantively different. Cold exposure for nervous system regulation and cortisol management isn’t categorically different from the breathwork and somatic practices women have been doing in wellness communities for years. What’s different is the presenter, the vocabulary, and the reception.

Scientists have documented that Huberman’s content contains significant misinformation, including undermining consensus data on fluoride, misrepresenting immunology, and structuring episodes around paid sponsor products in ways that create undisclosed conflicts of interest. A 2024 New York Magazine investigation documented pathological lying, manipulation, and alleged scientific fraud. The response from a significant portion of his audience was to call it a hit piece from scorned women.

That response is instructive. When immunologist Kristin Lennox raised concerns about Huberman’s scientific accuracy, she too was dismissed as a scorned woman. When male critics raised the same concerns, it became a story about misinformation in the wellness industry. The information was identical, but it was the source that determined how seriously it was taken.

The double standard is structural, not incidental. Women turned to wellness in large part because mainstream medicine consistently failed them. Women wait longer than men to receive pain medication in emergency rooms. They’re diagnosed years later than men for conditions like endometriosis and autoimmune disease. They’re statistically more likely to have physical symptoms attributed to anxiety rather than physiology. Women were excluded from clinical trials as standard practice until the 1990s, meaning decades of medical guidance was based entirely on male biology and applied to women without adjustment or acknowledgment. Women’s pain reports are routinely discredited, and their pain is more frequently attributed to mental health issues even when presenting symptoms identical to male patients.

Women who sought answers outside that system got called credulous. Men who sought answers outside that system got podcasts, book deals, and a market valuation of $69 billion. The difference isn’t that men’s approach to wellness is more rigorous. It’s that when men do something, the infrastructure of credibility follows.

From Sketchers to Loafers: Silicon Valley Discovers Fashion

The Silicon Valley wellness appropriation has a fashion parallel (as we discussed in our last post) that’s also very intriguing. Quiet luxury was adopted by the tech C-suite before it reached mainstream culture, with Loro Piana opening a Palo Alto store specifically for that market. The same demographic that built a culture around Patagonia vests and an explicit rejection of appearance-consciousness has in recent years developed a substantial investment in how they look. The gray hoodie gave way to the $5,000 cashmere blazer. The rebranding, again, is doing the work. It’s not vanity or fashion, it’s considered curation.

The clean girl aesthetic, more on this topic in a later article, was seeded by Black, South Asian, and Latina communities before being algorithmically amplified in a whitened form and commercialized at scale. The male wellness movement follows a similar arc: practices that women developed out of necessity, community knowledge, and centuries of cultural tradition are now being reframed as optimization protocols by men with capital, distribution, and the institutional credibility that comes with both.

Hair oiling, a practice deeply rooted in South Asian culture, was the subject of active mockery directed at South Asian women in Western schools and workplaces for decades. It’s now a TikTok trend, a product category, and a dermatology-adjacent conversation. Breathwork, herbalism, fasting, sleep prioritization, intuitive movement, and anti-inflammatory diets have all followed similar trajectories: dismissed when practiced by women, celebrated when repackaged with male spokespeople and scientific language. The practices didn’t change. The legitimacy assigned to them changed when the people holding them did.

Who Gets to Call It Science

When a tech founder talks about his skincare routine, it generates press coverage, a product line, and investor interest. When a woman talks about her skincare routine, it generates a beauty blog, maybe a brand deal, and a cultural assumption that she’s motivated by insecurity rather than optimization. The asymmetry isn’t subtle and it isn’t new, but it’s worth naming clearly because it’s actively reshaping where capital flows in the wellness industry.

The 2024 Global Wellness Institute trends report specifically flagged “From Manning Up to Opening Up” as a major emerging trend, identifying the surge in wellness programs and retreats designed specifically for men as a key market driver. The framing is revealing: men entering wellness is treated as a market expansion, a new frontier, and a cultural shift. Women having been in that space for decades, building its infrastructure, producing its content, and sustaining its commercial base, is treated as the baseline assumption, not an achievement.

The wellness industrial complex has a new primary customer and it’s reshaping the economics of health content, supplement sales, and longevity research accordingly. The global longevity supplements market reached $10.7 billion in 2024 and is forecast to double by 2033. The investment in longevity biotech, a category that barely existed as a named sector a decade ago, is now attracting Andreessen Horowitz, Flagship Pioneering, and a roster of Silicon Valley names who spent the previous decade building the attention economy. The trend the industry is now monetizing as new has been practiced, documented, and commercially built by women for decades. The market didn’t grow because the practices changed. It grew because the customer changed and, with him, the credibility assigned to the entire category.

The Bottom Line

The practices themselves aren’t the problem. Skincare is good. Sleep is good. Breathwork is good. Men caring about their health and bodies is genuinely fine, and in some ways a welcome shift from a culture that treated stoicism about physical decline as a virtue. The problem is a system that decides the scientific and commercial legitimacy of a practice based on who’s doing it rather than what it is. Women were told their wellness practices were irrational, indulgent, or insufficiently evidence-based. Men were handed a $69 billion market for the same practices with better branding, more funding, and the default assumption that if a man with a Stanford affiliation is doing it, it must be serious.

Once again, men trying to prove that their hobbies are more legitimate than ours. The only thing that got optimized is who gets the credit and who gets the multi-million dollar investment check.

OPEN SOURCE by SSQRD

Tonight is the Met Gala, and for the first time in the event’s history, it’s being headlined not by a fashion house but by a tech billionaire and his wife. Jeff Bezos and Lauren Sánchez Bezos are the 2026 Met Gala’s lead financial sponsors and honorary co-chairs, funding the “Costume Art” exhibition that pairs 200 artworks with 200 garments spanning 5,000 years of fashion history. The guest list reportedly draws from the couple’s Venice wedding attendees, which included Bill Gates, Oprah Winfrey, Leonardo DiCaprio, and Ivanka Trump, so we can expect a very normal, very representative evening.

But this piece isn’t really about the Met. The Met is the most visible symptom of something that’s been building for years: tech money systematically entering fashion, one sponsorship, acquisition, and merch drop at a time. Amazon was one of the first tech companies to sponsor the Met Gala back in 2012, with Bezos as honorary chair then too. Yahoo came in 2016. Apple in 2017. Instagram sponsored the 2021 and 2022 galas. TikTok threw a reported “high seven figures” at the 2024 gala even as the US was actively debating banning it as a national security threat. OpenAI’s technology was integrated into the 2024 exhibition itself. And now Bezos is writing the biggest check in the room. The pattern isn’t coincidental, it’s a strategy. So, let’s examine what fashion really is to these companies, and why they’re so eager to buy into it.

How Tech Learned That Fashion Is Actually a Distribution Problem

For most of its recent history, Silicon Valley operated on a deliberate aesthetic of not caring about aesthetics. The Patagonia vest, the Allbirds, the gray hoodie: a uniform that communicated that serious people don’t think about how they look, and that implicitly coded self-presentation as a feminine concern unworthy of serious people’s attention.That era is over, and the reason it’s over isn’t that tech founders suddenly developed taste. It’s that they identified fashion as solving a specific problem they haven’t been able to crack otherwise: female consumer trust and adoption.

This year’s Met Gala table buyers include OpenAI, Meta, and Snapchat, described by one analysis as “tech companies desperate for fashion-world acceptance” because “all of these businesses need female adoption.” That framing is unusually honest about what the transaction actually is. Fashion is the most efficient existing infrastructure for reaching women as consumers, building aspiration, and generating the kind of cultural credibility that can’t be purchased through traditional advertising. Tech figured that out and is now buying the infrastructure directly, which is a very Silicon Valley solution to a problem that might have been better addressed by simply not spending the last decade building products that actively alienate women.

Fashion's Biggest Night Has a New Owner

The 2026 Met is the clearest example of what tech’s entry into fashion looks like at full scale. According to insiders, Bezos and Sánchez have “quietly seized control” of the Met Gala’s direction, with sources describing their role as extending well beyond financial support into the actual shaping of the event. “They aren’t just donors. Jeff is writing the checks. Lauren is making the calls,” one insider told reporter Rob Shuter, which is a sentence that would read differently if the fashion world had spent more time thinking critically about what it means to accept this particular check.

Sánchez appeared on the digital cover of US Vogue in June 2025 wearing her Dolce & Gabbana wedding gown, a cover that critics noted fit awkwardly with the publication’s established editorial aesthetic, and which arrived at almost exactly the same moment Anna Wintour announced she was stepping back from the editor-in-chief role she’d held for 37 years. The timing raised obvious questions. Rumors have circulated since mid-2025 that Bezos is considering acquiring Condé Nast, Vogue’s parent company, reportedly as a wedding gift for Sánchez, which is either the most romantic thing a billionaire has ever done or the most efficient PR strategy in fashion history, depending on your perspective. Condé Nast has denied any plans to sell, but the speculation has not gone away.

The Washington Post comparison is instructive here because Bezos actually did that one. He bought the Post for $250 million in 2013, and later required its opinion section to focus almost exclusively on individual freedoms and free markets, a shift that caused significant internal backlash and the loss of 250,000 subscribers. The editorial direction of a publication changed when the owner’s interests and the publication’s historical stance diverged. So when the same person is now sponsoring the Met, potentially eyeing Vogue, and has already placed his wife on a Vogue digital cover, it’s reasonable to ask what the editorial direction of fashion media looks like in a few years if this trajectory continues.

The public response to the Bezos Met has been notably uncharitable. Protest group Everyone Hates Elon placed miniature bottles of fake urine outside the Metropolitan Museum of Art referencing Amazon workers’ documented inability to take bathroom breaks during shifts. “Boycott the Bezos Met Gala: Brought to you by worker exploitation” posters appeared across NYC. NYC Mayor Zohran Mamdani announced he would skip the event entirely, citing affordability concerns in the most expensive city in the US. None of this stopped the gala from charging $100,000 per individual ticket and $350,000 per table, which tells you something about whose concerns fashion’s institutional leadership is most responsive to.

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Amazon Already Owns Victoria's Secret's Biggest Night Too

The Met isn’t the only major fashion institution Amazon has quietly moved into, and the Victoria’s Secret situation is in some ways more instructive because it shows what the product-level version of this looks like once the cultural moment has been secured.

The Victoria’s Secret Fashion Show, cancelled in 2019 amid controversy over its handling of diversity and its organizer Edward Razek’s conduct, returned in 2023 as an Amazon Prime Video exclusive. The 2024 show was an Amazon Live and Prime Video exclusive, with a shoppable feature built directly into the stream allowing viewers to purchase looks on Amazon as models walked the runway. The 2025 show continued the same arrangement. Victoria’s Secret’s comeback is, functionally, an Amazon commerce event dressed in wings and Cher performances.

The shoppable runway is worth examining specifically because it’s the most transparent articulation of what tech actually wants from fashion. It’s not just a streaming deal. It’s Amazon integrating fashion’s most aspirational visual format directly into its shopping infrastructure so that the aspiration and the transaction are collapsed into one interface. The viewer watches the show, feels something, clicks the look, and buys it on Amazon. Fashion’s job in this model is to generate the feeling. Amazon’s job is to capture the purchase. The toll booth between aspiration and commerce is now an Amazon checkout page, and Victoria’s Secret’s revival exists, in significant part, to keep traffic moving through it.

TikTok Sponsored the Met While Congress Was Trying to Ban It

While Bezos is the 2026 story, TikTok’s 2024 Met Gala sponsorship deserves its own examination because it illustrates how far fashion institutions are willing to stretch their stated values when a large enough check is on the table. TikTok threw a reported “high seven figures” at the 2024 gala, with CEO Shou Zi Chew serving as honorary co-chair, the first time a social media executive had held that title at the event.

This happened in the same month the US passed legislation giving ByteDance nine months to divest TikTok or face a ban on the grounds that the platform posed a credible national security threat under Chinese ownership. The Met said it was “grateful for TikTok’s support”. Condé Nast deferred to the Met. Fashion’s most prestigious cultural institution took millions from a company the US government was simultaneously trying to shut down, and the fashion press covered it primarily as an aesthetic controversy rather than a conflict of interest worth examining. That’s the dynamic in miniature: fashion needs the money, tech needs the cultural legitimacy, and the transaction moves forward regardless of whether either party’s other activities would suggest it probably shouldn’t.

Palantir Has a Merch Drop and Calls It a Lifestyle Brand

Away from the red carpet, there’s a different and considerably less glamorous version of tech entering fashion that’s been happening in plain sight and receiving almost no coverage in the industry press. Since opening its merch store in 2024, Palantir has released five drops and a core capsule, borrowing the language and limited-release cycle of American streetwear to sell branded apparel to a community of investors and ideological supporters. The store is powered by Shopify. The copy reads like a military gear catalog written by someone who went to business school.

Palantir’s head of strategic engagement Eliano Younes has stated explicitly that he wants Palantir to be a lifestyle brand: “There are people out there wearing Palantir merchandise to signal their alignment with our mission, and that’s exactly what a lifestyle brand is.” That mission, for context, includes providing data infrastructure to ICE and military intelligence operations, and the company’s CEO Alex Karp co-authored a book that advocates for reinstating the draft and criticizes pluralism. One of their shirts read “SOFTWARE THAT DOMINATES,” another featured an image of Karp alongside the word “DOMINATE,” and a chore coat dropped on April 30. The merch is mostly sold out.

Palantir is using fashion’s distribution infrastructure, the drop model, the capsule collection, the lifestyle brand vocabulary, to build community and signal identity around a political and ideological project. This is a fundamentally different use of fashion than anything the industry has accommodated before, and the industry has largely not acknowledged it’s happening, possibly because “surveillance tech company uses streetwear drops to normalize its brand among retail investors and right-wing tech enthusiasts” is the kind of sentence that requires the fashion press to develop an opinion about something more complicated than hemlines.

What Fashion Is Actually Selling When It Sells to Tech

The common thread across all of these examples is that fashion is being purchased not for what it makes but for what it means. Tech companies aren’t entering fashion because they want to design clothes or support cultural institutions out of genuine appreciation. They’re entering fashion because fashion is one of the most powerful existing systems for building aspiration, signaling identity, and generating the kind of cultural trust that tech companies have spent the last decade systematically eroding through data breaches, labor violations, and the general behavior of people who decided that moving fast and breaking things was a mission statement rather than a warning.

But there’s a second transaction happening underneath the cultural one that gets almost no coverage. Every time Amazon powers a shoppable Victoria’s Secret runway, it collects data on what women buy, when they buy it, what they almost bought, how long they hovered over a product, and what they watched before they clicked. Every time a tech company sponsors a fashion event and integrates its infrastructure into the experience, it adds another data layer to a profile it’s been building for years. Fashion’s consumer base is exactly what these companies need: highly engaged, brand-loyal, and willing to share significant amounts of personal and behavioral data in exchange for access to aspiration. The Met Gala isn’t just a cultural moment for Amazon, it’s a targeting event. Victoria’s Secret’s comeback isn’t just a streaming deal. It’s a data acquisition pipeline dressed in wings.

Individual Met Gala tickets cost $100,000 in 2026 and tables run $350,000, which sounds like an enormous sum until you remember that Bezos’s fortune is estimated at around $224 billion, making the cost of sponsoring the entire event roughly equivalent to a median American household spending $2 on a cultural outing. The financial cost is negligible and the cultural return is significant, which is why every major tech company with a female adoption problem is now buying a seat at fashion’s table and calling it philanthropy.

Fashion’s institutional leadership has made a calculation that tech money is necessary to sustain these institutions at the scale they’ve grown to, and that calculation may be correct. The Met Gala raised a record $31 million last year and individual tickets have nearly doubled in price over the past few years. Those numbers don’t happen without corporate sponsors writing very large checks. The question worth asking is what gets negotiated away in the process: editorial independence, the ability to publish criticism of the companies writing the checks, the sense that fashion’s cultural conversation is shaped by people with genuine expertise in fashion rather than by whoever has the largest sponsorship budget and the most pressing need for female consumer trust.

The Labor Nobody Talks About

What doesn’t get discussed in any of these deals is the people at the bottom of the supply chains those tech companies depend on. The Amazon warehouse workers whose bathroom break situation is now the subject of Met Gala protest art. The factory workers producing the garments that Victoria’s Secret streams through an Amazon-shoppable interface. The contractors whose professional expertise is harvested to train the AI that OpenAI is now integrating into fashion exhibitions. Fashion has always had a complicated relationship with labor, and the industry’s critics have pointed that out for decades. What’s new is that tech is making the contradiction more visible by putting its name on the event and asking fashion to validate it in return.

The Met Gala has always been a transaction: cultural credibility in exchange for money, access in exchange for influence. What’s changed is who’s writing the check and how many other things they’re buying alongside the table. When the same person sponsors the gala, places his wife on the magazine cover, owns the newspaper with the shifted editorial direction, and is rumored to be in acquisition conversations for the media company that runs the whole thing, it stops looking like philanthropy and starts looking like infrastructure. Fashion is being acquired the same way everything else gets acquired in the attention economy: one asset at a time, until the ecosystem belongs to someone who never worked in it and has very different reasons for wanting it.

OPEN SOURCE by Nela Taeb

There’s a particular kind of confidence saturating the AI startup space right now. It shows up in pitch decks, in founder profiles that move from dorm room to Forbes cover in under two years, and in press releases that describe template software as “agentic intelligence.” For a while, that confidence read as momentum, but the more you look at what’s actually produced, the harder it is to call it that.

The current funding environment has created conditions where building a compelling story about a product is more strategically urgent than building the product itself. This isn’t unique to any one company or sector. It’s a structural outcome of how capital is currently moving through the tech ecosystem, who it’s rewarding, and what it’s choosing to overlook. The people who absorb the cost of that dynamic are almost never the people who raised the money.

The Machine That Funds the Lie

In Q3 2025 alone, nearly $45 billion in venture capital flowed into AI startups, representing close to half of all global VC investment that quarter. That volume of capital doesn’t move patiently, and it doesn’t tend to reward the slow work of building something that actually functions before announcing it. Investors who lived through the crypto cycle arrived at the AI moment already fluent in the rhythm of hype, and the vocabulary updated accordingly: agentic AI, autonomous workflows, B2B SaaS, vertical intelligence. These terms are legible to a pitch room in a way that a working product isn’t always, and for a certain class of founder, that gap has proven fairly easy to exploit.

Andy Liu, co-founding partner at Unlock Venture Partners, put it plainly: “Capital and valuations are running well ahead of fundamentals, particularly for companies without clear customer pull, durable differentiation, or credible paths to profitability.” Databricks CEO Ali Ghodsi was more direct at a conference late last year: “Companies worth billions of dollars with zero revenue, that’s clearly a bubble, and it’s, like, insane.”

When the fastest path to a term sheet is a captivating deck and a viral moment, founders optimize for the deck and the moment. The product becomes secondary, a proof of concept to be refined after the raise, after the press cycle, and after the cover story. That’s a rational response to a market that has signaled, repeatedly and with large checks, that narrative precedes product. What gets lost in that sequence is accountability to the people the product is supposed to serve. The three companies below are not chosen because they’re uniquely bad but because they document the pattern clearly.

Delve: Compliance as a Service, Fraud as a Feature

In July 2025, Delve, a Y Combinator-backed compliance startup founded by two 21-year-olds, raised $32 million at a $300 million valuation. Insight Partners led the round and Y Combinator had the company in its batch. The pitch was straightforward: agentic AI that could compress months of compliance certification into days.

What the institutional endorsement didn’t surface was whether the founders had any background in the domain their product was supposed to automate. Compliance isn’t an abstraction; HIPAA certifications, GDPR attestations, SOC 2 reports are the legal scaffolding that enterprises and insurers rely on as proof that a vendor’s security posture is real. The Delve founders came from research backgrounds, having virtually no experience with compliance. Signaling a passion gap, which means there was going to be a product gap.

An anonymous whistleblower writing under the name DeepDelver pooled evidence with former clients and found that Delve had been generating auditor conclusions before any independent review occurred, routing clients through what the report described as Indian certification mills, and producing reports so identical that 493 out of 494 shared the same grammatical errors. A subsequent installment alleged that Delve had taken an open source tool built by fellow YC company Sim.ai, stripped the attribution, and sold it to enterprise clients as proprietary software.

Y Combinator has since asked Delve to leave. It’s a meaningful consequence, but it doesn’t undo the damage already done to the hundreds of companies that may now be operating under a false sense of legal security. The more uncomfortable question is how Delve got this far without anyone in a position of institutional power asking harder questions earlier. Insight Partners and Y Combinator are some of the most resourced institutions in the startup ecosystem, and failed to complete their due diligence. Until investors treat domain expertise as a non-negotiable signal rather than a nice-to-have, Delve will not be the last company to build an impressive pitch around a product it was never qualified to build.

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Phia: Where manufactured hype overlooks serious privacy concerns

*A note on positionality: SSQRD and Phia operate in the same fashion-tech space. The analysis below is based solely on documented reporting and independent security research, and reflects no competitive interest.

Phia raised $43 million, landed on TIME’s Best Inventions of 2025, and assembled a celebrity investor list that includes Kris Jenner and Hailey Bieber. The product concept is straightforward: price comparison across 40,000 retail and resale sites, marketed as the “Google Flights of fashion”. A tagline that was coined by SecondSense first, revealing a broader pattern of borrowed positioning dressed up as original vision. Phia also wasn’t the first to build the product itself. Beni launched earlier with a comparable premise and considerably less fanfare, which says something about how much of Phia’s traction has been driven by marketing and investor recognition rather than product differentiation.

The user numbers deserve scrutiny too. Phia has reported 750,000 users, but its Google Play and Chrome extension stores show somewhere between 20,000 and 30,000 downloads, a gap that hasn’t been publicly explained. Its App Store reviews show patterns consistent with artificial inflation. These aren’t minor discrepancies. For a company whose valuation depends heavily on demonstrated consumer adoption, the difference between reported and verifiable numbers is material.

Phia’s actual business model relies on selling user data, and the privacy implications of that are more serious than the company’s public positioning suggests. A source with direct knowledge described being approached at an Andreessen Horowitz event by a third-party contractor Phia uses to sell user data to unauthorized parties, who disclosed, with text message evidence from Phoebe Gates, that Phia was actively selling user data outside of what users had consented to. Phia also has a partnership with Microsoft that grants access to Microsoft’s data for the same purpose. In November 2025, security researcher Maahir Sharma independently confirmed that Phia’s Chrome extension had been quietly logging the complete HTML of every page users visited, including Gmail inboxes, bank statements, and Instagram DMs. Phia removed the feature without notifying users or ever addressing it at all.

The product was marketed specifically to young women as a tool for more intentional, empowered shopping. The founders have last names that tend to lower the threshold for institutional trust and accelerate press coverage, and the scrutiny applied to Phia’s actual product and privacy practices has been considerably thinner than the coverage of their personal brands. That’s worth saying plainly, not to relitigate who they are, but because it illustrates how social capital functions as a substitute for due diligence.

Mercor: Growth That Outran Its Responsibility

Mercor is a harder case because the business model is concrete: connecting AI labs with domain experts for model training, paying out more than $1.5 million per day to contractors, scaling from $1 million to $500 million in annual revenue in 17 months.

The three 22-year-old founders are, by any measure, building something. But at a $10 billion valuation, the cracks are visible. Users widely suspect that the platform’s AI interview process is less about matching talent with work and more about harvesting professional knowledge to train models, with no mechanism for applicants to understand or ask how their data is being used. In early 2026, thousands of contractors were abruptly told their projects were over, then offered lower hourly rates for new roles. A subsequent security breach exposed sensitive contractor and client data, potentially including proprietary research from the AI labs Mercor services.

What’s concerning about Mercor specifically is that trust isn’t incidental to its business model, it’s the entire product. The company sits between AI labs handling sensitive research and contractors providing the professional expertise those labs depend on. A security breach in that context isn’t a growing pain or an operational oversight that can be patched quietly. It’s evidence that as Mercor scaled, the infrastructure required to actually protect the people and institutions it serves didn’t scale with it.

The Market Is Encouraging Bad Behavior

The consistent thread across all three isn’t the fraud itself but rather who is absorbing the cost of it. Startups that relied on Delve for HIPAA and GDPR compliance may now face regulatory exposure they were told they had covered. Phia’s users had their most sensitive browsing activity logged without their knowledge. Mercor’s contractors, the doctors, lawyers, and engineers whose expertise trains the next generation of AI models, are being cut and offered less. In each case, the people closest to the actual harm are the furthest from the decision-making that produced it.

This is unfortunately a feature of how the current funding environment works. When capital is moving at the pace it moved in 2025, the incentive structure doesn’t reward founders who slow down to get it right. It rewards founders who ship fast, generate press, and hit the metrics that trigger the next round. Domain expertise is a secondary consideration and user accountability is a post-series problem. The result is a class of companies that are optimized for investor confidence rather than user trust, and those aren’t the same thing.

The founders who built these products aren’t uniquely reckless people. They’re responding to what the market has consistently signaled it wants. A founder who moves slowly, discloses limitations honestly, and builds infrastructure before scaling doesn’t tend to make the Forbes list. But a founder who raises $300 million at 21 on a product that turns out to be a template does. Until the incentives shift, the behaviors surrounding the pursuit of the incentives won’t.

What makes this structurally difficult to fix is that the people funding it aren’t the ones paying for it either. A founder navigates a failed or fraudulent company and walks out with a network, a narrative, and in many cases, another term sheet. The hospital operating under a fabricated compliance report faces regulatory exposure. The user whose data was quietly uploaded faces a privacy violation most will never fully piece together. The contractor who trained the model gets a lower rate and a form email. The asymmetry isn’t subtle, it’s become the predictable output of a system that has decided speed and story are worth more than accountability, and has structured its returns accordingly.

Why SSQRD Is Not Playing the Same Game

We’re building in the same market as the companies in this piece, but we are not building to win by the same rules. What this ecosystem rewards right now is speed, narrative, and scale. It does not consistently reward accuracy, accountability, or a real understanding of the problems being solved. The companies we’ve discussed are products of it.

We are choosing, very deliberately, not to operate that way. That means we move slower, we don’t treat user trust as something to figure out after growth. It means we don’t abstract away the people most affected by the system we’re participating in. When we say we prioritize independent businesses against big corporations, it’s a decision to focus on the part of the market that is consistently ignored because it’s harder to scale. It comes with tradeoffs, but we are not going to inflate metrics to tell a better story than what actually exists or manufacture traction or fabricate success to meet expectations set by a market that rewards perception over reality.

We’ve seen what happens when companies make the opposite trade, what happens when products are treated as secondary to perception, when accountability is deferred, and when the people closest to the harm have the least power to respond to it. We don’t think that’s a neutral outcome. And we don’t think it’s inevitable.

In this market, it is often possible to fail upward. To walk away from a broken product with a stronger network, a better narrative, and another opportunity. We are building for underdogs, as underdogs, and we are choosing to challenge the norms that have defined the startup and tech ecosystem up until now.

It’s Nabihah from SSQRD. This wasn’t supposed to be our launch week (I’m in Japan for my birthday and writing this at 4 AM), but we decided to open up SSQRD early and give you first access.

What SSQRD is

SSQRD is a platform for fashion discovery, basically if Google and Pinterest had a baby for fashion/beauty. Our goal is to help you find products you love from small and niche brands. No fast fashion, no unethical brands.

What’s in V1

Explore Feed [Explore]
Browse a visual feed of products and heart your favorites. Everything is stored neatly in your account.

Search Engine [Search Bar]
Look up a specific product and we’ll scan the internet for the best versions from good brands only. Search is still early, so expect improvements as we expand coverage.

User Accounts [👤 > Account]
Save products and brands you like and build your own personal edit.

Shop by Aesthetic [Shop]
Browse fashion by category and vibe.

Try SSQRD

Create an account at ssqrd.co. Works on desktop (recommended) or mobile browser. We’re launching on browser first so everyone can try it, not just iPhone users. And the best part: SSQRD will only get better from here.

We want to make shopping more intentional and highlight brands that care about their communities and customers. And you get to say you were here from the beginning.

Let’s change the fashion industry together.

Best,
Nabihah
Founder & CEO, SSQRD

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Outsourcing Accountability: How Brands Circumvent Responsibility for Unethical Worker Conditions

Beneath the corporate marketing of ethical practice, sustainability, and innovation there lies a system designed to extract labor value while obfuscating accountability. From luxury fashion houses in Italy to coding hubs in India, global brands rely heavily on a secret workforce: third-party contractors and manufacturers who keep costs low and operations flexible.

What are Third-Party Contractors?

Third-party contractors are external agencies, suppliers, firms, or workers that a company hires to do specific tasks, such as manufacturing, coding, or customer service, rather than hiring direct employees.

When brands outsource labor to third parties in an effort to cut costs and reduce liability, they effectively remove themselves from any connection to the unethical labor conditions that allow their products to be created. This business model enables these companies to maintain the image of ethicality and sustainability, especially when overcharging for products.

Two sides of the same coin: Luxury fashion and the Tech Industry

In July 2025, The Guardian reported that luxury brand Loro Piana had subcontracted production of their apparel to illegal workshops in Italy and China. Workers in these factories earned as little as 4 pounds an hour for up to 90 hours a week, while the garments they made sold for over 3,000 pounds. Despite the garments being marketed as being “Made in Italy”, many were the product of unregulated labor practices hidden through the several layers of the supply chain.

The tech world boasts a similar problem: Companies based in the US, especially in Silicon Valley, often hire Indian developers through agencies that offer low-cost labor. These developers are expected to produce the same high-quality level of work as their American counterparts for a fraction of the pay. One post published on Reddit went viral for capturing the frustration of a developer who had been expected to deliver “Google-level” work while he earned less than 8,000 dollars annually. Simultaneously, many American tech workers have been laid off while startups and tech giants prioritize contractors over full-time employees for financial and legal flexibility. Some workers have even been laid off just to be requested as contractors for the same company.

In both sectors, business models rely on demanding intense and efficient performance while offering meager wages. And in both sectors, brands face little to no accountability.

Same Plight, Different Sectors

Garment workers and tech contractors operate within similarly exploitative systems. Both are often employed through third parties, whether that is an agency or a subcontracted factory. This intermediary status makes it extremely difficult for workers to receive any sort of legal protections, benefits, job security, or even the right to unionize. These workers are essential to the workings of these companies, but they are invisible in public sustainability reports.

These structural similarities between the sectors is not a coincidence, they are the products of a global economic system that prioritizes scalability and low cost often at the expense of labor rights.

Why Outsource?

Companies frame outsourcing as an economic necessity due to rapidly changing trend cycles and rampant consumerism. Labor in countries such as India, Bangladesh, or Vietnam is significantly cheaper which allows firms to maximize profit margins. Additionally, outsourcing provides strong legal protection due to the separation between the brand and the manufacturers or contractors– brands are able to remove themselves from the conditions under which workers produce their goods and services.

These layers of subcontracting can make it difficult to trace accountability and make it easier for brands to claim ignorance or limited control. Despite the narratives that these brands may be pedaling, research from UCLA and other institutions’ professors emphasizes that brands often dictate pricing, timelines, and production volume. These are all conditions that can immensely affect labor conditions even when passed through a chain.

Furthermore, international labor regulations are weak and, in some cases, non-existent which creates legal gray-zones for companies to operate in. The lack of enforcement mechanisms, especially internationally, puts workers at risk and prevents them from demanding better conditions.

The Garment Industry

Loro Piana is not the only example of this trend. Human Rights Watch has documented how business models in fashion directly encourage wage theft, forced overtime, and hazardous working conditions.

While it may seem like the vast majority of brands have adopted “codes of conduct” pertaining to worker conditions, these guidelines are usually voluntary and very poorly enforced. A 2022 report from Remake found that not a single major fashion brand ensured that their workers were receiving living wages for producing their garments. Instead, many brands were subcontracting through manufacturers working in informal economies where workers have minimal legal protections.

In the United States, factories in Los Angeles were found to be underpaying migrant workers, many of whom are undocumented. These factories pay workers by the piece which allows them to pay wages below the legal minimum while still misleading customers by labelling their clothing as “Made in USA” implying ethical working conditions.

The Tech Industry

In tech, outsourcing manifests in a different but just as exploitative manner. Major US tech firms are increasingly turning to agencies and global capability centers (GCCs) in India to hire developers, engineers, and support staff. These workers are technically not employees of the companies and therefore do not receive any benefits or protections that direct hires do.

Investigative reports from The Guardian and Business Insider reveal how this system leads to widespread exploitation. Some Indian IT workers are bound by restrictive contracts that limit their job mobility and suppress their wages. Others work under immense pressure with little recognition or monetary reward. And as AI continues to grow, it exacerbates the issue as companies use it to push productivity even more.

Many startups have also adopted this model. Platforms like OysterHR allow startups to legally hire international independent contractors without having to classify them as employees of the company. While this provides the company with legal and tax benefits, it leaves these workers without job security or benefits such as healthcare. This creates a system where workers are entirely disposable.

Next Steps

Meaningful change must be demanded of these companies. Transparency about supply chains and employee conditions, whether directly or indirectly hired, must be mandated. Tech firms must report wage data and employment classifications, not just diversity statistics and "sustainability" goals. The law should evolve to reflect modern labor dynamics both here, and abroad. If a brand dictates the terms under which a product is created, regardless of who signs the paycheck, they must be held accountable for labor conditions.

Consumers also play a vital role. Supporting worker-led initiatives, ethical businesses, and transparent brands can create bottom-up pressure. We must redefine what corporate responsibility means in a global economy.

What About SSQRD?

We’re in a unique position where we lie at the intersection of fashion and technology. Our mission is to build an ethical company, from our product to our operations. SSQRD is here to challenge the exploitative norms of both industries and platform brands that align with real sustainability and labor equity. Through transparency and innovation, we want to emphasize that responsibility and profitability don’t have to be mutually exclusive.

Earlier this month, the news broke that Ami Colé, one of the beauty world’s most beloved black-owned beauty brands, would be shutting down. Despite raising over 3 million dollars through Venture Capital, the brand’s founder, N’Diaye-Mbaye, cites an unsustainable market for the closure. Unfortunately, Ami Colé’s story is not a unique one. Whether it’s fashion, food, beauty, or even healthcare, we have all seen beloved brands go out of business and wonder what happened.

Although Ami Colé wasn’t directly owned by private equity, its shutdown raises questions about a deeper systemic issue: how independent brands, especially those owned by women and people of color, are being squeezed out of the market by unsustainable financial models and larger players, including private equity firms. As these big players grow through billions from institutional capital, independent, founder-led brands are being increasingly shut out. In beauty alone, private-equity backed groups like Forma and Waldencast are acquiring smaller brands, scaling them up, and aggressively pushing for returns. Many brands, like The Body Shop, eventually lose their core values or fail entirely, fueling a market that rewards financial engineering over innovation.

What is Private Equity– and Why Should You Care?

At first, “Private Equity” sounds unassuming, but it is one of the most powerful players in the global economy. Private Equity firms specialize in buying companies, often with money that is borrowed, and “improving” them to resell. Theoretically, this may sound productive, but practically, these firms are detrimental to many of these companies.

Companies bought by private equity firms are 10 times more likely to go bankrupt than companies that aren't. The retail sector has removed almost 600,000 jobs in the last decade alone while under private equity ownership. In other sectors, such as healthcare, the toll that Private Equity has taken has been even larger; Private Equity nursing home ownership has been linked to over 20,000 premature deaths over 12 years.

The Method: How Private Equity Drains Companies

The question remains: if the companies that Private Equity firms are buying are failing at such a rapid rate, how are these firms still thriving?

Private Equity firms rarely use their own money to make these purchases and instead use a tactic called a leveraged buyout (LBO). A LBO is when a private equity firm borrows large sums of capital to purchase a company, and then transfers that debt to the company it has just purchased. Once the debt is factored into the company’s balance sheet, the firm begins “restructuring”: cutting jobs and costs, selling valuable assets, and collecting millions in “advisory” fees. Many times the firm is able to execute a practice called “Asset stripping” where they are able to sell the company for parts. This allows the firm to maximize short-term profit and sell the company for a profit before the consequences catch up to them.

Case Studies: J.Crew and The Body Shop

One case of this is J Crew, the classic fashion brand that was once a staple in American preppy fashion. In 2011, J Crew was acquired by private equity firms TPG Capital and Leonard Green & Partner, which combined manage over 330 billion in capital, through a leveraged buyout. Under this new ownership, J Crew experienced increased interest payments, cut costs, and a brand image crisis. In 2020, against the backdrop of the pandemic and, more pressingly, 1.7 billion dollars in debt, J Crew filed for bankruptcy. While individuals lost their jobs and the brand suffered, the private equity firms were basking in the more than 760 million dollars they had received from the company through fees and dividends.

Another recent example is The Body Shop, a skincare brand known for its ethical, cruelty-free image. In 2017, The Body Shop was acquired by Natura & Co from L’Oréal, and in 2023 sold again to German private equity firm Aurelius, causing the brand to rapidly decline. In early 2024, The Body Shop announced a closure of all of its US stores and almost half of its UK stores after it filed for bankruptcy. This decline was caused by the familiar pattern of overexpansion, cost-cutting, and profit pressure all at the expense of the brand’s long-term integrity.

Legal Loopholes

So if private equity firms are causing such destruction why aren't they being held accountable? This is because these firms don't technically “own” the companies that they control. Ownership often passes through shell entities and funds, allowing the firms to claim distance in any legal proceedings.

Take the case of HCR ManorCare, a nursing home chain bought by the Carlyle group in 2007. Carlyle sold most of ManorCare’s real estate and pocketed nearly 80 million in fees. The company quickly deteriorated and experienced lawsuits that eventually led it to bankruptcy. When the family of a woman who died in one of the nursing homes tried to sue Carlyle the firm argued that it wasn't legally responsible because it was only there in an advisory capacity to the investment fund that owned the company.

A Systemic Issue

It’s a dirty game, and one that firms have become very good at not only playing, but controlling as well.

In the 2019-2020 cycle, Private equity spent over 75 million dollars lobbying in the US and has employed former senators, CIA directors, and even foreign prime ministers. These connections have allowed them to protect loopholes and fend off any type of regulation.

What Can be Done?

There are many solutions to mitigate this damage. First, regulators should make it clear that firms must bear the legal responsibility for the companies they control. Tax laws can be rewritten to eliminate the unfair advantages that private equity firms currently enjoy. And we, as consumers, should demand more transparency and fairness. Public Pressure has been successful in the past. Private Equity firms receded in the past when their PR was tarnished by their greedy image. We have the same power to hold these firms accountable by staying educated and demanding action from our lawmakers.

This is the exact reason we built SSQRD: to democratize entrepreneurship and provide a platform for independent brands to thrive in a world suffocated by capital-driven business empires. We’re working to shift attention and consumer spending away from these faceless corporations, and towards businesses that are ethical, community-based, and creative. We may mourn the loss of brands such as Ami Colé, but with that must come a desire to create change.

“Failed” brands are not always the outcome of a bad product, but a broken system.

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