Three distinct approaches are emerging to solve fashion’s $600B return problem. But which path will shoppers actually follow?
The $600 Billion Problem
Online fashion’s return crisis has reached epidemic proportions. With return rates hovering at 30-40% — compared to just 8-10% in physical stores — the industry loses an estimated $600 billion annually to shipping, restocking, and customer dissatisfaction. The root cause? Shoppers can’t truly visualize how clothes will look and fit on their unique body.
This year, three AI-powered startups are attacking this problem with fundamentally different strategies. Each promises to revolutionize how we shop, but their approaches couldn’t be more different.
Cutting-edge ai try-on systems are redefining the online shopping experience.
The Big Tech Context
Google’s integrated virtual try-on features and experimental Doppl app showed the tech giant’s interest in May. Meanwhile, multi-brand retailers like Zalando continue experimenting with body measurement-based avatars. But as Vogue Business discovered, the real innovation is happening at the startup level with three distinct approaches.
Three Competing Visions for Virtual Try-On
The Personal Stylist Approach: Alta
Alta (https://alta.ai/) launched in public beta in May, securing an $11 million seed round backed by Menlo Ventures and the Arnault family’s Aglae Ventures. Unlike traditional virtual try-on tools, Alta positions itself as a virtual personal stylist rather than just fit-tech.
The app creates hyperrealistic digital twins from user selfies, but goes beyond simple garment visualization. Users can upload their existing wardrobe, create wishlists, specify favorite brands, and receive AI-powered styling recommendations for specific occasions.
“Diffusion model technology improves every day — looking at my own Alta avatar, I’ve seen a significant evolution from January to May to today,” says Jenny Wang, Alta CEO and founder. “Some of the nuances where we’ve seen the most improvement include the ability to retain words and graphics on shirts, capture stripes or embellishments on shoes, and properly position fun accessories.”
Wang’s team focuses on complex styling challenges like multi-layer outerwear and detailed jewelry stacking. While Alta’s avatars may not be as photorealistic as competitors, the natural language prompting system makes styling recommendations remarkably accurate.
The Luxury Partnership Model: Doji
Doji (https://doji.com/) took a different path, raising $14 million in seed funding led by Thrive Capital. Currently invite-only, Doji prioritizes image quality to earn respect in the luxury fashion community.
The platform creates digital twins using advanced AI diffusion models, but emphasizes social shareability and brand collaborations. This week, Doji launched its first exclusive partnership with Peter Do, showcasing the designer’s PD-168 collection within the app.
“We see the future of shopping as being fun, but also deeply personal. There’s a utility to fit tech, yes, but there’s a deeper build at play here — trust,” says Dorian Dargan, Doji co-founder. “We feel like we’re inheriting and respecting the tradition of image making, because that’s really what the fashion industry is built upon.”
A sample avatar generated by Doji.
Peter Do’s shoppable PD-168 collection within Doji’s Look Studio.
The Universal Browser Approach: Own Every Look
A third contender is taking a radically different path. Own Every Look (OEL), available at https://owneverylook.com/, operates as a Chrome browser extension that makes virtual try-on available across any website.
Rather than requiring users to switch contexts or download dedicated apps, OEL places a floating widget directly on web pages where fashion discovery naturally occurs. This addresses a fundamental behavioral insight: most style inspiration happens organically while browsing Instagram, Pinterest, or retailer sites.
The platform combines Google’s Gemini 2.5 Flash AI with proprietary face-preservation algorithms, enabling users to experiment with both hairstyles and clothing simultaneously. By reducing try-on time from multiple minutes to under 30 seconds, OEL potentially eliminates one of virtual try-on’s biggest friction points.
Why These Approaches Matter
Each platform represents a different theory about how virtual try-on will succeed:
• Alta believes success comes from becoming an indispensable personal stylist
• Doji sees luxury brand partnerships as the key to mainstream adoption
• OEL argues that accessibility and eliminating friction will drive mass adoption
The Retention Challenge and Gamification
Getting users to engage consistently remains a hurdle. Amy Wu Martin, Alta’s lead investor at Menlo Ventures, argues that idealized AI-enhanced avatars create powerful user retention.
“It’s kind of like gamified learning — Duolingo showed us that the daily streak is a super powerful feature of retention,” Wu Martin says. “These avatars have the same power. Virtual try-on isn’t the product itself, it’s a question of what can the apps build around that daily streak?”
Alta’s power users generate around 300 looks per week, suggesting that once users start experimenting, they develop strong habits.
Beyond Fit-Tech: The Personalization Revolution
“I wouldn’t call this fit tech, it’s much bigger. I’d call it the future of shopping,” says Miles Grimshaw, Doji’s lead investor at Thrive Capital. “Right now, when you shop online, it’s like you’re an amorphous blob, at best a cookie — there’s no you. But this is bigger than just, ‘I might not return this.’ It’s: ‘I might not ever have discovered this.'”
Rather than just reducing returns, these platforms promise to transform shopping from a transactional chore into a personalized, inspirational experience. The gamified discovery tools harness consumers’ intent-based browsing to drive purchases.
“This is much more impactful down the funnel, too,” Grimshaw adds. “The breakthrough in technology is massive. It allows everyone to feel that shopping is personal, and commerce becomes uniquely fun and inspirational.”
Luxury Brand Adoption: Early Signals
The luxury sector’s adoption will be crucial for mainstream success. Doji’s partnership with Peter Do represents a significant milestone.
“Collaborating with Doji allows customers to mix and match pieces to create their ideal uniforms while seeing their individuality represented in the e-commerce experience,” says Peter Do. “This partnership enables a unique expression of the brand’s ethos.”
A look from Peter Do’s PD168 collection as styled by Doji’s AI.
Jordan Grant, co-founder of luxury shopping platform Mile Club, sees deeper potential: “It’s not just another sales channel, it’s a space where consumers are actively experimenting, discovering and building outfits. This means brands can show up in a much more organic, playful way, rather than through static ads.”
The Technology Commoditization Challenge
Matthew Drinkwater, head of the London College of Fashion’s Innovation Agency, warns of coming challenges: “There’s a bigger shift underway that both sides will have to contend with: the commoditisation of the technology itself. The underlying infrastructure for virtual try-ons — 3D body models, AI garment simulation, real-time rendering — is rapidly becoming more accessible.”
As barriers to entry fall, success will depend less on raw technology and more on compelling brand partnerships, emotional experiences, and user engagement.
A sample avatar styled by Alta’s personal shopping agent Photo: Alta Daily.
The Skeptics’ View
Despite the optimism, retail analyst Matt Powell at BCE Consulting remains cautious: “Visualising how I would look in a large blazer doesn’t get me to like how the blazer fits me when it arrives at my house. At some point, the consumer will want to try it on in-person.”
Powell points to inconsistent sizing standards and questions whether virtual try-on can truly solve the fit problem.
The Road Ahead
These three approaches — Alta’s personal styling, Doji’s luxury partnerships, and OEL’s universal accessibility — suggest virtual try-on is maturing beyond a single technical solution. Each addresses different aspects of the online shopping experience, potentially creating a more comprehensive ecosystem.
The real question isn’t which approach will win, but whether consumers will embrace virtual try-on as fundamentally as they’ve adopted online shopping itself. With return rates continuing to climb and consumer expectations rising, the pressure for innovation has never been greater.
The next year will reveal whether these AI avatars can finally solve fashion’s most persistent problem: the gap between what we imagine and what we receive.