The promise of virtual try-on is simple: see how a garment will look on your body before you buy it, and maybe you won’t send it back. The reality, for most online shoppers, is a leap of faith. NexTry AI, a Helsinki-based startup founded in 2023, is making a quiet, technical bet that a straightforward AI tool can close that gap [F6S, February 2024]. Its product is a virtual fitting room where users upload a full-body photograph, select clothing from a catalog, and generate a rendered image of themselves wearing the item [nextry.app]. It’s a familiar concept in a space crowded with ambition, but NexTry’s path is defined less by flashy augmented reality and more by the practical, neural-network-driven image synthesis its founder brings to the table.
The PhD in the Dressing Room
The company is the project of Elena Matyushenko, its solo founder and CEO, who holds a PhD and is described as having knowledge of neural networks [F6S, February 2024]. This academic grounding is a notable signal in a consumer-facing app; the core challenge of virtual try-on is not just overlaying an image, but accurately simulating how fabric drapes, folds, and conforms to a unique body shape under different lighting. While NexTry has not publicly detailed its model architecture or training data, its inclusion in programs like the NVIDIA Inception Program and support from the Helsinki Incubator suggest a focus on the underlying AI capability rather than just the front-end experience [F6S, February 2024]. The company has also expanded its toolkit to include adjacent image-generation features like Fashion Swap and Wear Print, hinting at a platform approach to AI-powered fashion visualization [Sota2, September 2026].
The Unseen Customer
For all its technical premise, NexTry’s commercial traction remains the critical unknown. The company’s website invites partnership inquiries but does not name any retailer customers, fashion brands, or marketplace integrations [nextry.app]. This is the central tension for any virtual try-on vendor: the technology must be adopted by merchants to reach consumers. The potential payoff is significant, anchored in reducing return rates, which can exceed 30% in online fashion and represent a massive cost center. Yet, convincing a retailer to integrate a new, unproven tool into their checkout flow requires demonstrable proof,metrics on conversion lift, return reduction, and user engagement that NexTry has not yet made public.
The competitive landscape is also formidable, though no direct competitors are named in the available sources. Larger players, from Amazon to major fashion retailers, are developing their own in-house solutions, while other specialized startups vie for the same merchant partnerships. NexTry’s wedge may be its simplicity and focus on the European market, but without disclosed deployments, its wedge remains theoretical.
For the end-user,the online shopper facing a wall of identical models on a retail site,the standard of care today is a combination of guesswork and generous return policies. They rely on static size charts, customer photos in reviews, and the hope that a garment’s fabric and cut will translate from screen to body. The patient population here is anyone who buys clothes online and has ever been disappointed by a fit. NexTry’s ambition is to replace that uncertainty with a generated image, a digital proxy for the dressing room experience. Whether that image is convincing enough to change buying behavior, and valuable enough for retailers to pay for, is the clinical trial this startup has yet to publish.
Sources
- [F6S, February 2024] NexTry company profile | https://www.f6s.com/company/nextry
- [NexTry] Company product page | https://nextry.app/
- [Sota2, September 2026] NexTry company profile | https://www.sota2.com/companies/nextry