Australian startup THDR Group has unveiled Neuono, a label it claims to be the world’s first AI fashion brand, not at the usual London Fashion Week but during London Tech Week. The company is launching with the bold claim that its system can generate up to 16 quadrillion different design combinations, and co-founder Sean Fagan believes the future of fashion lies in personalized, made-to-measure garments rather than mass-produced, ready-to-wear collections.
While several others have previously laid claim to being the first in AI-driven fashion — such as Korean designer YounHee Park in 2022 and the debut of AI Fashion Week in 2023 — Fagan argues Neuono’s uniqueness lies in its ability to bridge design and manufacturing. According to him, although AI has been used for years to generate fashion designs and predict trends, the technology had yet to fully integrate with scalable production. Neuono aims to change that by using customer inputs, such as style prompts and personal traits like age, hair color, and preferences, to develop tailor-made fashion that is both unique and deliverable. Their backend system translates these designs into detailed technical specifications—down to lapels and hemlines—that can actually be manufactured using real-world fabrics.
Fagan notes that Neuono has already established a functional supply chain capable of fulfilling these promises. Through five manufacturing partners in China, each specializing in different garment types, the company has the flexibility to produce anything from men’s suits to casual summer dresses. However, to achieve their ultimate goal of delivering personalized clothing in just five days, production will need to be moved closer to consumers through onshore or near-shore automated factories, which Fagan describes as a five-year strategic challenge akin to a Series A or B funding milestone.
THDR Group, founded in 2021 by Fagan and Timothy Aquino, began with a focus on men’s suits. The duo spent the first six months developing technology to accurately measure a person’s body using only a smartphone. Their initial app, Theodore, has been downloaded over 30,000 times, with 20,000 users completing full-body scans. The data gathered from this initiative has helped train their AI measurement system to an accuracy level they estimate at 97.5%. That same technology now powers Neuono’s personalized fitting system.
The company has already built significant brand credibility. Theodore was nominated for the National Designer Award and held a runway presentation at New York Fashion Week. Olivia Yuqi-Zhai, the company’s Chief Product Officer, played a critical role in creating the Neuono design model, combining her background in fashion and data analytics to handle the immense complexity of mixing fabrics, linings, and silhouettes. Neuono’s system can now generate up to 16 quadrillion construction variants, and Fagan himself has been hands-on—coding much of the app and backend systems. The startup has remained mostly self-funded, with the founders retaining close to 100% ownership apart from a small convertible note and an employee share scheme.
The process for users is straightforward. They begin by uploading a selfie and two body images—one from the front and one from the side—wearing either tight-fitting or minimal clothing. This enables the system to analyze key physical features and proportions. Users then input a style prompt, such as “boardroom outfit for 60-year-old man” or “garden party with young royals.” Neuono’s proprietary AI engine, named SenseThread, takes over from there, combining the user’s physical data with real-time trend research to generate custom outfit designs.
Every generated item comes with detailed specifications, including both front and back views, fabric and fit information, care instructions, and even an explanation of why each design works for that particular user. Rather than creating awkward try-on simulations with the user’s own image, Neuono opts to show an idealized model who mirrors the user’s features. Over time, the platform learns and evolves: if a user consistently dislikes certain features, like orange stripes, those are excluded from future suggestions. Actual purchases provide the strongest data, allowing the system to refine the user’s personal “style fingerprint.”
Once a user selects a garment, there’s no need to choose a size. The system has already determined this using the user’s scan data. Each piece is embedded with an NFC chip, opening the door to future smart integrations or personalized features. While Neuono currently promises a four-week delivery window, the team is working hard to shorten that timeline, aiming to collapse the entire cycle to just five days.
Fagan believes this rapid turnaround could disrupt the fast fashion industry, making made-to-measure the new norm. But getting there involves solving numerous logistical and manufacturing challenges, particularly in scaling up efficient, geographically optimized production. For now, their focus is on proving that consumers want this kind of fashion experience. If successful, the next steps involve refining speed, efficiency, and user convenience to grow market share and ultimately reshape the industry.
Not everyone is convinced, however. Prominent fashion designer Jonathan Ward, whose career has spanned from high-end couture to corporate uniforms, says that while the technology sounds impressive, it may struggle to address the nuanced reality of the human body. According to Ward, the body is a dynamic form that can change daily, and fitting complexities—particularly for women—are often underestimated. Subtle asymmetries like one hip being higher than the other or varied bust sizes are common, and capturing these nuances accurately is a significant challenge.
Nevertheless, Ward sees promise for Neuono’s technology, particularly for customers with unusual body types, including those who are very tall or require non-standard sizing. For these consumers, having access to reliable made-to-measure options could be transformative. Still, he remains skeptical about AI’s potential to disrupt the couture segment, where intricate handiwork and bespoke detailing go far beyond pattern cutting and stitching.
He also points out a practical limitation—fabric selection. As someone who never buys textiles online, Ward emphasizes the importance of physical feel, drape, and color accuracy, all of which are hard to gauge digitally. Despite these concerns, he acknowledges that Neuono’s model could be viable for tailored or semi-tailored pieces, where the complexity doesn’t exceed the capabilities of automated manufacturing.
As Neuono enters the market, it does so at the intersection of fashion and technology, where innovation continues to push the boundaries of personalization, production, and user experience. Whether it can redefine the industry or merely carve out a niche remains to be seen, but THDR Group is clearly betting on a future where AI and couture converge—at speed and at scale.
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