PointAI, a Simulation AI company built by a former Microsoft Research scientist, says it can render a photorealistic virtual try-on in under a second — without touching a generative AI model at all. That claim is now being tested inside one of India’s largest fashion retailers, and it points at a fork in the road for how “AI try-on” gets built going forward.
Two Very Different Ways to Fake a Fitting Room
Most of the virtual try-on tools that have made headlines this year — including the DressX-powered luxury pilots we covered a few weeks back — work the same way under the hood: a generative model looks at a photo of a shopper and a photo of a garment, then predicts, pixel by pixel, what the combination should look like. It’s often convincing, but it’s still a guess. The model has never actually draped that fabric on that body; it’s pattern-matching against everything similar it’s seen before.
PointAI is pitching something structurally different. Rather than asking a generative model to imagine how a garment would fall, its Simulation AI pairs proprietary AI models with physics-based simulation — the same category of engine used to animate cloth in film and games — to calculate how a specific fabric actually behaves on a specific body shape. According to the company, that combination renders a result in under a second, trained across more than 200,000 body-type variations, at roughly 1/100th the per-image cost of generative try-on APIs, which the company says typically run around $0.15 per image and take 30 to 60 seconds to generate.
Why a Retailer the Size of ABFRL Is Paying Attention
The technology isn’t just a lab demo. PointAI is already working with Aditya Birla Fashion and Retail Limited (ABFRL) — one of India’s largest fashion retail groups, with a footprint that runs into the thousands of stores — where the two companies showcased an in-store virtual trial setup and an AI styling advisor at ABFRL’s Fashion Excellence Day in Mumbai this week. Nothing is formally signed for a nationwide rollout yet, but the demo reportedly covered a mix-and-match trial room experience alongside a broader evaluation across ABFRL’s roughly 3,000 stores. PointAI has also shown the same underlying tech at Bharat Tex 2026 alongside Gokaldas Exports, in front of global manufacturing clients including Adidas, Aerie, Banana Republic, M&S, and Puma, and separately lists Amazon, Flipkart, Myntra, and Rakuten among its retail relationships.
That’s a meaningfully different sales pitch than most AI fashion tools make. The company isn’t leading with “look what generative AI can do” — it’s leading with independence from generative AI. Its argument is that not relying on a commercial foundation model API from OpenAI or Google gives enterprise retailers something generative try-on can’t: predictable unit economics, no exposure to a third party’s pricing changes, and tighter control over how shopper photos are processed. For a retailer running try-on at the scale of a few thousand stores, a $0.15-per-render generative pipeline and a 30-to-60-second wait aren’t rounding errors — they’re the difference between a feature that scales and one that gets quietly shelved.
What This Signals for the Rest of the Industry
PointAI founder Nitin Vats framed the bet in blunt terms: “The last decade of commerce was built for people who browsed. The next is built for people who delegate to agents.” That’s consistent with what we’ve been tracking across AI fashion coverage all year — brands are racing to make discovery and fit-checking instant enough that a shopper (or eventually a shopping agent acting for them) doesn’t bounce before converting. Where PointAI’s approach stands out is in treating “instant and cheap” as a technical requirement to be engineered around, rather than a trade-off to accept as the price of using generative AI.
None of that guarantees physics-based simulation wins out over generative approaches long-term — plenty of retailers will still choose GenAI try-on for its flexibility in rendering totally novel styling combinations a physics engine hasn’t modeled. But it’s a useful reminder that “AI try-on” isn’t one technology; it’s a category with genuinely different engineering bets underneath it, and the bet that wins at enterprise scale may not be the one that gets the most demo-day attention.
FAQ
Is PointAI’s virtual try-on already live in stores?
Not at full scale yet. PointAI has demoed its technology with Aditya Birla Fashion and Retail (ABFRL) at a Mumbai event this week, with a broader rollout across ABFRL’s roughly 3,000 stores reportedly under evaluation — no formal nationwide agreement has been announced.
How is “Simulation AI” different from the generative AI try-on tools other brands use?
Generative try-on tools predict what a garment-on-body image should look like based on patterns learned from training data. PointAI instead pairs AI models with physics-based simulation that calculates how a specific fabric actually drapes on a specific body shape, which the company says is faster and cheaper to run at scale.
Which retailers is PointAI already connected to?
Beyond the ABFRL pilot, PointAI lists relationships with Amazon, Flipkart, Myntra, and Rakuten, and it showcased the technology alongside manufacturer Gokaldas Exports at Bharat Tex 2026 in front of brands including Adidas, Aerie, Banana Republic, M&S, and Puma.
By Michelle Jones, Fashion News GF
Source: The Print / ANI Press Releases, “PointAI, AI Partner to Aditya Birla Fashion, Eyes Rollout of One-Second Virtual Try-On Technology Across ABFRL Stores” (published August 22, 2026), https://theprint.in/ani-press-releases/pointai-ai-partner-to-aditya-birla-fashion-eyes-rollout-of-one-second-virtual-try-on-technology-across-abfrl-stores/3022239/