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Fashion Tech: AI Design, Fit Tech and Virtual Try-On

Fashion Tech: AI Design, Fit Tech and Virtual Try-On — 2026-09-03

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Fashion Tech: AI Design, Fit Tech and Virtual Try-On — 2026-09-03

Fashion Tech: AI Design, Fit Tech and Virtual Try-On|September 3, 2026(2h ago)2 min read9.3AI quality score — automatically evaluated based on accuracy, depth, and source quality
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French startup Genlook launched a new AI virtual try-on model on September 1, 2026, enabling 10-second garment rendering from a single user photo. Meanwhile, Japanese tech firm Simplake introduced "Cocorde," a virtual try-on app that allows users to visualize outfits found on social media using their own avatars.

Fashion Tech: AI Design, Fit Tech and Virtual Try-On — 2026-09-03


Top developments


Genlook releases updated AI virtual try-on model for e-commerce

On September 1, 2026, Grenoble-based company Genlook unveiled a new version of its AI virtual try-on technology. The update focuses on speed and ease of use, allowing consumers to upload a single personal photo and see garments rendered on their body within 10 seconds. This rapid processing time is designed to directly impact e-commerce conversion rates by reducing the hesitation shoppers feel when buying clothes online.

AI virtual try-on technology interface showing quick garment rendering
AI virtual try-on technology interface showing quick garment rendering


Simplake launches "Cocorde" app for social-media-driven virtual fitting

Japanese company Simplake announced the launch of "Cocorde" (Co-Code), a virtual try-on application that leverages AI to let users visualize outfits they discover on social media or in magazines. Unlike traditional tools that require users to select items from a specific retailer's inventory, Cocorde allows users to map these external styles onto their own digital avatars. This development highlights a shift toward interoperable fashion tech that bridges social inspiration with practical fit visualization.

Simplake's Cocorde app interface for avatar-based virtual try-on
Simplake's Cocorde app interface for avatar-based virtual try-on


Local view

In Japan, Simplake's press release via PR Times emphasized the app's ability to turn "curated coordinates" from social platforms into personalized visualizations, addressing the gap between online inspiration and purchase confidence.

In Chinese-speaking markets, coverage from Sun Media (via Scoop.tw) highlighted Genlook's technology as a significant evolution in "AI virtual fitting," noting its potential to boost shopping cart conversion rates by reducing the friction of size uncertainty.


Context & numbers

No new specific financial data or return rate statistics were published in the last 7 days. Recent industry context remains focused on the broader goal of reducing e-commerce returns through improved fit accuracy, with previous reports indicating that early adopters like Zalando have seen initial engagement with over 30,000 customers shortly after launch, though definitive long-term return reduction figures are still being refined across the industry.


On the radar

  • ZOZO's LINE Integration: Following the recent launch of ZOZO's AI styling chatbot on LINE, observers are watching for further integration of conversational AI into their virtual try-on ecosystem.
  • Genlook's Retail Partnerships: While the tech is live, specific retail brand partnerships for the new 10-second model are expected to be announced in the coming weeks as e-commerce platforms look to integrate faster rendering engines before the holiday season.

This content was collected, curated, and summarized entirely by AI — including how and what to gather. It may contain inaccuracies. Crew does not guarantee the accuracy of any information presented here. Always verify facts on your own before acting on them. Crew assumes no legal liability for any consequences arising from reliance on this content.

Explore related topics
  • QHow does Genlook handle user data privacy?
  • QWhich retailers will first use Cocorde?
  • QWhat is ZOZO's chatbot doing next?

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