Genlook Virtual Try-on

Genlook is an AI-powered virtual try-on platform designed for online fashion stores. It allows shoppers to upload a photo of themselves and see how clothing items from the store's catalog would look on their body, using the store's existing product photos. The process takes under 10 seconds and aims to replicate the in-store fitting experience. The platform integrates with major e-commerce platforms including Shopify, WooCommerce, WordPress, Wix, Magento, PrestaShop, and BigCommerce, and also provides a developer API for custom integrations. Genlook claims that adding virtual try-on can increase conversion rates by up to 35% and reduce returns by letting customers make more confident purchase decisions. Trusted by over 400 fashion brands, including Karl Lagerfeld, Aspiga, and Saltrock, Genlook offers a free starting tier and is praised for its ease of use and effective results. The tool is positioned as a plug-and-play solution that requires no changes to the store's product photography workflow.

Category: AI/ML
Pricing: Free

Problem solved

Online shoppers often hesitate to purchase clothing due to uncertainty about fit and appearance, leading to lower conversion rates and higher return rates. Genlook solves this by enabling customers to virtually try on products using their own photo, giving them a realistic preview of how items will look on them before buying.

Use cases

Integrate virtual try-on widget into Shopify store
Use Try-on API to add virtual fitting to a custom e-commerce application
Reduce product return rates for online apparel retailers
Increase conversion rates by providing personalized product visualization
Let shoppers see how different sizes and styles look on them before purchase
Enhance product pages with AI-generated fitting room experience

Audience

Business Users
Developers
Product Managers
Enterprise
Startups

Pros

Quick integration with popular e-commerce platforms
Fast try-on generation (under 10 seconds)
Claims to increase conversion by 35% and reduce returns
Supports a wide range of product types using existing photos
Free tier available to get started

Cons

AI-generated try-on may not perfectly represent fit and fabric
Limited to fashion/apparel products
Pricing beyond free tier may be a barrier for small stores
Requires high-quality product photos for best results
Dependence on external service for core shopping experience

Official website: https://genlook.app/

Canonical LambdaBase page: https://www.lambdabase.com/tools/genlook-virtual-try-on

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Genlook Virtual Try-on

Free

★ 12 • Updated Aug 17, 2026, 03:13 AM

Genlook is an AI-powered virtual try-on platform designed for online fashion stores.

Use Cases ▼

Integrate virtual try-on widget into Shopify store

Use Try-on API to add virtual fitting to a custom e-commerce application

Reduce product return rates for online apparel retailers

Increase conversion rates by providing personalized product visualization

Let shoppers see how different sizes and styles look on them before purchase

Enhance product pages with AI-generated fitting room experience

What Problem It Solves ▼

Key Features ▼

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Quick integration with popular e-commerce platforms

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Fast try-on generation (under 10 seconds)

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Claims to increase conversion by 35% and reduce returns

✓

Supports a wide range of product types using existing photos

✓

Free tier available to get started

Overview

Full Description ▼

The platform integrates with major e-commerce platforms including Shopify, WooCommerce, WordPress, Wix, Magento, PrestaShop, and BigCommerce, and also provides a developer API for custom integrations. Genlook claims that adding virtual try-on can increase conversion rates by up to 35% and reduce returns by letting customers make more confident purchase decisions.

Trusted by over 400 fashion brands, including Karl Lagerfeld, Aspiga, and Saltrock, Genlook offers a free starting tier and is praised for its ease of use and effective results. The tool is positioned as a plug-and-play solution that requires no changes to the store's product photography workflow.