FASHN

FASHN

FASHN is a virtual try-on platform and API that renders any garment realistically on a chosen model or person. FASHN takes a product image plus a target model and generates a photo of that garment being worn, and as of 2026 it also converts flat-lay shots into on-model imagery, creates reusable AI models, and generates packshots for product pages. FASHN is available as a self-serve app and a developer API, with outputs licensed for commercial use. It deliberately excluded intimate apparel from training to reduce misuse.

Production credibility: Founded 2022 and based in Tel Aviv with a small team. Built its try-on in-house as a multi-model pipeline anchored by a roughly 1.2-billion-parameter model trained from scratch on about 4 million curated fashion images, and distributes through partners including fal.ai. Outputs across its endpoints carry commercial-use licensing for ecommerce and marketing.

Key Features

• Virtual try-on: render a garment on a model or person from a product photo
• Product-to-model: convert flat-lay or ghost-mannequin shots into on-model imagery
• AI model creation for consistent, reusable fashion models
• Model swap that preserves product, pose, and lighting
• Packshot generation for catalog-grade product images
• Developer API with commercial-use licensing on all endpoints

Ideal Use Case

Ecommerce brands, marketplaces, and developers who need on-model product imagery and virtual try-on at scale — replacing or supplementing photoshoots with API-generated images for product pages and campaigns.

How FASHN differentiates

Botika and similar tools focus on turning existing photos into on-model shots for stores. FASHN leads with a developer-grade try-on API backed by an in-house model pipeline, so teams can build try-on and product imagery directly into their own apps and catalogs. It is positioned as a B2B ecommerce product and deliberately excluded intimate apparel and swimwear from training to reduce misuse, though standard consent and likeness considerations still apply to any person-and-clothing tool.

FAQ

Q: What does FASHN do? A: FASHN generates realistic images of clothing worn by a model or person from a product photo, plus on-model imagery, AI model creation, and packshots for ecommerce, via a self-serve app and a developer API.

Q: FASHN vs Botika? A: Both target ecommerce fashion imagery; FASHN leads with a developer-grade try-on API and an in-house model pipeline, while Botika focuses on turning existing photos into on-model shots for stores.

Q: Who is behind FASHN? A: FASHN is a Tel Aviv startup founded in 2022 that built its own multi-model pipeline anchored by a roughly 1.2B-parameter model trained on about 4 million fashion images.

Q: Is there a free option? A: There is a free trial with starter credits to test the tools, then paid monthly plans and separate metered Developer API pricing.

tl;dr

FASHN is an AI virtual try-on platform and API that renders any garment realistically on a model or person, plus product-to-model imagery, AI models, and packshots for ecommerce. Built in Tel Aviv on a 1.2B-parameter in-house model; ships via fal.ai. A developer-first alternative to Botika and Pixelcut.