Case Study

Dmagni, AI Virtual Try-On for Fashion E-commerce

A cutting-edge AI fashion platform that lets users virtually try on clothes in seconds: realistic fitting simulation across outfit styles and body types, packaged as a SaaS that e-commerce sites can integrate.

My Role
Full-stack developer
Scope
Try-on experience, AI simulation flow, SaaS packaging
Audience
Fashion shoppers and the retailers serving them
Dmagni, AI Virtual Try-On for Fashion E-commerce

The Challenge

The biggest question in online fashion is "how will this look on me?" — and it drives both abandoned carts and returns. A try-on has to look believable across body types, come back fast enough to keep the shopper engaged, and plug into stores that already exist.

  • Try-on results must look believable
  • Speed keeps shoppers in the flow
  • Different outfit styles and body types
  • Retailers need integration, not a rebuild

The Approach

Built on Next.js with an AI-powered fitting simulation that renders a realistic try-on in around 15 seconds — fast enough for high-volume retail use. The product is structured as a SaaS so e-commerce sites integrate it modularly instead of rebuilding their stores around it.

  • Realistic AI-powered clothes-fitting simulation
  • ~15-second simulation for high-volume retail
  • Compatibility across outfit styles and body types
  • SaaS model for modular e-commerce integration

What I Built

A try-on experience that answers the shopper's real question.

  • Virtual try-on in seconds
  • Realistic results across body types
  • Integration-ready SaaS packaging
  • A modern, fast shopping UI

The Outcome

Dmagni demonstrates AI applied where fashion e-commerce actually bleeds — uncertainty before purchase — with a live demo online.

  • Live demo online
  • The "how will it look on me" gap addressed
  • Productized as a SaaS, not a one-off demo

Technology Stack

Next.jsTailwindAIReact

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