CATA Virtual Try-On

AI Fashion-Tech Platform

Overview:

CATA is a fashion-tech platform that enables users to digitise their real wardrobe and virtually try on their own clothes using a personal avatar. The project focused on building an AI-powered proof of concept that demonstrates high-quality garment rendering and investor-ready performance.

The Challenge

The client needed an investor-ready virtual try-on proof of concept that could preserve real garment textures, logos, and fabric identity without producing generic outputs. The system also had to remain modular so the rendering engine could evolve as better AI models become available.

Our Solution

We designed and developed a two-stage AI pipeline that preprocesses garments before generating realistic avatar-based try-on results. The system combined high-fidelity rendering, caching, modular APIs, and scalable cloud infrastructure to create a flexible and investor-ready virtual try-on platform.

Key Features

Two-Stage AI Pipeline

Garment Preprocessing Flow

Avatar Try-On Rendering

Modular Engine Architecture

Achieved Outcome

The project delivered a fully functional virtual try-on PoC within 8 weeks, demonstrating superior garment fidelity, modular scalability, and a strong technical foundation for investor demos and future model upgrades.