CATA is a fashion-tech startup building an AI-powered digital wardrobe platform that helps users digitise their real clothes, create a personal avatar, and virtually try on outfits for styling, shopping, and resale experiences.
Industry:
Services Provided:
AI system architecture
Virtual try-on pipeline
Garment preprocessing
Computer vision integration
Frontend web development
Cloud infrastructure setup
API development
Performance optimisation
High-fidelity garment rendering
Preservation of textures, logos, and patterns
Modular architecture for future model upgrades
End-to-end user flow (upload garment → generate try-on)
Cloud-based scalable infrastructure
Investor-ready demo system
Defined system goals, quality benchmarks, and architectural requirements.
Designed a two-stage processing pipeline and tested multiple AI approaches.
Built backend services, APIs, and frontend user flow.
Performed quality comparisons and tuning for garment fidelity.
Delivered full source code, documentation, and investor-ready demo.
Standard VTON models produced generic results and lost garment detail
The system needed to preserve logos, patterns, and fabric textures
The client required an investor-ready proof of concept
The architecture had to be modular to allow engine replacement
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