Project CIG
Contorr Image Gen — AI human models and virtual try-on
Category: Product & client work
- Built with:
- Next.js 16 (App Router)
- React 19
- TypeScript
- Tailwind CSS v4
- Prisma
- PostgreSQL
- Redis
- BullMQ
- MinIO/S3
- Fal.AI
- ComfyUI
- Express
- Zod
- argon2
- Docker
- Railway
- pnpm
- Vitest

What it is
A full-stack app that generates hyper-realistic human models with AI, then dresses them in real apparel photos via virtual try-on. A guided prompt builder and per-model parameter forms drive every render, and each output is stored with its model and parameters.
Value
Replaces studio photo shoots for apparel catalogs: on-model product imagery across body types, skin tones and settings in minutes instead of days, at a fraction of the cost. Stored parameters make winning looks reproducible across a whole product line.
Technology highlights
- Async AI pipeline — a BullMQ/Redis worker submits jobs to Fal.AI (or a self-hosted ComfyUI proxy), polls to completion and streams results into S3/MinIO, keeping the web tier responsive.
- Type-safe pluggable model registry — declarative model specs render the parameter forms dynamically and are Zod-validated end to end, so new AI models need no UI changes.
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