Reference-led
Start from actual inputs.
Use a person photo and garment references instead of relying on vague text prompts or imaginary styling.
CCLOSET is a visual AI system for testing outfits from real people and real garment references. It helps stylists, creators, and fashion teams see a look before the pull, the fitting, the shoot, or the purchase.
01 / Product
A faster way to make visual wardrobe calls.
Reference-led
Use a person photo and garment references instead of relying on vague text prompts or imaginary styling.
Built for editing
The product is tuned around preserving the human subject while applying wardrobe references clearly.
Visual comparison
Organize tops, bottoms, shoes, outerwear, and accessories into valid looks before rendering.
Private memory
Generated looks can become a private record of ideas, rankings, notes, and client-ready directions.
02 / Workflow
Fashion work is not only about producing a nice image. It is about making decisions under constraints: fit, silhouette, mood, client taste, inventory, timing, and the reality of what is available.
CCLOSET gives those decisions a visual surface. Instead of describing a look in the abstract, you can assemble wardrobe inputs and see a clean editorial preview that is easy to compare, save, and discuss.
03 / Use
Stylists
Compare options quickly and give clients a visual read before committing production time.
Fashion teams
Explore merchandising stories, campaign looks, and lookbook concepts from concrete references.
Creators
Turn a closet, pull list, or shopping shortlist into generated outfit options.
Shopping
See how a garment might behave in a styled look before buying, renting, pulling, or returning.
04 / Point of view
CCLOSET does not remove creative judgment from styling. It gives judgment a faster image-making loop: more options, clearer comparison, and less friction between idea and visual proof.
Private by design for v1: saved looks and rankings belong to the user account, not a public feed.