Case Study

Goût

3D wardrobe scanning and AI styling for a smarter closet

Client: Goût
Sector: Fashion Tech / Consumer
Timeline: iOS & Android
Year: 2025

Challenge

People own more than they wear and face daily decision fatigue — digitizing a wardrobe and styling it intelligently required 3D capture combined with contextual AI.

Solution Approach

01Built photo-to-3D garment capture from multiple angles
02Designed an AI concierge suggesting outfits by style and weather
03Added colour-matching based on the chromatic harmony of pieces
04Integrated lookbooks, community sharing, and an in-app shop

Key Metrics

Photo → 3D

Garment capture

24/7

AI concierge

Style + weather

Styling inputs

Demo — Photo / Video

Goût video preview — A product walkthrough of 3D wardrobe capture, AI styling by weather and taste, colour matching, and integrated shopping.

Goût 3D wardrobe scanning — Photo-to-3D garment capture

Goût AI styling concierge — AI concierge outfit suggestions

Goût lookbook and colour matching — Lookbooks and colour matching

Deliverables

Cross-platform mobile app with a 3D wardrobe
AI styling and colour-matching recommendation engine
Lookbook, community, and integrated shopping flows

Outcomes

Reduced getting-dressed decision fatigue
More intentional, harmony-driven purchasing
A living, shareable digital wardrobe

Technology Stack

3D CaptureAI RecommendationComputer VisionReact NativeNode.js

Project Summary

A fashion-tech app that turns real garments into 3D models and pairs an AI concierge with wardrobe management, lookbooks, and in-app shopping.

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