AI-Powered Fashion Assistant
MyCloset
A full-stack AI fashion platform that transforms how users manage their wardrobe. MyCloset combines multimodal LLM classification, intelligent outfit recommendation, and real-time computer vision processing in a production PWA.
The Challenge
Fashion is deeply personal, contextual, and visual. Building a system that reliably understands clothing taxonomy, generates stylistically coherent outfit combinations, and processes images at consumer-grade quality required bridging multiple AI disciplines in a single product.
Our Approach
- 1Multimodal classification with Gemini for rich clothing taxonomy extraction -- type, color, pattern, material, fit, season, occasion, and brand recognition with confidence scoring.
- 2LLM-driven outfit recommendation that reasons over a user's full wardrobe, considering occasion, weather, personal style profile, and wear history to generate coherent combinations.
- 3Automated background removal pipeline with graceful degradation across Gemini image generation, dedicated ML service on Cloud Run, and segmentation mask fallbacks.
- 4Closet-level style analytics that synthesize wardrobe composition into actionable insights -- dominant colors, style descriptors, gap analysis, and shopping recommendations.
AI & Technical Highlights
Multimodal LLM Classification
Image-to-taxonomy pipeline extracting 10+ attribute dimensions from clothing photos using Gemini's multimodal capabilities.
Generative Recommendation
LLM-based outfit suggestion engine that reasons compositionally over items, context, and user preferences.
Computer Vision Pipeline
Multi-strategy background removal with automatic fallback chains between model approaches.
Style Intelligence
Closet-level analysis synthesizing wardrobe patterns into style profiles, gap identification, and personalized recommendations.