Better Discovery
Users find relevant products faster because recommendations are shaped by real wardrobe, style, and size signals.
AI Fashion Personalization Engine
Maz Style
An AI-powered personalization engine for fashion discovery.
Core Sub-Features
Three signals. One personalization engine.
Maz Style combines wardrobe context, personal style signals, and size preferences to create recommendations with stronger purchase intent.
Wardrobe Intelligence
Explore featureMy Closet
Digitize the user’s real wardrobe and recommend outfits, missing pieces, and complementary products.
Maz Style
Explore featureStyle Finder
Analyze user behavior and visual inputs to understand personal style and surface relevant products.
Fit Intelligence
Explore featureMy Size
Save size preferences across categories and recommend products that match both style and fit.
Why It Matters
Personalization that improves discovery, intent, and seller relevance.
Maz Style turns scattered user signals into a decision layer that makes fashion discovery more useful and commerce more targeted.
Higher Purchase Intent
Recommendations become more actionable because they reflect what users own, prefer, fit into, and are likely to buy.
Smarter Seller Matching
Seller inventory can be surfaced to users with stronger relevance, improving product visibility and conversion quality.
Founder-ready positioning