IOS mobile app.
Main goal: AI automated outfit constructor
Second goal: Merge customer’s wardrobe with all available clothes on market
Principles:
CONVENIENT solution to the problem of choosing clothes INDIVIDUAL style personalisation The main unit in the application is the outfit.
Individual elements of the clothes - tool. Decision Booster: Outfit rendering on user's digital avatar
Solving 3 types of problems:
assembling an outfit from existing clothes recommending missing items to buy, taking into account the existing wardrobe checking if the new item fits into your existing wardrobe Functionality:
Clothes capturing and catalogisation:
Auto-detection of: type, style, mood, vibe Local outfit discovery:
All possible great outfit combinations in one place Number of outfits is limited by the number of great combinations of added items. Prioritisation of the output - first - by likes, then by match-metric Filter by season and mood etc Decision Booster: Outfit rendering on user's digital avatar Outfit constructor:
Amazingly native way of selecting and evaluating Full-screen vertical outfit view Sections: top, bottom, shoes, hat, socks, outwear Auto-match with function of freezing one or few items (top/bottom etc) Decision Booster: Outfit rendering on user's digital avatar Extended outfit discovery (suggestions of available clothes in e-shops):
Great mechanics of suggesting missing clothes and finding the most relevant new ones to existing wardrobe. Decision Booster: Outfit rendering on user's digital avatar
Backend:
ML models:
Parsing:
most popular fashion e-shops
Minimum Valuable Product