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Minimum Valuable Product

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

NATIVE usability

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:

catalogisation

recomendation

rendering

Parsing: