Back to selected work
Fashion · Concept

Fashion Frame

AI-powered app that helps users create outfits using their own wardrobe.

Personal AI Stylist

Product summary. A mobile-first concept that turns a photographed closet into structured wardrobe data, then uses AI to propose outfits for real life—work, weekends, and events—while learning from what you save, skip, or rate. The goal is practical daily use, not generic lookbooks.

Problem

People don’t know how to style the clothes they already own.

Solution

AI suggests outfits based on the user’s real wardrobe and preferences.

How it works

From closet to confident looks in four steps.

Upload or scan clothes

Add pieces with photos or camera capture.

AI organizes wardrobe

Sorted by category, color, and season.

Get outfit recommendations

Tailored to you—not a generic catalog.

Preview outfits

See combinations before you get dressed.

Features

Everything you need for daily styling, in one calm interface.

  • AI outfit generation

    Fresh looks from pieces you already own.

  • Smart wardrobe organization

    Structured closet data the model can reason over.

  • Occasion-based styling

    Work, weekend, events—context-aware suggestions.

  • Style learning over time

    Recommendations improve as you save and skip looks.

  • Virtual try-on Optional

    Visualize fits digitally when you want an extra nudge.

What makes it unique

  • Real wardrobe first — not one-size outfits from a generic catalog.
  • Learns your personal style from saves, skips, and feedback.
  • Built for everyday use — quick decisions on busy mornings.

Future vision

A focused roadmap for what comes next.

  • AI stylist chat
  • Social features
  • Feedback-based recommendations
  • E-commerce integration

Tech stack

Illustrative stack for a production build—API-first, mobile clients, and retrieval-friendly wardrobe data.

Concept stack: TypeScriptReact NativePythonFastAPI PostgreSQLpgvectorOpenAI APIRedis AWSFigma