Flutter
FigmaYour AI wardrobe, simplified.
Drape is the mobile app we built for people who want to look put-together without buying anything new or spending the morning staring into a closet. It turns the clothes someone already owns into a stylist that knows their taste.
The Problem
Most people wear a fraction of their wardrobe on repeat, not because the rest is bad, but because remembering what they own, and what goes with what, is genuinely hard. Style apps built for e-commerce make this worse: their whole business model depends on the user buying more, not styling what they have.
What We Built
Drape flips the model. It starts from the closet a person already has:
- Photo scan. Point the camera at a garment and Drape catalogs it into a digital wardrobe automatically, no manual tagging.
- Daily outfit. Each morning, Drape proposes a complete look built only from items already in the wardrobe, tuned to a stated style (the app captured this as "Warm - Minimal" in one profile) and the day ahead.
- Virtual try-on. Before committing to a look, the user can preview it on their own photo, so the outfit is seen, not just described.
- Ask Drape. A style chat that answers direct questions: what to wear to a specific event, what pairs with a new piece, how to dress a color they are unsure about.
- Saved looks. Outfits worth repeating get saved instead of re-decided from scratch.
How It Works
Drape is built in Flutter and Dart for a single codebase across iOS and Android. Garment photos are processed through an AI vision model that identifies category, color, and pattern well enough to catalog automatically and to compose outfits that actually match. The same vision pipeline powers virtual try-on, rendering a selected outfit onto the user's own reference photo. Figma carried the design system, built around a soft, editorial visual language rather than a typical utility-app look.
The Results
Drape ships as a live iOS app. What it proves out is the harder part of a wardrobe app: getting a vision model to catalog real, imperfectly lit closet photos reliably enough that the daily outfit suggestion is actually usable, not a novelty someone tries once and abandons.