Sude Mut
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Sude Mut

Istanbul, Turkiye  /  Product x Engineering x Data

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Designed and built by Sude Mut.

All work

Product Engineering · Startup

Outfique

An AI-assisted fashion product combining digital wardrobe management, personalized outfit recommendations and garment understanding from user photos.

Context

Startup

Role

Co-Founder & CFO, Software Engineer

Year

2025

Stack

ReactComputer VisionProduct StrategyConsumer Product
Outfique

Problem

What needed solving

People who own plenty of clothes still struggle to plan outfits from what they already have, and most fashion apps are built to sell new items rather than help with what is already in a closet.

What I built

Concrete responsibilities

  • The React frontend for digital wardrobe management and outfit recommendations
  • Backend integrations connecting the wardrobe, recommendation and garment-extraction flows
  • A garment isolation pipeline that extracts individual clothing items from user-uploaded photos
  • The personalized outfit recommendation workflow built on top of a user's digital wardrobe
  • The landing page used to introduce the product publicly and in investor conversations
  • Product positioning, investor presentations and day-to-day business operations alongside the engineering

System

How it fits together

A user photographs a garment; the computer-vision pipeline isolates the clothing item from the photo and adds it to their digital wardrobe. The recommendation workflow then combines wardrobe contents with user preferences to suggest outfit combinations, surfaced back through the React frontend.

Key technical decisions

What was interesting or non-trivial

Scoped garment isolation to single-item photos before attempting full-outfit photos.

A narrower input requirement for users, in exchange for meaningfully higher extraction quality to build the rest of the product on.

Result

What the system produced

A working product spanning wardrobe management, garment extraction and outfit recommendation, demonstrated through a public landing page and used in investor conversations.

What I learned

How differently a feature gets scoped when you are also the one pricing it, pitching it and supporting it, not only building it.

outfique.net

Next project

Building Height Detection from Satellite Images