Private beta

Fashion discovery, reimagined

Discover boutiques
that match your style

Social media is full of style inspo, but figuring out where nearby to shop for the clothes you actually want is still hard. rroom matches your aesthetic, occasion, and budget to local stores. Think Pinterest meets the map, built for taste.

iOS app in closed TestFlight

Hidden gems

Surface underground boutiques and local favorites, not just the chains everyone already knows.

Style matching

Upload outfits you love or pieces you own. rroom learns your taste and recommends stores that fit.

Occasion-aware

Dressing for a date, interview, or night out? Get store picks tuned to the moment, not generic search results.

The problem

Style inspo is everywhere. Local discovery isn’t.

People care about how they dress, but it can still be hard to figure out where nearby to find the clothes and styles they actually want. You might see a look online, save it, and then have no clear idea which stores around you carry anything similar. rroom helps make that easier by connecting people with nearby stores that fit their style, budget, and what they are shopping for.

The product

Built for iPhone. Currently in private beta.

The app is being tested in closed TestFlight. Here’s a look at what rroom is building.

Explore: Map-based store discovery
Match: AI style matching from your look
Wardrobe: pieces you own, stores that fit

How it works

From a look you like to stores near you

  1. 01

    Upload or explore

    Share an outfit photo, add wardrobe pieces, or browse boutiques nearby.

  2. 02

    AI reads your style

    rroom turns fashion images into style fingerprints and aesthetic signals the app can compare.

  3. 03

    Get matched boutiques

    Nearby stores are ranked by visual similarity, taste fit, distance, and hidden-gem quality.

Real taste from real people

Community reviews, outfit inspiration, and curated lists so discovery feels personal, not algorithmic noise.

Founder

Jacob Mathew LinkedIn

Jacob Mathew

Computer and Information Science & Economics, The Ohio State University

Software Engineer