We built BURS for the eighty percent of your closet that never gets worn.

Most of your wardrobe is invisible to you. Eighty percent of what you own never gets worn — not because you don't like it, but because you can't see it from inside a closet at 7am. The shirt is folded behind another. The jacket is one hanger out of view. The dress was bought for a job you no longer have. The combination you'd love never occurred to you because you've never seen those two pieces at the same time.

This is the problem BURS exists to solve. Not the problem of not having enough clothes. The problem of not seeing the clothes you already have.

The unworn 80%

The number is informal — different studies put it between 50% and 80% — but the experience is universal. You stand in front of an open closet and feel that you have nothing to wear. The truth is the opposite: you have too much, and your eye is overloaded.

The closet, finally read.

BURS reads what's already there. A wardrobe scan takes under ten minutes — point a phone camera at your clothes, tap once per cluster, done. Every piece becomes structured: colour, fabric, silhouette, formality, season-fit. Your closet, for the first time, is something you can ask questions of.

Why feeds make it worse

Every fashion app, instinctively, returns to the feed. Pinterest is a feed. Whering is a feed. Instagram Shopping is a feed. The feed is a default because it transfers the cost of choosing onto the user — twenty options, scroll, scroll, scroll, eventually a pin. The feed is also where shopping lives. Every fourth tile is something you could buy. The feed is, in the end, optimised for the platform's revenue, not your morning.

BURS does the opposite. One outfit. Not twenty. The cost of choosing has been moved off the user, onto the model.

One outfit. Not twenty. The cost of choosing has been moved off the user, onto the model.

What "one outfit" actually means

Before BURS recommends anything, it reads the weather, your calendar, your location, and yesterday's outfit. The day, understood. The recommendation that arrives is specific to this Tuesday, not a generic Tuesday. If you don't like it, the AI Stylist refines in a sentence — make this warmer, soften the palette, give me something for a 7pm dinner. Every refinement uses pieces already in your wardrobe.

The week works the same way. The trip works the same way. The capsule packs the city in twelve pieces. Your closet, finally working for you.

What we will never do

• — We will never recommend pieces you don't own.
• — We will never sell your wardrobe data.
• — We will never train public models on your images.
• — We will never run ads.
• — We will never replace one outfit with twenty options.

The unworn 80%

The share of a typical wardrobe that never gets worn — the pieces you forgot, the combinations you never saw, the trip you'll repack from scratch on Sunday.

Wardrobe scan

Pointing a phone camera at your clothes; BURS uses computer vision to catalogue every piece (colour, fabric, silhouette) in under ten minutes.

Context-aware styling

Outfit recommendations that read the weather, your calendar, your location, and yesterday's outfit before suggesting anything.

— Signed: BURS, Stockholm, 2026.