Wave3 products

Match clothing choices to personal context

Wardrobe decisions are filtered through weather, existing clothes or an individual profile.

Different approaches

Outfitcast starts with the weather; Aesty starts with the closet and a planning horizon; Catwlk adds personalized scores while shopping. The shared task is deciding what fits the current person and situation, with different inputs and without asserting that recommendation quality is proven.

What brings them together: Explicit contextual or personalized clothing, outfit or fashion-product recommendations.
Outside this wave: Generic apparel shops, image generation without styling guidance and broad shopping aggregators.

How the waves were researched

Where it sits on the board

Consumer apps

Builders in Asia 1 · Europe 1 · 1 not placed

In the wave3

Aestywww.aesty.ai · Consumer apps · by Nadia Zueva

AI stylist with digital closet, outfit planning and avatar try-on.

“See any look on your avatar”Catwlkcatwlk.com · Consumer apps · by Idil Saglam

Browser extension for assessing clothing details before purchase.

Outfitcastoutfitcast.app · Consumer apps · by Hazem Oz

Weather-based clothing and carry-item recommendations.

“Outfitcast reads the day's weather for your city and answers in one sentence — then shows the pieces behind it: what to wear, and what to take with you.”