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Real fashion on real people ®

Chicisimo has built a learning system that classifies clothes and understands people’s taste, by automatically learning from users’ outfit data.

With 5M users, we’ve built a method to learn fast and iterate, and just on iOS we’ve shipped 204 public releases and 919 pre-production releases.

Read about our tech, taste graph and ontology here, and about how we reached our first 4M users, here.

The In-Bedroom Fashion Stylist helps your shoppers decide how to wear their clothes. Right in their bedrooms! The In-Bedroom Fashion Stylist is powered by our Taste Graph and the Alexa Platform, understands the user taste, and knows what clothes the user has in her closet. It can be programmed to be connected to a retailer app and catalogue, and offer the shopper unique services with her closet and your catalogue. Read more.

The In-Store Outfit Recommender helps shoppers understand how a product they are about to buy, matches the clothes in their closet at home. The device reads the QR, extracts the images, and sends the selected image to our system where a Deep Learning algorithm extracts the descriptors of the garment. These descriptors are then sent to our Taste Graph, in charge of identifying how to best combine the new garment with the clothes in the shopper’s closet. Read more.

Our Smart Fitting Room helps shoppers make purchase decisions. When they are about to purchase a product, the Smart Fitting Room tells them how they can combine that product, with the clothes they have in their closet at home. Read more.

Our Smart Virtual Closet Technology allows your shoppers to digitally store all their physical clothes, without any friction. The clothes they bought on your site; The clothes they bought in other fashion retailers. Read more.

In Q3 2019, Chicisimo opened its API to 3rd parties. You can read about our technology in the Fashion Taste API website.


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