Experience. Approach. Technology. Dataset
During the last 20 years, we've solved specific problems in car manufacturing, music and finance by introducing technologies to understand specific behaviours and automating very concrete processes.
In fashion, our success comes from 3 elements:
The Year 2000 brought a horizontal approach to AI that has proven ineffective.
These are the main differences between Legacy personalization vendors and Next-Gen Omnichannel Personalization, and about why we don't believe in black-box technologies, or in helping a shopper without knowing her taste.
Technology serves product and business teams. Not the other way around.
We've analized millions of closets that we receive via our consumer apps, millions of described outfits, and hundreds of millions of what-to-wear queries from people trying to decide what to wear for any occasion you can think of.
With this data and the experimentation layer it has provided, we've built our Taste Graph Technology as a tool to serve the business. Our experimentation layer has provided us with a learning process and some of its outputs are our In-Bedroom Fashion Stylist, the Smart Fitting Room and the In-Store Outfit Recommender.