StyleAtom’s founders have set out to change the way people shop online, because they believe that the future of shopping lies in discovery, not search. StyleAtom makes clothes shopping more targeted to consumers’ individual styles, showing only clothes that suit their style (or the style they aspire to) rather than clothes that manufacturers and editors push on to them. In so doing, StyleAtom increase conversion rates and basket size for retailers, and can positively impact wastage and over-buying and therefore minimising sales or return stock. StyleAtom uses visual machine learning to understand users’ personal style, without the need for long questionnaires, endless forms or in person visits.

StyleAtom helps retailers understand their customer's personal styles. It uses AI and machine learning to analyze customer supplied images or clickstream data and understand the styles within them. Its algorithm selects the clothes that most closely match the customer's style.