Shopagon

Visual intelligence for real-time retail personalization

Next Generation Personalization

Related Items

Artificial intelligence that provides suggestions based on the personal style and current intent of each user.

Adaptive Search

Search technology that enables users to intuitively search your catalogue.

Visual Search

Allow users to interactively find relevant items from any image inspiration.

Recommendation Emails

Learn your users’ visual styles to recommend things they will love.

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About Us

Tamara's lifelong passion for artificial intelligence and fashion led her to become a leader in research on computer vision for clothing and style recognition, and to co-found Shopagon with Alex in 2016. With a PhD from UC Berkeley and over 15 years of experience developing research in computer vision and natural language processing, Tamara is currently on leave from her position in the computer science department at UNC Chapel Hill to pursue her dream of creating a smart, personalized, shopping experience.
Alex is an expert in computer vision and machine learning with 18+ years of research experience and an ongoing goal of helping computers understand the world around us. He has worked at a number of universities across the country from UC Berkeley to Columbia and is currently on leave from his position as an Associate Professor in the computer science department at UNC Chapel Hill to build Shopagon. He has been collaborating with Tamara for 13+ years.
Jonathan joined the team in September 2016 after working for 3 years as a software engineer at Facebook, Vurb, and Originate. With an MS from UCLA and a BS from UC Berkeley, Jonathan brings real-world expertise in building computer vision and search technologies to Shopagon.