GrokStyle develops computer-vision visual search that lets users point their camera at furniture and immediately find similar or identical items for purchase. The team, led by Sean Bell and Kavita Bala, spun the company out of computer‑vision work at Cornell University. Its core product is integrated into IKEA’s Place AR app, and the company is rolling out pilots and APIs for retailers. GrokStyle is also building recommendation systems and business‑intelligence tools to monetise search data. Financially, the company attracted $2 million in funding last year and has secured competitive grants from the U.S. government to support development. Management says the immediate plan is to execute on the IKEA deployment and use that proof point to win additional retail customers. GrokStyle builds computer-vision and machine-learning systems that identify furniture and home decor from photos and return close matches from a library of millions. Users can upload or take pictures from almost any angle and the service finds the same item or visually similar alternatives, with hooks into individual stores’ inventories and filters like price range. The company offers its technology as an API for retail apps and web interfaces and plans to push hard in the furniture space while exploring other visual markets. GrokStyle spun out of Cornell research—co-founder Kavita Bala led the lab where the work began and co-founder/CEO Sean Bell was a grad student—and presented foundational work at SIGGRAPH in 2015. The team is focused on improving algorithm accuracy and flexibility and is hiring engineers while working to establish partnerships with retailers. Financially, the company has secured early funding including a $225,000 NSF grant and additional investor financing.

Total raised

$3M

Funding rounds

2

Latest round

Grant

Latest activity

Mar 2018