This Startup Is Using AI to Help Keep Store Shelves Stocked

Shoppers around the world have experienced going to the store to buy their favorite shampoo or candy bar only to find the shelf empty. Because of inflation and high rates of employee turnover, retailers are struggling to keep their shelves stocked. Supply-chain issues caused in part by the COVID-19 pandemic have added more challenges in keeping shelves stocked and increased the product-unavailability rate from 5 percent to 15 percent during the past three years, according to the Consumer Brands Association.

StartupWisy developed an AI platform to make it easier for stores to track whether there are available products that haven’t yet been put on display. It uses image recognition to detect which items need to be restocked.

“We are not only solving a customer-experience problem but also a sustainability problem,” says IEEE Senior Member Min Chen, Wisy cofounder and CEO. “All those products that are not sold because they were not displayed get thrown away. WisyAI enables store employees to quickly get information about the stock, reduce losses, and sell [products] more effectively.”

Chen was featured on the cover of Forbes Centroamérica‘s July/August issue.

The startup, headquartered in San Francisco, received the 2022 Startup of the Year Award at the Cloud Wars Expo. Wisy also won this year’s CCU (Compania Cervecerias Unidas) Chile’s Innpacta Global Open Innovation Challenge. The competition is for startups that have designed technologies for the consumer goods and retail industry. Wisy is piloting its AI platform with CCU.

Unreliable Internet Connection

Chen, a software engineer, founded her first company, Alcenit, in 2006. The consulting business worked with companies in the banking, retail, and oil-and-gas industries to help them manage their IT department. One of Alcenit’s clients—a supermarket chain—was having problems collecting reliable ground-truth data, or data collected at scale from real-world scenarios.

Chen discovered that the retailer wasn’t the only client struggling with product data collection. [READ MORE]