Shelf Engine’s order prediction engine analyzes historical order and sales data and makes recommendations about how much retailers should order to minimize waste and increase margins. The more retailers use Shelf Engine, the more accurate its machine learning model becomes. The system also helps suppliers, because many operate on guaranteed sales, or scan-based trading, which means they agree to take back and refund the purchase price of any products that don’t sell by their expiration date. While running Molly’s, founder Stefan Kalb learned what a huge pain point this is for suppliers. To alleviate that, Shelf Engine itself buys back unsold inventory from the retailers it works with, taking the risk away from their suppliers.
Kalb, Shelf Engine’s CEO, claims the startup’s customers are able to increase their gross margins by 25 percent and reduce food waste from an industry average of 30 percent to about 16-18 percent for items that expire within one to five days. (For items with a shelf life of up to 45 days, the longest that Shelf Engine manages, it can reduce waste to as little as 3-4 percent).
Shelfnegine raised seed funding from Initialized Capital, the venture capital firm founded by Alexis Ohanian and Gerry Tan, and is now used at more than 180 retail points by clients including WeWork, Bartell Drugs, Natural Grocers and StockBox.