Operating a restaurant at scale requires precision. Our AI Demand Predictor analyzes weather, local events, and historical sales to tell chefs exactly how much prep is needed for the day. Coupled with a Digital Smart Menu, it highlights high-margin items that are currently well-stocked in the kitchen.

Research was centered on the 'Cost of Waste.' We found that 15% of restaurant revenue is lost to over-ordering. Our ML models were trained on 3 years of transaction data to find seasonal correlations that human managers often overlook.

A 22% reduction in food waste within the first quarter and a optimized supply chain that saved the client 10% in monthly procurement costs without compromising quality.