A Japanese fusion food truck in Portland faced a specific challenge—expensive seafood inventory that spoiled faster than anticipated. Without demand forecasting, overproduction was driving waste costs up while ingredient costs remained unpredictable.
The operator implemented WasteChef's AI-powered forecasting alongside daily waste logging. The forecasting model analyzes historical sales, upcoming events, and seasonal demand to predict optimal production quantities. Waste logs captured actual waste by ingredient and category.
Within 60 days, the data showed that prep overages—not spoilage—accounted for 48% of total waste. Adjusting batch sizes based on AI recommendations reduced monthly waste from $1,500 to $800.
The $700 monthly reduction represents direct savings on both waste disposal and ingredient costs. The operator notes that WasteChef's demand data has also informed smarter purchasing decisions, further reducing spoilage risk.