Demand Forecasting AI for Inventory Optimization

As technical support for an AI systems company, we guided the adoption of state-of-the-art time-series forecasting methods. The target was a system managing merchandise stock and demand.

What we did

Product demand is strongly driven by seasons, trends and sales events, and turnover is fast. Simply extrapolating past sales has limited accuracy. Drawing on current research, we evaluated and selected modern forecasting methods and supported their integration into the existing system.

Outcome

Forecast accuracy improved, allowing ordering and inventory-allocation decisions to be based on predictions. The system now curbs both overstock and stockouts, reducing inventory losses.