Part 6/11:
Alert Generation and Feedback Loop
Alerts are generated using a hybrid rule-based and machine learning approach, depending on retailer needs and product importance. These alerts are integrated with broker systems via APIs or FTP, enabling them to visit stores, verify stock, and update records.
Crucially, the system continuously learns from broker feedback—whether an alert was accurate or a false positive—improving future predictions. Over time, the accuracy of alerts has notably improved from a mere 10% to over 55%, with projections aiming for even higher precision.