AI Inventory Features

AisleStock's demand forecasting engine processes over 40 signals per SKU to predict future sales with industry-leading accuracy. Unlike traditional statistical models that rely solely on historical volume, our AI incorporates promotions, competitor activity, local events, school calendars, and real-time weather data.

Forecasts are generated at daily, weekly, and seasonal granularities for every SKU in every store. Store managers see a simple recommended action; category managers see the full probabilistic distribution behind it.

Manual reorder point management across hundreds of SKUs and dozens of stores is a full-time job with a high error rate. AisleStock automates the entire replenishment cycle: monitoring stock levels, calculating optimal order quantities, and submitting purchase orders directly to suppliers or your ERP.

Rules-based constraints, supplier lead time variability, and minimum order quantities are all factored in. Finance teams retain approval workflows for orders above defined thresholds.

Perishable waste is one of the largest controllable costs in grocery and fresh retail. AisleStock tracks expiry dates, monitors temperature excursions, and generates dynamic markdown schedules that clear stock before it expires while maximising sell-through at the best possible price.

Waste dashboards give ops teams real-time visibility into at-risk SKUs, with automatic alerts to store staff when intervention is required.

Out-of-stock events are often invisible to HQ until they show up as lost sales days later. AisleStock's shelf analytics layer uses computer vision integration with your existing in-store cameras to detect empty shelves, misplaced products, and planogram compliance issues in real time.

Automated alerts are pushed to store associates with the exact location and recommended action. No more manual shelf walks as the primary detection method.