The client operated a multi-channel supply chain with multiple warehouses and suppliers, facing constant overstock, stockouts, inaccurate procurement planning, and lack of synchronization between sales, inventory, and logistics systems. Planning was done manually in spreadsheets without real-time adjustments.
We designed a full-cycle AI-powered supply chain optimization system: ML-based demand forecasting, dynamic inventory optimization across warehouses, automated purchase planning, real-time stock monitoring, supplier lead-time modeling, and a centralized dashboard. The system integrates CRM, ERP, sales platforms, and warehouse systems into a single pipeline.
Demand forecasting accuracy was around 60–65%, overstock reached 25–30% of inventory, stockouts occurred on 10–15% of SKUs monthly, and planning cycles took 2–3 days manually.