For automotive and industrial manufacturers, aftermarket parts inventory represents a massive working capital investment with severe availability penalties for stockouts. Manual forecasting fails to account for product population aging, regional failure rates, and seasonal demand shifts, leading to overstock in some nodes and critical shortages in others. A custom multi-agent workflow automates this by ingesting telemetry, warranty claims, and sales data to generate probabilistic demand forecasts, then orchestrates stocking decisions across a global network of distribution centers and dealers. The operational upside comes from a 15-25% reduction in global inventory carrying cost while improving part fill rates by targeting availability where failure is most likely to occur.




