AI Inventory & Warehouse Optimization

Objective

Hold the right stock at the right location to minimize working capital while keeping service levels high across the network.

Methodology

Agile delivery: demand & lead-time discovery, feature engineering on sales, stock & supplier data, model training, and back-testing.

Architecture

Cloud data lake unifying WMS, ERP, sales & lead-time data, a feature store, ML inventory-optimization models, and stock dashboards.

Solution

An automated platform delivering dynamic safety stock, reorder points, slotting optimization, and excess and obsolete-stock alerts.