Intelligent Warehouse Management
Logistics & Manufacturing — A multi-level warehouse system processing thousands of transactions daily with AI-driven demand forecasting.
Client Context
A mid-size logistics and manufacturing company managing multiple warehouse locations with thousands of SKUs. Manual inventory counts, delayed reorder processes, and lack of demand visibility were causing stockouts, excess inventory, and fulfillment delays.
The Challenge
Inventory Accuracy
Manual cycle counts were infrequent and error-prone, leading to discrepancies between system records and physical stock.
Reorder Timing
Static reorder points did not account for demand variability, seasonal patterns, or supplier lead time changes.
Multi-Location Complexity
Inventory distributed across warehouses with different layouts, capacities, and fulfillment priorities required coordinated management.
Reporting Gaps
Management lacked real-time visibility into stock levels, turnover rates, and fulfillment performance across locations.
Our Approach
- Discovery workshop to map warehouse processes, SKU classifications, and integration touchpoints
- Designed multi-level inventory model supporting locations, zones, bins, and lot tracking
- Built real-time tracking layer with barcode/RFID integration and transaction journaling
- Developed AI demand forecasting module using historical sales, seasonality, and external signals
- Implemented automated reorder engine with dynamic safety stock and supplier lead time adaptation
Solution
A full-stack warehouse management system built on .NET and PostgreSQL with a React dashboard. The system provides real-time stock visibility, automated reorder triggers, AI-powered demand forecasting, and multi-location inventory coordination — deployed as containerized services for operational resilience.
Outcomes
95%+
Inventory accuracy
40%
Reduction in stockouts
Real-time
Multi-location visibility