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Supply Chain Optimization AI
Intelligent system that optimizes logistics and reduces costs by 30%
LogisticsCase study
- Problem
- Logistics teams balanced routes, inventory, and demand with static plansāleading to stockouts, rush fees, and idle inventory.
- Approach
- Created optimization and forecasting services (OR-Tools + ML) integrated with operational dashboards for planners.
- Outcome
- Roughly 30% logistics cost reduction through better routes, demand alignment, and inventory positioning.
Details
Created an AI-powered supply chain management system that optimizes routes, predicts demand, and manages inventory levels automatically, resulting in significant cost savings.
Technologies Used
PythonOR-ToolsFastAPIVue.jsPostgreSQL