AI-Powered Supply Chain Optimization

Machine learning to optimize demand, routing, and inventory across a global network.

#AI/ML#Logistics#Optimization#Python

Client

Global Logistics Company

Duration

12 months

Team Size

15 developers

Key Result

Lower operating costs

The Challenge

Multiple variables driving cost and delay across regions

Our Solution

Forecasting, route optimization, and predictive alerts

Key Results

Lower operating costs, faster deliveries, better inventory turns

Technologies Used

PythonTensorFlowApache KafkaPostgreSQLDockerKubernetes

Managing a global supply chain requires balancing demand, routes, and inventory under uncertainty. We delivered a pragmatic ML stack to improve outcomes.

What We Built

Demand Forecasts: Regional predictions for planning
Route Optimization: Constraints-aware routing
Inventory Intelligence: Reorder suggestions based on risk

Results

Operational metrics improved across cost, speed, and on-time delivery.