
Problem Statement
Our client is a leading global automotive manufacturer, known for its vast supply chain network and a wide-reaching customer base. The company came across challenges related to managing sudden demand spikes. With operations spread across numerous distribution centers and production lines, accessing real-time insights from the massive flow of data across the company was becoming increasingly complex and time-consuming.

Key Challenges
- Lack of real-time systems to flag demand spikes and inventory shortages.
- Inefficient coordination between inventory, logistics, and production teams.
- Bottlenecks in approval workflows, causing slow response to market needs.
- Fragmented data sources slowing decision-making.
- High operational costs due to poor production planning or last-moment expedited shipments.

Solution Framework
Polestar analytics helped them to set up a connected system of AI agents, each putting focus on disparate parts of the supply chain to keep things running in a smooth way. We deployed:
- Orchestrator Agent: Acts as central coordinator for large or urgent orders.
- Inventory Agent: Checks stock and suggests fastest delivery from warehouses.
- Production Agent: Reviews capacity and adjusts schedules or overtime if needed.
- Decision Support Agents: Provide fulfillment options with cost and time insights.
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