Logistics

Case Study: Elevating Chatbot Intelligence with Multi-Agent Orchestration

The organization's enterprise chatbot was built to handle complex, data-driven user queries such as KPI reporting, but its original architecture relied on traditional API calls with limited agent capabilities. A single LLM handled all decision-making, functions like order lookup were wrapped in static, predefined schemas, and there was no dynamic filtering or robust security layer. This tightly coupled design struggled to scale to new functionalities, made multi-step tasks like generating KPI reports with complex filters cumbersome and error-prone, and left the system rigid and difficult to extend.

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Elevating Chatbot Intelligence with Multi-Agent Orchestration