Azure Multi-Agent RAG System Cuts Latency 60% for High-Volume Support

A B2B SaaS platform implemented a multi-agent Retrieval Augmented Generation system using Azure Functions and Redis Cache to handle over one million daily support tickets. The new architecture replaced a monolithic RAG stack that experienced high latency and frequent errors during traffic surges. By separating policy, retrieval, and generation into isolated agents, the system reduced average response times from 1.2 seconds to below 300 milliseconds. Operational costs increased by 50% due to the more complex infrastructure, but the significant service level agreement improvements justified the expenditure. The design provides better security against prompt injection and allows independent scaling of system components.