How to agentify contact center at enterprise scale

At Europe’s largest gas distributor, the customer contact center handled approximately 120,000 calls per month using a traditional IVR system. This resulted in 22,000 calls dropped during navigation and 10,000 calls resolved through automation. Thus the IVR was replaced with a conversational AI agent built on Databricks. The AI Gateway provides the backbone for real-time agent serving, while MLFlow tracks performance. Data is securely accessed from Unity Catalog, while the tools are served via MCP through a Databricks app. The agent interacts with callers in natural language, gathers contextual information, and accurately routes users to the correct resolution path. The solution reduced call drops during navigation by 50% and increased automated resolution by 44%. This session shares how we designed and operationalized a production-grade conversational AI on Databricks, used Unity Catalog as a governed knowledge layer for GenAI, and defined measurable KPIs.