Delli, Serena

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

At Italgas, Europe’s leading gas distributor both by network size and number of customers, we are spearheading digital transformation through a state-of-the-art, fully-fledged Databricks Intelligent platform. - Achieved 50% cost reduction and 20% performance boost migrating from Azure Synapse to Databricks SQL - Deployed 41 ML/GenAI models in production, with 100% of workloads governed by Unity Catalog - Empowered 80% of employees with self-service BI through Genie Dashboards - Enabled natural language queries for control-room operators analyzing network status The future of gas distribution is data-driven: predictive maintenance, automated operations, and real-time decision making are now realities. Our AI Factory isn't just digitizing infrastructure—it's creating a more responsive, efficient, and sustainable gas network that anticipates needs before they arise.