Just like we don't put crude oil in a car—we refine it into gasoline—AI can't run on raw, stale data. But different AI workloads need different refinements: Model training and BI need fresh, queryable, and governed tables, while AI agents and LLM applications need comprehensive, trustworthy context served in real time. In this session, see how Confluent's data streaming platform delivers both. Learn how Confluent Tableflow automatically materializes Kafka topics into Delta tables registered with Unity Catalog—no custom ingestion pipelines required—and how Confluent's Real-Time Context Engine serves that same operational data as live, governed context to AI agents on Databricks. You'll leave with a clear architecture for turning real-time data into AI-ready tables and AI-ready context, and the patterns to move from brittle pipelines to production-grade AI while reducing TCO.