Real-Time Context Engineering for AI With Databricks

Just like we don’t put crude oil in a car, we refine it into gasoline. AI can’t run on raw data either. It needs continuous, refined context. Serving fresh context is the missing architectural layer for reliable AI.

In this session, learn how Confluent Intelligence and Databricks turn operational data into low-latency context for AI agents and applications. See how Confluent’s fully managed streaming platform feeds trusted data into the Databricks lakehouse for Agent Bricks and AI/BI.

We’ll demo real-time architectures for anomaly detection, product personalization, and AI-powered data enrichment, showing how to keep ML models and LLMs grounded in the live state of your business, not stale batch snapshots.

You’ll leave with practical, streaming-native patterns to move from brittle pipelines and demos to production-grade AI on Databricks while reducing TCO.