Al agents fail in production because they’re overwhelmed with data but starved for context. LLM models aren’t the problem. The bottleneck is the data stack: fragmented silos, inconsistent definitions, and logic hidden in tribal knowledge. Agents need structured, reliable, and interpretable context-not just data access.In this session, we’ll show how Apache Iceberg becomes the backbone of Al-ready pipelines. You’ll learn how to elevate your Iceberg implementation from a storage format to a live context layer that powers structured retrieval-augmented generation (RAG), schema-aware agents, and autonomous reasoning grounded in truth.What we’ll cover:1. Iceberg Foundations for Al – from ACID to TimeTravel2. From Rows to Relationships – The role of the semantic layer3. Structured RAG in Practice – Fully open sourceThe session includes a live demo of a fully open- source Structured RAG stack built on Apache Iceberg, featuring semantic query translation, hybrid retrieval, and governed agent reasoning. Expect architecture diagrams, real code, and practical guidance.