​​Iceberg for Agents: Elevating Lakehouse Data Into AI-Ready Context | Open Lakehouse & AI Meetup скачать в хорошем качестве

​​Iceberg for Agents: Elevating Lakehouse Data Into AI-Ready Context | Open Lakehouse & AI Meetup

This was one of four talks from the Open Lakehouse and AI Berlin Meetup on January 27, 2026. ​Title: ​​​Iceberg for Agents: Elevating Lakehouse Data Into AI-Ready Context ​​Speaker: Andrew Madson, Head of Developer Relations @ Fivetran ​​​​Abstract: AI agents fail in production because even though they're stuffed with data, they're starved for context. Better 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 AI-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: ​​Iceberg Foundations for AI - from ACID to Time Travel ​​From Rows to Relationships - The role of the semantic layer ​​Structured RAG in Practice - Fully open source ​​The 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. _____________________________________ Learn more about the OSA Community here: osacom.io