As AI applications and agents move toward production, a consistent challenge emerges: how to provide reliable context and reasoning across complex, connected data.

Traditional RAG approaches handle retrieval well, but often fall short when applications require deeper understanding.

In this session, see how Neo4j and Databricks together help teams transform governed lakehouse data into a connected knowledge asset that can ground AI agents, support more reliable reasoning, and power production-ready AI workflows.

GraphRAG in Action: Building Smarter AI Agents with Neo4j and Databricks
2:00 - 2:45pm (UK) | 3:00 - 3:45pm (CEST)

We’ll cover:

• Where vector-only RAG breaks down
• How graph context enables multi-hop reasoning
• A practical integration pattern
• Real-world application of GraphRAG

This session is designed for teams looking to move from experimentation to production-ready AI.