AI agents are only as effective as the context they can reason over. Traditional RAG approaches can retrieve relevant information, but they often fall short when enterprise AI applications need to understand relationships, trace decisions, and reason across complex, connected data.

In this 45-minute session, Neo4j and Databricks come together to show how GraphRAG closes the gap, connecting governed lakehouse data in Databricks with the contextual power of a Neo4j knowledge graph to deliver AI agents that actually understand your business.

You'll see GraphRAG in action through a live demo, walk away with a clear picture of how the two platforms work together, and leave with resources to get started with graph enrichment in your own data pipelines.

You'll learn:

• Where traditional RAG falls short for complex enterprise AI, and how GraphRAG helps
• How Neo4j and Databricks combine to power AI agents at scale
• A practical architecture for graph-enriching your Lakehouse data
• Live demo: GraphRAG applied to a real enterprise AI workflow

Who should attend: Data and AI engineers, architects, and business leaders exploring the next frontier of enterprise AI.

Secure your place today

Can’t attend live? Register anyway and we’ll send you the recording after the session.