As AI agents move into production, memory becomes the difference between a bot that retrieves and an agent that understands. Recall gets an agent facts; reasoning gets it insight. This session shows you how Neo4j and Databricks deliver both for Databricks Agent Bricks. In this focused 30-minute session, you'll see how to give your agents memory that's built for reasoning, using Neo4j Agent Memory, and how to surface it directly through Genie One.

Graph-powered agent memory turns a standard conversational bot into something that actually understands context: connecting related facts and decisions, reasoning across them, and letting business teams query that structured memory in plain language through Genie One.

You'll learn:

• How Neo4j knowledge graphs give Databricks Agent Bricks memory built for reasoning, not just recall
• How to query and explore complex agent memory in real time using Genie One
• Architectural best practices for connecting graph memory with Databricks workflows
• Live demo: building, memory-enriching, and querying AI agents across Neo4j and Databricks

Who should attend: Data engineers, AI/ML architects, enterprise analytics leads, and tech leaders looking to scale AI agents in real-world settings.