[Munich] Plug-and-Play AI Memory with Neo4j Knowledge Graphs & AI Agents

“Plug-and-Play AI Memory with Neo4j Knowledge Graphs & AI Agents” by Zaid Zaim (Developer Advocate at Neo4j) AI agents are becoming core to modern applications, from copilots that assist knowledge workers to autonomous systems that manage complex workflows. Yet one major challenge remains: memory. Without it, agents lose context, forget past interactions, and often hallucinate—undermining trust and reliability. In this session, you’ll learn how to use a plug-and-play Neo4j knowledge graph as a powerful memory layer for your AI agents. Knowledge graphs capture not just facts, but relationships, allowing your agent to build a living model of conversations, decisions, and data over time. Combined with modern AI services, this approach helps ground responses, reduce hallucinations, and create a feedback loop where agents become more adaptive, contextual, and trustworthy. Through a live demo, we’ll show how to connect graph-powered memory into your AI workflows with minimal setup, so you can build copilots and agentic applications that don’t just respond in the moment—but remember, learn, and evolve with your users.