Most AI agents lose context fast. In this session, you’ll learn how to combine Microsoft Foundry with Neo4j to build decision-aware agents with lasting, dynamic memory.

Through guided exercises, you’ll use Microsoft Foundry to develop and orchestrate your agent experience while leveraging Neo4j to model relationships, store conversation history, and retrieve the context that matters. You’ll see how graph-powered memory can enrich your agent stack with persistent knowledge, enabling assistants to make more informed decisions, personalize interactions, and maintain continuity over time.

Discover how Microsoft Foundry and Neo4j work together to provide the context and memory layer needed for more intelligent, stateful AI agents.