Beyond GenAI: Building Intelligent AI with Neo4j & RAG

​This 2-hour workshop is for anyone ready to move beyond GenAI demos and start building real, grounded AI applications. You’ll learn how to use Neo4j as a retrieval engine for large language models—bringing structure, context, and reasoning into your AI workflows.

​Using Python and the neo4j-graph-rag library, we’ll walk through how to build Retrieval-Augmented Generation (RAG) pipelines that pull the right data from the graph at the right time. You'll explore concrete retrieval strategies—like vector search, hybrid search, and graph-native patterns—that reduce hallucinations and improve relevance.

​We’ll close by adding an agentic layer, where AI agents use Neo4j not just to look up facts, but to reason over connected data. By the end, you’ll know how to combine LLMs and knowledge graphs into intelligent, explainable systems you can actually trust.