As you might have experienced, LLMs are powerful but not always trustworthy assistants. With a combination of a knowledge graph and vector search, you can provide the LLM with the correct, relevant context information it needs to answer your user's questions. GraphRAG is an advanced RAG (retrieval augmented generation) pattern in the Haystack-Neo4j integration. In this talk, we'll explain and demonstrate the building blocks of such an approach and show an example of code and live in action. Of course, nothing is perfect; it's important to walk through the challenges of building such GenAI apps and how to address them.