Generative AI is only as good as the data it retrieves—but traditional RAG (Retrieval-Augmented Generation) is limited by flat, disconnected search. AI models struggle to connect structured data (databases, APIs) with unstructured data (docs, PDFs, chat logs), leading to incomplete answers and hallucinations. Enter GraphRAG—a next-generation retrieval approach powered by Neo4j. This workshop will show you how graphs unlock deeper context, better reasoning, and enterprise-ready AI applications. No graph experience needed! You’ll learn how to: - Integrate structured and unstructured data into a unified retrieval system. - Use GraphRAG to improve accuracy, explainability, and trust in AI-generated answers. - Leverage graph-native retrieval, embeddings, and hybrid search for better responses. - Apply GraphRAG to real-world use cases, from enterprise AI copilots to knowledge-driven automation. Whether you’re building AI-powered search, chatbots, or intelligent assistants—GraphRAG makes AI retrieval smarter. Join us to learn how Neo4j can take your Generative AI applications to the next level.