This article demonstrates how to integrate LangChain4j with Neo4j, a high-performance graph database, to perform graph-based question answering. LangChain4j is a Java library that simplifies the integration of AI/LLM capabilities into Java applications. By integrating LangChain4j with Neo4j, developers can leverage advanced language models and graph data to answer complex queries based on the relationships and properties stored within the database. The article covers various aspects of the integration, including the creation of an Embedding Store instance, storing embeddings in a Neo4j database, executing searches, and implementing hybrid search capabilities. Additionally, it provides examples of how to use the LangChain4j framework with Neo4j for content retrieval and graph-based question answering. The article also discusses future updates and improvements to the LangChain4j library, including new features such as LLMGraphTransformer and GraphRAG concepts.