The new integrations with Google Cloud and Vertex AI enable organizations to access contextually rich external data to deliver accurate and explainable results in GenAI development. GraphRAG combines retrieval-augmented generation and knowledge graphs, allowing LLMs to reason, infer, and accurately answer questions and execute tasks based on factual information. The integrations simplify the implementation of GraphRAG by providing tools like Gemini models, LangChain, and Neo4j's graph database, enabling developers to quickly create knowledge graphs from unstructured data and ingest real-time data into their applications. This enhances decision-making and user experience across domains and use cases, while reducing hallucinations and improving GenAI accuracy and explainability.