Neo4j, a graph database and analytics company, announced an integration with Google Cloud’s generative AI features in Vertex AI, Google’s large language model (LLM) platform. The result helps enterprise customers harness knowledge graphs built on Neo4j’s cloud offerings in Google Cloud Platform for generative AI insights and recommendations that are more accurate, transparent, and explainable. Specifically:
- Leverage natural language to interact with knowledge graphs: Vertex AI’s generative AI capabilities can be used to provide a natural language interface to the knowledge graph.
- Transform unstructured data into knowledge graphs: Developers can leverage new generative AI capabilities in Vertex AI to process unstructured data, structure it, and load it into a knowledge graph.
- Real-time GenAI enrichment: Neo4j databases now have the ability to call Vertex AI services in real-time to enrich knowledge graphs.
- Support for vector embeddings: Neo4j can be leveraged to provide long-term memory for large language models through support of vector embeddings. Neo4j’s Graph Data Science supports more than 60 algorithms.
- Grounding with knowledge graphs: Grounding is the ability of enterprise customers to validate responses received from large language models against enterprise knowledge graphs. Developers can use LangChain along with Neo4j-based knowledge graphs to enable grounding use cases.
