Neo4j announced a multi-year Strategic Collaboration Agreement (SCA) with Amazon Web Services (AWS) to enable enterprises to achieve better generative artificial intelligence (AI) outcomes through a combination of knowledge graphs and native vector search that reduces generative AI hallucinations while making results more accurate, transparent, and explainable.
Neo4j also anncounced a new integration with Amazon Bedrock, a managed service that makes foundation models from AI companies accessible via an API to build and scale generative AI applications. Neo4j’s native integration with Amazon Bedrock enables:
- Reduced Hallucinations: Neo4j with Langchain and Amazon Bedrock can now work together using Retrieval Augmented Generation (RAG) to create virtual assistants grounded in enterprise knowledge.
- Personalized experiences: Neo4j’s context-rich knowledge graphs integration with Amazon Bedrock can invoke an ecosystem of foundation models that generate personalized text generation and summarization for end users.
- Get complete answers during real-time search: Developers can leverage Amazon Bedrock to generate vector embeddings from unstructured data (text, images, and video) and enrich knowledge graphs using Neo4j’s new vector search and store capability.
- Kickstart a knowledge graph creation: Developers can leverage new generative AI capabilities using Amazon Bedrock to process unstructured data so it becomes structured and load it into a knowledge graph.