Neo4j, the graph database and analytics company, is announcing that it has integrated native vector search into its core database capabilities, introducing massive support for the ever-popular and -growing world of generative AI, semantic search, and LLMs.
Neo4j’s graph database technology notably surfaces and connects relationships between data entities, offering a thorough understanding of an organization’s data estate. While graph technology can certainly underpin AI systems—enabling it to reason, infer, and retrieve relevant information effectively—vector search can catapult the utility and application of AI in the enterprise, according to the vendor.
With its newfound integration, Neo4j’s vector search capability enables the detection of implicit patterns and relationships based on similar data attributes, as opposed to exact matches. This provides massive utility for search processes, including that of surfacing similar texts or documents, offering recommendations, and more, according to the company.
The combined powers of Neo4j’s graph database technology and its newfound vector search capability will drive greater accuracy while reducing potential hallucinations.
“We see value in combining the implicit relationships uncovered by vectors with the explicit and factual relationships and patterns illuminated by graph,” said Emil Eifrem, co-founder and CEO of Neo4j. “Customers when innovating with generative AI also need to trust that the results of their deployments are accurate, transparent, and explainable. With LLMs evolving so dynamically, Neo4j has become foundational for enterprises seeking to push the envelope on what’s possible for their data and their business.”
To learn more about Neo4j’s latest vector search capability addition, please visit https://neo4j.com/.