Neo4j's graph databases can query data in a way that mirrors how real-world entities are connected - a boon for AI. Data in graph databases is expressed as a 'knowledge graph,' which grounds AI in context that can inform its outputs.
'We conceived the idea for the first property graph database during a flight to Mumbai in 2000,' Eifrem told TechCrunch. 'We sketched it on a napkin - one that I wish I still had but, alas, has since disappeared.'
Neo4j's software enables companies to build, orchestrate, and deploy graph databases. Like other graph databases, Neo4j's store data as nodes, relationships, and properties.
With the rise of AI, Neo4j has invested heavily in what it calls 'GraphRAG,' a technique that enables AI to retrieve data from external sources.
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