Neo4j announced Neo4j 3.5, the native graph platform designed to drive the success and adoption of real-time business applications

Neo4j customers have demonstrated that connected graphs are a foundational element of enterprise AI applications. Graph-based data models provide the necessary context for AI applications by capturing facts related to and relationships among people, processes, applications, data, and machines. Informed by successful AI customer deployments including knowledge graphs, fraud detection, a real-time recommendation, and conversation engines, Neo4j 3.5 delivers foundational features for AI-powered systems of connection to generate tangible business value.

Data Relationships Drive Context for AI

Most current models and techniques that underpin AI systems are not optimized for detecting connections or traversing relationships. Property graphs are the ideal data structure to reveal and navigate connections and therefore discover context by linking attributes and complex relationships across the graph.

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