Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
Enterprise AI deployments face significant challenges at the database layer rather than the model layer. The data stack was not designed for AI agents, resulting in rising costs and inefficiencies. A ...
Retail Banker International on MSN
Interview: Neo4j global head of finserv Michael Down on the $442bn fraud problem banks can't see
Michael Down, Global Head of Financial Services at Neo4j, tells RBI Editor Douglas Blakey that the fraud challenge for banks ...
Dynamic family data entry, deletion, and relationship querying using AIML + Neo4j + Streamlit. stage 2's Prolog/Python reasoning layer has been replaced with a Neo4j graph database. The AIML chat ...
Tracing product flow Analyzing supplier dependencies Tracking supplier risks and dependency chains Understanding APIs (Active Pharmaceutical Ingredient) dependencies and connections Identifying risks ...
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