Connected Intelligence: Operationalizing secure, cost-optimized graph architectures across multi-cloud AI

Neo4j’s Q3 2026 initiatives focused on making enterprise AI more secure, cost-efficient, and practical across Google Cloud, AWS, and Microsoft environments. The company reported expanded co-sell deployments involving property intelligence, AI-assisted codebase management, financial-services sales automation, and telecommunications security and churn prediction, with customers using Neo4j graphs to supply connected context for production AI systems. Neo4j also introduced Virtual Graph in public preview for Snowflake, Databricks, and Google BigQuery, allowing graph queries to run as optimized SQL against warehouse-resident data without copying or moving it. A reference architecture for Microsoft Copilot Studio, Okta, and Neo4j uses per-user authentication to enforce database-level access controls and reduce risks from shared AI-agent credentials. Benchmark results for Neocarta’s graph-based semantic layer indicated lower Text2SQL token use, improved query accuracy, and faster execution by retrieving only relevant catalog metadata and join paths. Looking toward Q4, Neo4j plans workshops, digital events, and joint field activities with cloud and data-platform partners to promote graph-grounded AI applications.

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