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The MachineCon

New York 2026

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Michael Moore

Senior Director, Strategy & Innovation, Neo4j, Inc. Field CTO

Michael works with customers and partners to help build compelling services and products leveraging Neo4j’s industry-leading graph database and graph analytics platform.
Michael has over 25 years experience delivering high-value enterprise analytics solutions and portfolios for startups, agencies and Fortune 100 companies. Michael has architected and delivered full-stack graph applications across multiple industries and use cases and has deep expertise in knowledge graph design, semantic layer graphs and GenAI.
Michael is a member of the NSF / White House Office of Science and Technology Open Knowledge Network (OKN) Working Group, focused on strategic supply chain digital twins.
Michael has been working with Neo4j graph databases and graph analytics since 2013, and prior to joining Neo4j, Michael was an Executive Director at EY where he established EY’s practice in Knowledge Graphs and AI.
Prior to EY, Michael was at Microsoft where he managed a global portfolio of over 65 applications in the connected sales and marketing space for Microsoft’s B2B and partner ecosystems. Michael is based in Redmond, WA.

All Sessions by Michael Moore

  • MachineCon 2026

    Jul 24, 2026

  • 11:25  - 11:45
    While enterprise AI promises unprecedented efficiency, up to 80% of projects fail due to LLM hallucinations, "black box" obscurity, and a lack of proprietary context—risks that FinTech, Pharma, and Manufacturing leaders simply cannot afford. Knowledge graphs bridge this gap by establishing a trustworthy, explainable semantic layer that transforms siloed enterprise data into connected, agent-readable context. By integrating Graph Retrieval-Augmented Generation (GraphRAG), Model Context Protocol (MCP), and Agent Memory Graph tools, this knowledge graph-based approach improves the accuracy of LLM responses while providing an ironclad, fully auditable map for autonomous AI agents to navigate. A well-constructed semantic layer ultimately helps organizations de-risk their AI investments, delivering highly secure, governable, and accurate generative AI solutions with unmatched speed to value.