David Gloyn-Cox

**Fractional CIO and Chief Data and AI Officer | Enterprise Architect | Data and AI Governance** David Gloyn-Cox is a Vancouver-based technology executive who works at the join between three disciplines that are usually held by three different people: the CIO seat, enterprise architecture, and data and AI governance. He operates through nemul.ai, advising founder-led and mid-market organizations on the operating model, architecture, and governance needed to grow without accumulating structural debt. As a fractional CIO, David builds the operating spine of a scaling firm: delivery, knowledge, governance, and commercial systems that survive revenue pressure rather than collapsing back into founder dependency. His current engagement is with an Ontario-based AI consultancy, where he has built the go-to-market operating system in active use by the business development function alongside the AI implementation practice. The work is deliberately unglamorous; rate cards, stage models, bid tracking, and client hubs are what turn a capable team into a company that can sell and deliver repeatably. As an Enterprise Architect, David is TOGAF-certified with 25+ years establishing architecture practices in organizations that had none. He has built capability models, application catalogs, technology standards, design authority processes, and governance gates at Manitoba Hydro, Bosa Properties, and ThoughtsWin Systems. He combines TOGAF with Open Agile Architecture and Digital Practitioner methods into named frameworks used across client engagements, and holds the throughline that matters to executives: traceability from business objective to investment decision to technical execution. In data and AI, David advises on the path from fragmented data estates to governed platforms that can actually carry analytics and AI workloads. His credential stack pairs TOGAF with the Responsible AI Professional designation (BC+AI), AIGP (IAPP), and Databricks Unity Catalog and Generative AI certifications, with CDMP nearing completion. He has led Azure enterprise data warehouse builds, metadata and taxonomy programs, and AI governance frameworks covering model integrity, privacy alignment, adversarial risk, and lifecycle control. **Practical technical background.** David remains hands-on. He has built and operated Azure data platforms and warehouse migrations; Salesforce IAM and CRM integration architecture; high-volume streaming pipelines (Kafka to BigQuery); SOC2-aligned security and compliance architecture; and, in health tech, FHIR, HL7, and DICOM interoperability under FDA SaMD constraints. His current build work is a multi-LLM document processing pipeline (AWS Textract with OpenAI and Gemini) and a multi-agent development practice using Claude and Codex: architecture agent to reference architecture, planner and documentation, development and test agents, deployment through GitHub Actions. He maintains 26+ public repositories spanning Python utilities, graph-based EA tooling on Neo4j, and BPMN modelling. He is an engineer by training, with a BEng (Hons) in Electronic and Electrical Engineering from City University, London. David serves on the board of DAMA Vancouver, chairs Big Data and Analytics West 2026, and has keynoted Google DevFest Surrey on AI governance. He writes and speaks regularly on architecture governance, responsible AI, and the operating models that let mid-market firms adopt AI without inheriting enterprise-scale risk.