Creating.
Building.
Delivering.
The right value — not the most value, not the fastest value. The value that endures, compounds, and regenerates. Every engagement is grounded in the Planet › People › Profit hierarchy and delivered with the precision of a trained mathematician and the judgment of a seasoned architect.
How I Work
Three phases. Every engagement. No exceptions.
Most organizations have data. Few have knowledge. The difference is meaning — the formal, machine-readable, governed representation of what your data actually means, how concepts relate to each other, and who is accountable for each assertion.
I build Unified Semantic Knowledge Layers — the connective tissue between your data assets, your AI systems, and your business decisions. Using OWL, RDF, SPARQL, SHACL, SKOS, and GraphDB, I construct knowledge graphs that don't just store information but reason over it.
- Enterprise ontology design and implementation
- Knowledge graph deployment and governance framework
- Semantic data asset inventory and classification
- SHACL constraint validation and data quality rules
- Knowledge engineering practice standup and team enablement
- GraphDB / triplestore architecture and operations playbook
AI systems deployed in healthcare, aerospace, defense, and financial services cannot fail silently. The consequences are measured in lives, not user experience metrics. Yet most AI governance frameworks are advisory documents — not executable architectures.
The AI Circuit Breaker and RDSG v2.0 are formal, implementable assurance architectures. They integrate STPA/STAMP hazard analysis, GUM-based uncertainty quantification, and morphism-grounded category theory to provide mathematically traceable safety guarantees — not just compliance checkboxes.
- AI Circuit Breaker architecture implementation
- STPA/STAMP hazard analysis for AI systems
- Requirements-Driven Semantic Gateway (RDSG) deployment
- AI governance framework design and rollout
- Uncertainty quantification and MTBH metric baseline
- Human-system interface safety analysis
Digital transformation fails when it is treated as a technology program rather than an architectural discipline. The question is never "which platform should we buy?" It is "what does our organization need to know, and how do we build the capability to know it reliably?"
I design enterprise intelligence platforms — holonic architectures that integrate semantic governance, operational data, AI inference, and human judgment into coherent, governable wholes. From smart manufacturing floors to pharmaceutical R&D pipelines to telecom network operations.
- Enterprise intelligence platform architecture
- Holonic system design and integration blueprint
- OT/IT convergence architecture (ISA-95 / Purdue model)
- Digital twin semantic layer design
- Data product and data mesh governance framework
- Platform vendor evaluation and selection support
Frontier research requires frontier architecture thinking. I bring the same structural rigor to research proposals and academic collaboration that I bring to enterprise deployments — because the quality of the question determines the quality of the answer.
Current active research includes morphism-grounded AI trustworthiness targeting DARPA DSO Thrust 4, co-authored with Paul Wach at the University of Arizona, and the AI Circuit Breaker paper submitted to INCOSE SE4AI. I also provide strategic advisory to organizations navigating the intersection of systems engineering, AI governance, and institutional policy.
- DARPA / NSF / DoD proposal architecture and writing
- Academic co-authorship and peer review preparation
- INCOSE working group contributions and framework papers
- AI governance policy design for regulated industries
- Executive briefings and board-level AI strategy advisory
- Competitive landscape analysis and positioning
How We
Work Together
Three engagement models designed around your context and timeline.
What Problem
Are You Solving?
The best engagements begin with a direct conversation about what's actually broken — not a proposal process. Let's start there.