Bridging rigorous conceptual foundations and real-world intelligent systems
I work at the intersection of formal modeling, conceptual and semanticSemantics refers to the explicit modeling of conceptual distinctions in a conceptual schema, supporting shared meaning, reasoning, and action through use, interpretation, and refinement over time. foundations, and practical application. My background includes over a decade in Banking as a Service and Ad Tech, where I've applied enterprise architecture and integration methodologies to complex business problems.
This site documents my research and explorations in formal conceptual modeling (DEMODEMO (Design & Engineering Methodology for Organisations) is a theory-based approach for modeling the essential structure of organizations in terms of actor roles, commitments, and coordination acts, explicitly separating what an organization does from how it is implemented or supported by technology, ORMORM (Object-Role Modeling) is a fact-oriented conceptual modeling method that represents domain knowledge through object types, fact types, explicit roles, and constraints, enabling precise conceptual schemas independent of data structures, processes, or system implementation.), semantic foundationsSemantic Foundations refers to the principle that semantics belongs to conceptual schemas, purpose belongs to intent, execution belongs to agents, and authority and accountability belong to humans., and the integration of symbolic and learning-based approaches to AI. I build tools and demonstrations to explore how disciplined conceptual models can power more explainable, maintainable intelligent systems.
This demonstration application was built using the ORM Toolkit with AI code assistance. It shows how formal conceptual models drive intelligent decision systems with explainable logic and semanticSemantics refers to the explicit modeling of conceptual distinctions in a conceptual schema, supporting shared meaning, reasoning, and action through use, interpretation, and refinement over time. validation—the same approach I apply to API integration projects.
These tools demonstrate how rigorous conceptual models can power explainable decision logic in real applications.
Web-based conceptual modeling tool for Object-Role Modeling. Features AI-powered assistance for model creation and validation.
Note: This is a proof-of-concept. Access as guest (5 AI requests/hour) or with Google sign-in (unlimited). Publishing service currently disabled.
Design precise, formal models of business domains using DEMO and ORM methodologies to create foundations for intelligent systems.
Develop structured semantic representations that support reasoning, explainability, and intentIntent is a modeled expression of purpose that connects conceptual distinctions to goals, situations, and expected outcomes without prescribing execution.-driven, AI-assisted decision-making in complex domains.
Design and implement complex API integrations for Banking as a Service, Ad Tech, and multi-provider systems using systematic methodology.
Integrate symbolic logic with learning systems to create explainable and robust neuro-symbolic AI applications.
Build working POCs using AI-assisted development and formal modeling to validate feasibility and demonstrate technical approach.
Lead implementation teams through complex integration projects with systematic methodology and clear architectural guidance.
Interested in discussing knowledge modeling, conceptual schemasConceptual Schema is a formal model that captures the relevant conceptual distinctions of a domain—objects, relationships, constraints, and rules—independent of implementation or execution. and semanticSemantics refers to the explicit modeling of conceptual distinctions in a conceptual schema, supporting shared meaning, reasoning, and action through use, interpretation, and refinement over time. foundations, or potential collaboration? Feel free to reach out.