About the service
I am a developer working in the logical programming paradigm in Prolog, and for many years I have solved problems that ordinary imperative and machine learning approaches handle poorly. Where normal code steps through exactly how to do something, I describe facts and rules of your domain, and a logical inference engine takes care of finding answers. This declarative style is perfect for expert systems, compliance checks, scheduling, diagnosis, and any situation where rules are complex, change often, and must be auditable. When a solution needs to be explained, not just delivered, a Prolog knowledge base gives a transparent chain of reasoning instead of an opaque black box.
In practice I build rule engines encoding hundreds of business policies, constraint solvers that distribute, route, and pack resources within real limits, and knowledge bases that model taxonomies, ontologies, and relationships between entities. I write careful, well-indexed predicates, apply definite clause grammars to parse structured input, and use constraint programming over finite domains for scheduling and configuration tasks. I also connect Prolog to the outside world: expose inference logic as an API, embed it in a larger service in Python, Java, or C, and wire it to SQL and document stores so the logic layer stays cleanly separated from data and presentation.
Beyond building new systems, I rescue and clean up sprawling legacy logic, optimize queries with excessive backtracking, and add explanations and tracing so non-programmers can trust the result. Whether you need a prototype of a reasoning idea, a working expert system, or a tricky combinatorial solver—I will take the task from specification to tested, documented, and maintainable delivery.
— Expert systems and rule engines in SWI-Prolog and compatible dialects
— Constraint solving and scheduling with CLP(FD) over finite domains
— Knowledge bases, ontologies, and semantic reasoning
— Definite clause grammars for parsing and interpreting input
— Integration with Python, Java, C, SQL, and web APIs
— Refactoring, optimization, and explainable reasoning for legacy logic
In practice I build rule engines encoding hundreds of business policies, constraint solvers that distribute, route, and pack resources within real limits, and knowledge bases that model taxonomies, ontologies, and relationships between entities. I write careful, well-indexed predicates, apply definite clause grammars to parse structured input, and use constraint programming over finite domains for scheduling and configuration tasks. I also connect Prolog to the outside world: expose inference logic as an API, embed it in a larger service in Python, Java, or C, and wire it to SQL and document stores so the logic layer stays cleanly separated from data and presentation.
Beyond building new systems, I rescue and clean up sprawling legacy logic, optimize queries with excessive backtracking, and add explanations and tracing so non-programmers can trust the result. Whether you need a prototype of a reasoning idea, a working expert system, or a tricky combinatorial solver—I will take the task from specification to tested, documented, and maintainable delivery.
— Expert systems and rule engines in SWI-Prolog and compatible dialects
— Constraint solving and scheduling with CLP(FD) over finite domains
— Knowledge bases, ontologies, and semantic reasoning
— Definite clause grammars for parsing and interpreting input
— Integration with Python, Java, C, SQL, and web APIs
— Refactoring, optimization, and explainable reasoning for legacy logic
