Regulatory Compliance in the AI Era

This website showcases the RegulaComp framework, an enabler for semi-automated regulatory compliance using semantic web technologies

RegulaComp

Semantically-powered framework for regulatory compliance

Domain-agnostic Model

The domain-agnostic model allows to capture and represent the regulatory statements structure at an abstract level, in a machine-readable format.

FAIR Regulatory Knowledge

Regulatory statements are formalized using RDF, ensuring the knowledge to be Findable, Accessible, Interoperable, and Reusable (FAIR). This provides a solid foundation for achieving and maintaining regulatory compliance.


SHACL-based Compliance

The compliance checking process leverages SHACL validation features to ensure that your data adheres to the specified regulatory requirements.

Injectable Domain-Dependent Logics

Domain-dependent computation is kept separate from the formalization model, allowing one to inject their own domain-dependent logic into the compliance checking process. This is made possible by SHACL-X.