As artificial intelligence (AI) systems become increasingly prevalent across diverse industries, robust compliance frameworks are essential to ensure responsible and ethical AI development and deployment. The European Union’s proposed AI Act seeks to provide a harmonized regulatory framework for AI systems, emphasizing transparency, accountability, safety, and human oversight. In this paper, we introduce an automated compliance evaluation method that aligns with the AI Act’s requirements for real-world AI systems. Our approach leverages natural language processing (NLP) techniques to extract compliance-related information from system documentation and compare it against the AI Act’s provisions. The resulting data is then integrated into a compliance knowledge graph, which facilitates the automated detection of potential gaps and the generation of compliance reports. By harnessing novel tools and technologies, this architecture streamlines the compliance evaluation process, reduces manual workloads, and supports ongoing compliance monitoring for AI systems.