Abstract: Methods, systems, and devices for automating compliance control mapping are described. In some implementations, the system may ingest compliance artifacts, including text and images extracted from uploaded files. The ingested compliance artifacts may be analyzed by generating vector embeddings for the extracted text and images. These vector embeddings may be mapped to compliance controls based on predefined criteria, with the compliance controls stored in a knowledge graph database. The mappings between the vector embeddings and the compliance controls may be stored in the knowledge graph database, facilitating efficient retrieval and association of compliance information. Some implementations may enhance the accuracy and efficiency of compliance documentation by leveraging advanced computational techniques and structured data storage.

Abstract: Methods, systems, and devices for generating automated artificial intelligence (AI) compliance mappings for regulatory standards are described. In some implementations, the system may obtain regulatory guidance and documentation to extract compliance requirements and security controls. The compliance requirements and security controls may be processed to generate source control mapping guidance and implementation evaluation criteria tailored to the security controls. The system may dynamically create prompts based on the source control mapping guidance and implementation evaluation criteria, the prompts including instructions and contextual information for evaluating system artifacts. The system may evaluate the system artifacts in response to the prompts to generate compliance mappings for the security controls.