This article introduces a novel engine that continuously ingests regulatory feeds, enriches a knowledge graph with contextual evidence, and powers real‑time, personalized answers for security questionnaires. Learn the architecture, implementation steps, and measurable benefits for compliance teams using the Procurize AI platform.

The article explains a novel self‑evolving compliance narrative engine that continuously fine‑tunes large language models on questionnaire data, delivering ever improving, accurate automated responses while maintaining auditability and security.

Security questionnaires are the gatekeepers of SaaS deals, but each regulatory framework forces vendors to start from scratch. This article shows how adaptive transfer learning can turn a single AI model into a multi‑framework powerhouse, auto‑generating compliant answers across SOC 2, ISO 27001, GDPR, and emerging standards. We walk through the architecture, workflow, implementation steps, and future directions, giving you a practical roadmap to cut response cycles by up to 80 % while preserving auditability and explainability.

This article explores the fusion of confidential computing and generative AI within the Procurize platform. By leveraging Trusted Execution Environments (TEEs) and encrypted AI inference, organizations can automate security questionnaire responses while guaranteeing data confidentiality, integrity, and auditability—transforming compliance workflows from risky manual processes to a provably secure, real‑time service.

This article explores a novel AI‑driven engine that combines large language models with a dynamic knowledge graph to auto‑recommend the most relevant evidence for security questionnaires, boosting accuracy and speed for compliance teams.