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.

Procurize introduces a Dynamic Semantic Layer that translates disparate regulatory requirements into a unified, LLM‑generated policy template universe. By normalizing language, mapping cross‑jurisdictional controls, and exposing a real‑time API, the engine lets security teams answer any questionnaire with confidence, reduces manual mapping effort, and ensures continuous compliance across [SOC 2](https://secureframe.com/hub/soc-2/what-is-soc-2), [ISO 27001](https://www.iso.org/standard/27001), [GDPR](https://gdpr.eu/), [CCPA](https://oag.ca.gov/privacy/ccpa), and emerging frameworks.

This article unveils a novel architecture that blends large language models, streaming regulatory feeds, and adaptive evidence summarization into a real‑time trust‑score engine. Readers will explore the data pipeline, the scoring algorithm, integration patterns with Procurize, and practical guidance for deploying a compliant, auditable solution that slashes questionnaire turnaround time while boosting accuracy.

The Real‑Time Regulatory Change Radar is an AI‑driven engine that continuously watches global regulatory feeds, extracts relevant clauses, and instantly updates security questionnaire templates. By marrying large language models with a dynamic knowledge graph, the platform eliminates the latency between new regulations and compliant responses, delivering a proactive compliance posture for SaaS vendors.

This article explores how Procurize can fuse live regulatory feeds with Retrieval‑Augmented Generation (RAG) to produce instantly up‑to‑date, accurate answers for security questionnaires. Learn the architecture, data pipelines, security considerations, and a step‑by‑step implementation roadmap that turns static compliance into a living, adaptive system.