This article explores how Retrieval‑Augmented Generation (RAG) can automatically pull the right compliance documents, audit logs, and policy excerpts to back up answers in security questionnaires. You’ll see a step‑by‑step workflow, practical tips for integrating RAG with Procurize, and why contextual evidence is becoming a competitive advantage for SaaS firms in 2025.

Modern SaaS firms struggle with static security questionnaires that become outdated as vendors evolve. This article introduces an AI‑driven continuous calibration engine that ingests real‑time vendor feedback, updates answer templates, and closes the accuracy gap—delivering faster, reliable compliance responses while reducing manual effort.

Organizations often struggle to keep their compliance documentation up‑to‑date, leading to missed controls and costly audit delays. This article explains how AI‑driven gap analysis can automatically detect missing controls and evidence across frameworks like [SOC 2](https://secureframe.com/hub/soc-2/what-is-soc-2), [ISO 27001](https://www.iso.org/standard/27001), and [GDPR](https://gdpr.eu/), turning a manual bottleneck into a continuous, data‑backed compliance engine.

This article explores a novel AI‑driven real‑time evidence orchestration engine that continuously syncs policy changes, extracts relevant proof, and auto‑populates security questionnaire responses, delivering speed, accuracy, and auditability for modern SaaS vendors.

Manual security questionnaires drain time and resources. By applying AI‑driven prioritization, teams can identify the most critical questions, allocate effort where it matters most, and reduce turnaround time by up to 60 %. This article explains the methodology, required data, integration tips with Procurize, and real‑world results.