This article explores a novel architecture that merges disparate regulatory knowledge graphs into a unified, AI‑readable model. By fusing standards such as [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/) and industry‑specific frameworks, the system enables instant, accurate answers to security questionnaires, reduces manual effort, and maintains auditability across jurisdictions.

In an environment where vendors face dozens of security questionnaires across frameworks such as [SOC 2](https://secureframe.com/hub/soc-2/what-is-soc-2), [ISO 27001](https://www.iso.org/standard/27001), GDPR and CCPA, generating precise, context‑aware evidence quickly is a major bottleneck. This article introduces an ontology‑guided generative AI architecture that transforms policy documents, control artifacts and incident logs into tailored evidence snippets for each regulatory question. By coupling a domain‑specific knowledge graph with prompt‑engineered large language models, security teams achieve real‑time, auditable responses while maintaining compliance integrity and reducing turnaround time dramatically.