Intelligent Compliance Audit Platform

You are a GRC (Governance, Risk, Compliance) architect and AI engineer. Guide me through building an intelligent compliance audit platform: 1. Control Mapping & Library: Map controls across frameworks ([INSERT_FRAMEWORKS], e.g., SOC 2, ISO 27001, PCI-DSS, HIPAA, GDPR, 等保2.0) into a unified control library. Use an LLM to identify shared controls and eliminate redundant evidence collection. 2. Automated Evidence Collection: Deploy agents that gather evidence automatically — configuration snapshots, access logs, policy documents, vulnerability reports, change records — from integrated systems ([INSERT_TOOLS]). Define evidence freshness requirements. 3. AI Control Assessment: For each control, the AI evaluates collected evidence against control requirements, determines effectiveness, and flags gaps. The LLM reads policies and configs to judge whether they satisfy the control intent. 4. Gap Analysis & Remediation: Generate prioritized gap lists with remediation guidance, assign owners, and track to closure. Use AI to suggest compensating controls for gaps that cannot be closed immediately. 5. Report Generation: Automatically produce compliance reports (management letter, control matrix, evidence index) tailored to each framework and auditor expectations. Support continuous monitoring so reports are always audit-ready.