Audit readiness is not a narrative. It is a set of artifacts that prove controls are designed, implemented, and operating. For GenAI platforms, that evidence must cover both normal cloud operations and AI-specific workflows.
Core Evidence Pack
- Architecture diagram for the AI agent platform
- Service inventory covering cloud services, models, vector stores, identity providers, and external tools
- Data flow diagram for prompts, retrieved documents, embeddings, tool outputs, traces, and logs
- Responsibility matrix across cloud, identity, model, data, platform, and application teams
- Risk assessment for agent capabilities and data classifications
Identity and Access Evidence
- SSO and MFA configuration screenshots or exports
- Administrator role assignments and access review results
- Token scope definitions for each tool integration
- FGA or authorization model for documents, tools, and tenant boundaries
- Sample denied and allowed authorization decisions
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View on Amazon →Operations Evidence
- Deployment pipeline controls and change approval records
- Prompt template and policy version history
- Monitoring dashboards for availability, errors, latency, and token usage
- Backup, restore, deletion, and reindexing test results
- Incident tickets with timelines and recovery actions
Provider Evidence
- Cloud provider assurance reports
- Model provider data processing terms and security documentation
- Vector database and observability provider security assessments
- Subprocessor list and regional processing commitments
- Exit and portability notes for critical platform components
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Start on Educative →Bottom Line
A C5 evidence checklist for GenAI should prove control operation, not just policy intent. The strongest evidence connects a real user, an agent task, an authorization decision, a model interaction, a tool call, and an auditable outcome.
Related Solution
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Luca Berton
