Evidence Library
Evidence Library
Registers, checklists, questionnaires, crosswalks, and prototype files for AI assurance evidence mapping.
Library Index
Evidence HubFeatured artifact
AI Evidence Register
The AI Evidence Register is the core artifact for this library. It maps AI systems, use cases, risks, controls, owners, evidence items, review status, exceptions, and audit-readiness signals into one practical evidence structure.
- AI system and use case
- Risk and control mapping
- Control owner and reviewer
- Evidence item and source
- Review date and status
- Gap, exception, or remediation
Core templates
Templates for reviewable AI assurance evidence.
These artifacts support the first layer of AI assurance work: inventory, evidence ownership, vendor review, human oversight, audit requests, and role clarity.
Vendor AI Risk Questionnaire
Questions for third-party AI tools, embedded AI features, data use, transparency limits, monitoring, audit rights, and contractual risk.
Review Vendor AI RiskAI Audit Evidence Request List
A request structure for policies, inventories, mappings, approvals, logs, vendor documentation, exceptions, and remediation records.
View Request ListHuman Oversight Checklist
A checklist for reviewer authority, rationale, escalation, override logic, intervention records, and meaningful human review.
Explore OversightAI Governance RACI Matrix
A role-clarity artifact for system owners, control owners, risk, compliance, audit, legal, privacy, vendor risk, and governance councils.
View RACI MatrixLLM/RAG Control Matrix
Control mapping for prompts, retrieval, outputs, access, logging, monitoring, evaluation, human review, and incident evidence.
View AI Risk DomainsAI Contract Risk Checklist
Contract review prompts for vendor obligations, audit rights, documentation, limitations, incident notice, data use, and shared responsibility.
View Contract RiskCrosswalks
Framework-to-evidence mapping.
Crosswalks should connect high-level AI governance obligations to practical controls, evidence items, owners, and review workflows.
Maps AI risk management functions and categories to evidence artifacts, owners, and review signals.
CrosswalkConnects AI management system clauses to governance artifacts, control records, and assurance documentation.
CrosswalkTranslates selected AI Act obligations into evidence needs for inventory, oversight, transparency, risk management, and documentation.
CrosswalkShows where model governance overlaps with broader AI risk, vendor AI, LLM governance, human oversight, and system accountability.
Financial ServicesGridLock files
Prototype materials for evidence mapping.
GridLock GRC is the public proof-of-work layer behind this library. It shows how static artifacts can become structured evidence objects.
Initial GridLock files should include sample inventories, vendor reviews, oversight logs, audit request lists, crosswalks, and dashboard wireframes.
View GridLock GRCRepository structure
Files to publish first.
These are the first Evidence Library and GridLock files to build because they create a coherent artifact set without overclaiming product maturity.
Template Files
AI evidence register, vendor AI risk questionnaire, human oversight checklist, audit evidence request list, governance RACI matrix, and contract risk checklist.
Sample Data
Sample AI system inventory, sample vendor review, sample oversight log, sample audit request list, sample exceptions, and remediation records.
Crosswalk Files
NIST AI RMF to evidence, ISO 42001 to evidence, EU AI Act to evidence, and model risk vs. AI risk mapping.
Dashboard Wireframes
Board AI risk dashboard, audit-readiness dashboard, vendor AI risk dashboard, and evidence register summary view.
Use notice
Independent research and portfolio artifacts.
InfoSecured.ai publishes independent AI assurance research, templates, and public proof-of-work artifacts for education, review, adaptation, and validation by qualified internal teams.
Materials are not legal advice, audit advice, certification advice, regulatory advice, model-validation advice, or a substitute for organization-specific professional review.
Read Editorial StandardsBuild the evidence layer first.
Use the Evidence Library to structure AI system inventories, vendor reviews, oversight records, control mappings, evidence registers, and audit-readiness files.