Policy is abstract
Frameworks rarely say what your architecture needs.
Policy-Driven AI Governance Review
Make Enterprise AI Governance Actionable
Enterprise AI needs governance built in—from policy to code. AIGovQ turns your use-case context into relevant governance checks, explains gaps and next steps, and provides a Governance Readiness Rating (GRR) during development.
- GenAI / LLM apps
- RAG assistants
- AI agents
- Agentic workflows
- Multi-agent systems
The problem
Governance gaps get missed while AI is built.
Gaps stay hidden
Access, oversight, and data risks go unchecked in prototypes.
Found too late
Fixes cost more once a system has users and integrations.
Teams lack a shared view
Product, risk, and compliance review different pictures.
The solution
Your use case becomes checks you can act on.
Use case
Description or README
AI review
Policy-driven analysis
Recommendations
With reasons and next steps
Readiness report
Priorities and flagged gaps
Informed by the EU AI Act, GDPR, NIST AI RMF, ISO/IEC 42001, Singapore's Model AI Governance Framework, and OWASP LLM and agent guidance. Readiness guidance only; not legal advice, certification, or a guarantee of compliance.
The Advantage
AI governance checks tailored to your use case.
Plan early with reasoned recommendations, then measure readiness once the system takes shape.
Pre-development
Recommendations with Reason
Plan governance from the start with recommended compliance checks, controls and metrics—and why they matter for your PoC or development.
Development
Governance Readiness Report
Get your Governance Readiness Rating (GRR), identify governance gaps, and prioritize actions for further implementation.
What the review covers
What is GRR?
GRR reflects the governance readiness of your AI use case, helping teams identify gaps, prioritize actions, and understand what to implement to address applicable AI governance requirements.
Applicable governance checks
AI identifies relevant governance requirements and gaps from your use-case description or documents.
Must-have governance coverage
Stated implementation receives full credit; documented plans receive 75% planning credit, not completed coverage. Missing information receives zero, and critical safeguards must be implemented.
Category-weighted readiness rating
The readiness rating is based on applicable Must-have checks across governance categories. Categories more relevant to the use case’s risks carry greater weight. Good-to-have recommendations do not affect the rating.
Critical safeguards gate
An unmet critical safeguard prevents a Ready rating, even when other coverage is strong.
Pre-development: recommendations only, no GRR.
Incomplete context: GRR is provisional and based only on what you supply. Missing information is declared, not treated as confirmed absence.
For a more comprehensive review: upload a use-case or model risk management (MRM) document. If unavailable, provide a README with supporting plans or references covering the use-case purpose and owner, risk and data classification, data sources and handling, governance safeguards, and output evaluation and testing plans. You can upload multiple documents together to provide this context.
What it is not: a measure of output quality or runtime performance, a legal certification, or an AI use-case validation or evaluation score.
How it works
Context in. Clear next steps out.
Context
Type, upload, or continue with limited context. No follow-up questionnaire.
Review
See applicable checks, their rationale, and highlighted information gaps.
Report
Download your report and follow prioritized next steps.
A glimpse of AIGovQ
Governance categoriesSee where governance needs attention
Category-level percentages bring strengths and gaps into focus, so teams can plan their next steps.
Find governance gaps. Know what to do next.
Turn AI governance from a late-stage hurdle into a design input. Find gaps while they are still easy to fix.
Get startedGuidance, not certification. Not legal advice or a guarantee of compliance.