How ready are you for NIST AI RMF?
Answer an adaptive assessment to derive your AI system’s current profile, actor role and risk tier — then get an instant, self-attested readiness score across Govern, Map, Measure and Manage, with a confidence score, top gaps and a prioritized roadmap.
- No documents to upload
- No personal info to start
- Adaptive & profile-aware
- Framework snapshot · Jun 2026
A profile-specific NIST AI RMF readiness report, instantly
Your free report turns an adaptive questionnaire into a defensible picture of where you stand across the four RMF functions — with foundational caps that cannot be averaged away and a confidence score that tells you how much to trust the number.
AI-generatedPriya Raman
Customer-facing GenAI + RAG support assistant — strong transparency and monitoring; tighten RAG security and grounding to reach verification.
View report- Risk tier
- medium
- Confidence
- 100 · High
- Controls
- 105
See how the engine profiles and scores three very different systems — a customer-facing GenAI/RAG assistant, a high-impact recruiting ranker, and an agentic CRM workflow.
A three-layer, profile- and risk-aware assessment
The assessment establishes scope, actor role, lifecycle and risk tier first, then asks only the RMF and GenAI Profile controls relevant to your derived profile.
Discovery & profile
Scope, role, lifecycle & risk tier
Adaptive RMF controls
Only the controls that apply
Final attestation & confidence
Resolve unknowns & contradictions
Instant free report
Score · gaps · roadmap
RMF & GenAI Profile modules — shown only when they apply to you
Four functions, a confidence score, and foundational caps
Govern, Map, Measure and Manage scores roll up into a confidence-adjusted readiness score. Foundational gaps cap the result regardless of the average.
Each function is weighted equally. Functions with no applicable, answered controls are marked not assessed and excluded — the remaining weights renormalize. A separate confidence score adjusts the result downward when profile facts are uncertain, and foundational caps (no inventory, no monitoring, no kill switch…) prevent a strong area from hiding a missing foundation.
Trustworthiness overlay · 7 characteristics
Shown as a secondary, explainable view of how your implemented controls map to NIST’s seven trustworthiness characteristics — without double-counting into the four function scores.
Every technology and risk path that changes your controls
The engine derives your current and target profile before showing a score — and activates GenAI, RAG, agent, high-impact and vendor modules only when they apply.
AI 600-1 GenAI Profile: provenance, misuse, safety, red-teaming.
Data-source inventory, permissions, grounding, indirect injection.
Tool scope, approval gates, kill switch, audit trail, tool-abuse tests.
Impact assessment, human review, fairness, appeal & monitoring.
Model intake, contracts, post-integration monitoring, contingency.
Early-stage system — baseline preparation path, no full score.
This assessment is informational and self-attested. It is not a NIST endorsement, certification, audit, conformity assessment, or proof that an AI system is safe, fair, valid or trustworthy. No documents or evidence are reviewed. Every session records the framework snapshot used to determine its result.
Built for the people accountable for AI risk
AI governance & GRC
Build a repeatable AI RMF current/target profile with function scores, gaps and a prioritized roadmap.
Product & engineering
See which risk practices matter most before launching RAG, agents, APIs and GenAI features.
Security & platform
Surface prompt-injection, model/data-attack, monitoring and kill-switch gaps the classic AppSec lens misses.
Model risk & data science
Operationalize MAP/MEASURE/TEVV — metrics, validation, fairness, safety and monitoring as an action plan.
See where your AI system stands against NIST AI RMF
Start the free assessment — it adapts to your profile and risk tier, and your report is ready instantly.
Start the assessment →Frequently asked questions
What does this assessment tell me?
How closely a specific AI system, use case or program aligns with the NIST AI Risk Management Framework — as a self-attested 0–100 readiness score with four function scores (Govern, Map, Measure, Manage), a trustworthiness overlay, a confidence score, your top gaps and a prioritized remediation roadmap.
Is this a NIST certification or endorsement?
No. NIST AI RMF is voluntary, outcome-focused and non-prescriptive. This is an informational, self-attested readiness diagnostic against a selected AI RMF current/target profile — not a NIST endorsement, certification, audit, conformity assessment, or proof that a system is safe, fair or trustworthy. No documents or evidence are reviewed.
Why does the score get capped?
Some gaps are foundational — no AI inventory, no documented intended purpose, no production monitoring, no human oversight on a high-impact system, or no kill switch for an agent. These cap the score so a strong area cannot average away a missing foundation.
What is the confidence score?
A separate score reflecting how complete and consistent your profile and current-state answers are. It never improves readiness — it adjusts the result downward when there are unknowns or contradictions, so you know how much to trust the number.
Do you upload documents or store personal data?
No. The assessment is self-attested and asks for no evidence uploads or personal data. You provide an email only if you want your report delivered or to resume later.
Which technologies and paths does it cover?
Predictive and generative AI, RAG, agentic/tool-using systems, fine-tuning, high-impact decisioning, public APIs and third-party model dependencies — plus the four RMF functions and ten industry overlays. The NIST AI 600-1 Generative AI Profile branches activate when relevant.