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AI Governance · NIST AI RMF
NIST AI Risk Management Framework
AI inventory, baselines, evaluations, and incident records turned into function-mapped evidence. GOVERN, MAP, MEASURE, and MANAGE, all from one continuous pipeline.
FrameworkNIST AI RMF
Functions4
TypeVoluntary
Four functions, one evidence stream.
Every claim in the report traces back to source evidence, ownership, and the workflow decision it supports.
Valuefund next
Riskcontain now
Fluencytrain where work changed
What it isType: Voluntary risk frameworkIssuer: NIST (US)Published: AI RMF 1.0, January 2023Profile: Generative AI Profile, July 2024
At a glance
Four functions, and MEASURE carries the load.
Function → Evidence
The framework names the functions. We produce the evidence under each.
NIST AI RMF functionEvidence we produce
GOVERNPolicies, accountability, oversight, risk tolerancesAI policy registry, owner map, approval workflow, threshold history, exception log, review trail
MAPContext, intended use, stakeholders, boundaries, data flowsUse-case inventory, workflow context, user population, data classification, source, impact scope
MEASURETesting, evaluation, validation, and monitoringBaseline-specific eval results, groundedness and hallucination scores, fairness checks, drift detection
MANAGERisk treatment, prioritization, response, escalationRisk queue, remediation owner, incident-resolution trace, control update, change approval
One pipeline, every framework
How the NIST AI RMF evidence gets produced.
Trace
production behavior
Classify
sensitivitysource
Evaluate
per-use-case baseline
Map
every framework
Pack
on demand
What teams should remember
Three things NIST evidence gets right.
01
NIST is the vocabulary; evidence is the work
An aligned policy is only useful when it points to live system behavior.
02
MEASURE carries the load
MAP without MEASURE is static inventory. MEASURE turns context into thresholds and evals.
03
Reuse existing risk muscle
It pairs with the model-risk, vendor-risk, operational-risk, and internal-audit workflows already running.
NIST AI RMF, asked plainly
Direct answers.
No. It is voluntary guidance, widely used when buyers or audit teams want a common AI risk vocabulary.
Keep the evidence map connected
Pairs cleanly with the rest.
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