Frameworks · NIST AI RMF

Organize AI governance around NIST AI RMF-style operating practices

Explore how SentinelAI helps teams structure Govern, Map, Measure, and Manage-style workflows across AI systems, datasets, and evidence.

NIST AI RMF

A practical operating model for NIST AI RMF-style programs

Many organizations use the AI RMF as a way to create shared language across teams. SentinelAI supports that operating model by keeping inventory, controls, evidence, and monitoring context connected.

NIST AI RMF

Workflow coverage across the lifecycle

The platform helps teams move from one-time review to an ongoing governance loop tied to the AI systems and datasets in use.

Map business and system context early so review work starts from the right record.
Measure operational observations, unresolved gaps, and supporting evidence in a repeatable way.
Manage follow-up actions, approvals, and reporting without losing traceability.

NIST AI RMF

Why this matters to enterprise stakeholders

NIST AI RMF-style governance often spans compliance, security, risk, product, and ML teams. SentinelAI helps those groups work from shared records instead of disconnected spreadsheets and inboxes.

Related routes

Move from framework framing into product detail and evaluation

Need a walkthrough?

Map NIST AI RMF priorities to your current governance operating model

Use a guided conversation when your team wants help translating the framework language on this page into the records, approvals, and reporting workflows you use today.