AI vendors aligned with the NIST AI Risk Management Framework
AI vendors that publicly align their AI risk management practices with NIST AI 100-1, the U.S. voluntary framework for AI risk across the system lifecycle.
NIST AI RMF (AI 100-1, January 2023) is voluntary but increasingly cited in U.S. federal procurement, executive orders, and bank regulator guidance. Vendors aligned with the framework typically publish how their AI systems map to the four core functions (Govern, Map, Measure, Manage) and the Generative AI Profile (NIST AI 600-1) for generative-AI-specific risks. Alignment is self-declared rather than certified. The vendors below explicitly reference NIST AI RMF in their public posture.
Vendors with NIST AI RMF
Anthropic
Score 11.44 · low
Amazon (AWS)
Score 12.34 · low
Salesforce
Score 12.74 · low
Adobe
Score 13.74 · low
Cohere
Score 13.79 · low
IBM
Score 14.11 · low
Microsoft
Score 14.68 · low
SAP
Score 16.63 · low
OpenAI
Score 18.36 · low
Google DeepMind
Score 18.85 · low
Oracle
Score 19.89 · low
Palo Alto Networks
Score 19.89 · low
Nuance (Microsoft)
Score 20.86 · moderate
Writer
Score 20.93 · moderate
Workday
Score 22.45 · moderate
Mosaic (Databricks)
Score 22.6 · moderate
Nvidia
Score 22.63 · moderate
SentinelOne
Score 22.96 · moderate
Scale AI
Score 23.3 · moderate
Snowflake
Score 24.36 · moderate
ServiceNow
Score 24.4 · moderate
SambaNova
Score 24.5 · moderate
PolyAI
Score 24.72 · moderate
Palantir
Score 25.09 · moderate
Databricks
Score 25.4 · moderate
Slack
Score 26.47 · moderate
GitHub Copilot
Score 27.12 · moderate
Vanta
Score 27.24 · moderate
Zoom
Score 27.35 · moderate
Kensho (S&P Global)
Score 29.4 · moderate
Khanmigo (Khan Academy)
Score 29.49 · moderate
Casetext
Score 29.77 · moderate
CoreWeave
Score 29.93 · moderate
LexisNexis
Score 30.29 · moderate
Arize AI
Score 30.6 · moderate
Moveworks
Score 30.84 · moderate
Zendesk
Score 30.94 · moderate
Galileo
Score 30.97 · moderate
Bloomberg
Score 31.1 · moderate
Groq
Score 31.46 · moderate
Abridge
Score 32.09 · moderate
Meta AI
Score 32.15 · moderate
OctoAI
Score 32.75 · moderate
Hippocratic AI
Score 33.46 · moderate
Cerebras
Score 34.64 · moderate
Darktrace
Score 35.77 · moderate
Buyer checklist
- Ask for the vendor's public NIST AI RMF Profile or its equivalent internal documentation.
- For generative AI use cases, verify alignment with the Generative AI Profile (AI 600-1).
- Cross-reference RMF's Govern function with the vendor's AI ethics board, oversight policies, and incident reporting.
- For Measure function, request red-team results and evaluation metrics across demographic and use-case slices.
- Where possible, prefer vendors that combine NIST AI RMF alignment with ISO 42001 certification for an external attestation.
Compliance is necessary, not sufficient. Holding NIST AI RMF is a meaningful baseline, but no certification covers AI-specific risk end-to-end. Layer this on top of vendor-specific diligence — sub-processor disclosure, training-data policy, model card transparency, dependency-chain mapping.