Governance summary

NIST AI RMF governance page

Last updated: April 16, 2026. This page summarizes the fuller governance document in docs/NIST_AI_RMF_GOVERNANCE.md.

Govern

pAIgeBOTS assigns accountability for security, privacy, incident response, vendor review, and model configuration. Access is role-based, sessions are controlled server-side, and customer workspaces are separated by company membership.

Map

We treat healthcare, technology, and manufacturing use cases differently and scope prompts using approved context values instead of trusting arbitrary browser-supplied system prompts. We aim to minimize data collection and avoid retaining conversation content by default.

Measure

We measure system activity through audit logs, blocked PHI submissions, authentication events, and rate-limit responses. We also expect periodic review of output quality, hallucination patterns, and control effectiveness before expanding into higher-risk use cases.

Manage

We manage risk through rate limiting, PHI detection, secure headers, session encryption, vendor due diligence, documented policies, and a formal incident response process. Higher-risk claims, including HIPAA or SOC 2 statements, must track actual completed controls rather than aspirational marketing language.

Human oversight

AI outputs are decision support, not final authority. Users remain responsible for reviewing outputs before operational, contractual, legal, or patient-impacting use.

Contact

Governance questions should be sent to governance@paigebots.com.