Quick answer
OptiTech implements the AI RMF's four functions on infrastructure you may already run: Map is the AI system inventory with per-system context and classification, Measure runs trustworthiness assessments (bias, robustness, safety) as structured workflows with versioned results, Manage turns treatments into owned controls and monitoring, and Govern lives in the policy machinery, ownership model, and board reporting. One AI governance layer serves the RMF, the EU AI Act, and ISO 42001 simultaneously.
Map and Measure with maintained artifacts
Every AI system registers once with its purpose, data, models, and stakeholders; RMF context-mapping fields sit alongside the AI Act classification, so one registration feeds both. Measurement runs as recurring assessment tasks per system: bias evaluations, robustness testing, drift monitoring, each with attached results and history, which is what turns "we test for bias" from a claim into an evidence trail.
Manage as controls, not intentions
Identified risks route into the risk register and their treatments become controls with owners: human oversight gates verified in deployment pipelines, logging completeness checked through integrations, model rollback procedures tested on a calendar, and AI incidents handled through the incident flow with lessons feeding back, the Manage function's monitoring loop, running on the same machinery as everything else.
Govern with the same accountability as security
AI policies version and get acknowledged, system ownership is explicit, and the RMF profile view shows posture per function for management review. When a US enterprise's AI due-diligence questionnaire arrives in RMF vocabulary, answers draw from live governance data, and when the same customer's security team asks in CSF terms, it's the same workspace answering, consistently.
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