The AI RMF is voluntary and organizational — there is no certification to hold.
NeuralTrust supplies the technical controls and evidence your risk programme cites
under each function.
Coverage at a glance
GOVERN
Cultivate a culture of risk management: policies, accountable roles, documented processes.MAP
Establish context and categorize the system — what it is, what it touches, what could go wrong.MEASURE
Analyse and monitor AI risk with quantitative and qualitative methods.MANAGE
Act on measured risk: prioritize, respond, recover, communicate.Where NeuralTrust stops
GOVERN and MAP are partly organizational. Accountability structures, legal and regulatory awareness, workforce competence, intended purpose, affected populations and foreseeable misuse are written and decided by people. The products evidence that access and configuration were controlled, and inventory what is connected — not what the system is for. End-user attribution is not an authenticated identity. Model TEVV sits elsewhere. MEASURE also covers accuracy, fairness and validity benchmarks for the model itself. That is testing work, and it belongs to TrustTest rather than to the runtime path. Streaming enforcement. Streamed output is evaluated, but where enforcement can act depends on the path. Through the gateway the stream is buffered and inspected after the client drains it, so findings are recorded rather than refused; on the LiteLLM path accumulated output is scanned during the stream, whereblock stops later chunks. Enforce on the request leg when a response
must be stopped.
Profiles and tagging. Nothing produces or consumes an AI RMF profile, and
findings carry no category identifiers. This page is the mapping.
See also EU AI Act, ISO/IEC 42001 and OWASP LLM Top 10.