Last updated: August 2026
Read this first. This article is an evaluation guide. It is not a certification claim, a legal opinion, or a substitute for the ISO/IEC 42001 standard, an accredited auditor, or professional advice.
Organizations adopting agentic AI have to answer two different questions:
- What policies and controls govern the system?
- Can we demonstrate that those controls actually operated?
ISO/IEC 42001 addresses the first question. It defines the requirements for an artificial intelligence management system, or AIMS: the organizational machinery of governance, risk management, accountability, monitoring, and continual improvement. Certification applies to that management system, never to a software product. Installing SAFi does not make an organization certified or compliant with anything, and nothing in this article says otherwise.
SAFi addresses the second question. It is an open-source runtime governance engine for agentic AI. It enforces policies in real time, governs tool calls, and records every decision for audit.
The gap between having a policy and proving it ran
An AI policy can say the agent must protect confidential information or obtain authorization before acting. The policy is necessary. It is not evidence that it operated.
An organization preparing an AIMS may also need to show which policy version governed a specific interaction, what was evaluated, what decision was reached, whether an action was authorized before it executed, and whether a human review occurred.
That is the difference between documentary evidence and operational evidence. Documentary evidence is policies, procedures, training records, and meeting minutes. Operational evidence shows the controls working on actual turns and tool calls. SAFi exists to provide that second layer.
Where SAFi sits
SAFi runs at the moment an agent produces an answer or prepares to take an action. The governing process separates five faculties:
- Values define what matters.
- Intellect drafts the response or proposed action.
- Will authorizes or declines action.
- Conscience evaluates the draft against the governing values and policies.
- Spirit measures consistency and longer-term alignment.
This separation keeps generation apart from authorization, authorization apart from evaluation, and runtime decisions apart from later review. The underlying model that fills the Intellect is configuration; the charter, policies, and audit trail stay independent of the model provider.
Every governed turn produces an evidence record: the draft, the policy version in force, the value-by-value evaluation ledger, the enforcement decision, the authorization record for any tool call, and the alignment measurements used for monitoring.
The audit runs before the answer is delivered, and a tool call is checked against the allow-list before it executes. An after-the-fact log can only show what happened. A runtime record also shows what was evaluated and authorized before it happened.
SAFi does not make an agent correct, unbiased, or free of hallucinations. It governs and records the decision process. Grounding quality, model behavior, and human review remain their own controls.
A practical mapping
This table is a starting point for evaluation, not a conformity assessment.
| AIMS need | Potential SAFi contribution | Organization responsibility |
|---|---|---|
| AI policies that operate in practice | Versioned charters, policies, and value rubrics evaluated during governed turns | Authoring, approving, and reviewing policies |
| Accountability and role separation | Role-based permissions and recorded supervisory dispositions | Assigning roles and maintaining accountability |
| Runtime operation records | Audit records with the draft, evaluation, decision, and policy version | Retention, review, and evidence-management procedures |
| Human oversight | Supervisory review routing based on configured conditions | Staffing reviewers and acting on dispositions |
| Governed tool use | Tool allow-lists and pre-execution authorization records | Approving tools, scopes, vendors, and credentials |
| Third-party model governance | Organization-level provider controls | Vendor due diligence and contracts |
| Performance evaluation | Alignment, consistency, drift, and violation measurements | Defining objectives, thresholds, and review cadence |
| Data governance support | Encryption, retention, export, and erasure mechanisms, where configured | Legal interpretation and records management |
| Evidence integrity | Integrity-protected governance records, where configured | Deployment verification and evidence preservation |
| Continual improvement input | Trends, review outcomes, and violation patterns | Management review and corrective action |
The phrase “potential contribution” is deliberate. Whether a SAFi control supports a given AIMS requirement depends on the organization’s scope, configuration, and procedures.
What stays yours
SAFi is an operational governance engine, not an entire management system. The organization keeps full responsibility for its AIMS scope and leadership, risk assessment and treatment, AI impact assessments, policy ownership, training and competence, internal audit and management review, nonconformity handling, and certification itself. Software can feed these processes with records and metrics. It cannot perform them.
One point bears repeating: only an organization’s AIMS can be certified. SAFi cannot be described as ISO/IEC 42001 certified, and no one becomes certified by deploying it.
How to evaluate SAFi
Skip the feature descriptions and inspect the evidence path directly:
- Can you identify the policy version that governed a historical turn?
- Can you see the draft and the value-by-value evaluation behind a delivered answer?
- Can you tell an approved answer from a redirected or blocked one?
- Can you show that a tool call was authorized before it ran, and by which rule?
- Can you see whether a turn went to supervisory review, and the reviewer’s written reason?
- Can you measure alignment and drift over time, and verify the integrity of the deployment and its records?
- Can you say which responsibilities remain outside the engine?
Clone the repository, run the demo, inspect a governed audit trail, and open an issue if a control mapping or evidence artifact needs clarification. Do not ask whether SAFi makes you certified. Ask whether it gives your own management system an inspectable runtime control point.
The control-by-control detail behind this article lives in the ISO/IEC 42001 readiness document, part of SAFi’s regulatory readiness series alongside the EU AI Act, SEC/FINRA, and HIPAA documents.
Conclusion
ISO/IEC 42001 puts AI governance responsibility on the organization and its management system. That system needs more than policies stored in documents. It needs evidence that governance operated in practice.
SAFi is built for that operational point. It applies your values and policies during governed turns, checks tool calls before execution, records the decision and its policy context, and measures consistency over time.
SAFi is an open-source runtime governance engine for agentic AI that helps organizations turn declared values and policies into inspectable, auditable runtime decisions.
Readiness is not certification. Evaluate the evidence path.
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