Know every material AI system
Maintain ownership, purpose, risk, model or vendor, validation, and approval context rather than relying on an informal list of pilots.
Reserve Bank of India
Turn RBI FREE-AI principles into operating evidence.
Connect AI inventory, validation, incident handling, emergency intervention, and board oversight to the requests and actions your systems execute.
Read FREE-AI with the right legal status
The Framework for Responsible and Ethical Enablement of Artificial Intelligence was published by an RBI committee in August 2025. Its 7 Sutras, 6 Pillars, and 26 recommendations signal a detailed supervisory direction, but the report does not itself amend an RBI Master Direction or create a new binding circular.
Intervene before impact
Apply policy, PII handling, human review, and emergency-stop controls before a model or agent produces a material banking outcome.
Report from evidence
Connect board and risk reporting to traceable system, validation, incident, policy, and intervention records.
AxonFlow control mapping
| Operating need | AxonFlow surface | Edition boundary |
|---|---|---|
| Govern requests consistently | System and tenant policy enforcement, request audit, and India-relevant PII controls. | Community foundation; higher policy and operational limits in licensed editions. |
| Maintain AI-system records | RBI-oriented AI system registry workflow for purpose, owner, risk, and approval context. | Enterprise workflow. |
| Record validation and findings | Validation records and lifecycle state linked to the governed system. | Enterprise workflow; AxonFlow does not run model validation for you. |
| Manage incidents | Incident records connected to systems, evidence, remediation, and status. | Enterprise workflow. |
| Stop unsafe operation | Scoped and broader circuit-breaker patterns with actor, reason, and reset history. | Licensed operational controls. |
| Prepare oversight evidence | Board-report and audit-export workflow APIs based on captured records. | Enterprise workflow; governance owners approve the final report. |
A bank-grade pilot should answer five questions
What system is this?
Can risk and audit identify the owner, approved purpose, model, data domain, deployment, and downstream actions?
What can it do?
Are tool and connector permissions enforced independently of model instructions and prompt content?
Who can intervene?
Do material actions pause for an authorized reviewer, and can the team halt the system without a code deployment?
Can events be reconstructed?
Can an investigator join the policy decision, approval, model call, tool action, and downstream transaction?
Does reporting reflect reality?
Can a board or control function trace summary claims back to system, validation, incident, and runtime evidence?
What remains outside AxonFlow?
Model validation, fairness analysis, legal interpretation, business ownership, and final board accountability remain yours.
What not to claim
Accurate positioning
- RBI FREE-AI-aligned runtime and evidence workflows
- Technical foundations for policy, PII, approvals, and audit
- Enterprise workflows for registry, validation, incidents, intervention, and reporting
Claims the product cannot establish
- That RBI has certified or approved AxonFlow
- That using AxonFlow makes an institution compliant
- That the FREE-AI report is already a binding Master Direction
- That runtime records replace independent validation or board oversight
Test the control path against a real workflow.
Use the Evaluation license to assess policy enforcement, human review, evidence records, and deployment boundaries before a regulated rollout.