Runtime Governance and Execution Control Plane for AI Systems
RIO governs any consequential action taken by AI agents, automated workflows, or software systems on behalf of humans. Each use case follows the same governed execution pipeline.
An AI agent integrated with the accounts payable system identifies an invoice due for payment and submits a transfer_funds request to RIO for a $48,250 wire transfer to a vendor.
Without RIO, the AI agent would have initiated a $48,250 wire transfer with no human review, no audit trail, and no proof of authorization.
A data management system receives a GDPR right to erasure request. An automated workflow submits a delete_data request to permanently remove a customer's personal data from the production database.
The receipt provides legally defensible proof that the deletion was authorized by a qualified individual, followed a governed process, and was recorded in a tamper-evident ledger.
A CI/CD pipeline completes a build and submits a deploy_code request to push a new release to the production environment. The deployment affects customer-facing services.
If the deployment causes an incident, the receipt and ledger provide a complete chain of accountability: what was deployed, who authorized it, what risk score it carried, and when it happened.
An onboarding automation system submits a grant_access request to provision a new employee with access to internal systems, including source code repositories and production monitoring.
Every access grant is traceable. During security audits, the organization can prove exactly who authorized each access grant, when, and under what policy.
An orchestrator AI agent delegates a task to a specialist agent. The specialist agent needs to send an email to a customer. Instead of acting directly, it submits the request through RIO.
In multi-agent systems, RIO ensures that no agent — regardless of how many layers of delegation exist — can take a consequential action without human authorization and a complete audit trail.
See RIO enforce these governance patterns in real time.
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