Agent governance

Build agents anywhere. Keep every action under control.

Your organisation will use agents from many providers, suppliers and partners. Without one control point, they can all reach customers, payments, records and APIs in different ways. DataInbox checks who may act, on whose behalf, under which rule and with which approval before work reaches a business system.

Any agent or model
One policy-aware checkpoint
Approval before risky actions
Evidence for GRC and audit

Supplier, company, customer, auditor, cloud and local agents connect directly to CRM, ERP, payments, databases, healthcare and APIs without one control point; Scrut, Drata and Vanta receive evidence below

The gap between GRC and execution

Your controls may be documented. Agent actions happen live.

Platforms such as Scrut, Drata and Vanta help manage controls, compliance and evidence. But an agent still needs a live decision before it reads data, changes a record or starts a payment. DataInbox turns the relevant requirement into an execution rule and returns evidence of what happened.

ScrutDrataVanta

DataInbox checks before execution

Identity, customer context, current business state, policy, authority and approval produce one clear result: allow, warn, approve or block.

AllowWarnApproveBlock

All supplier, company, customer, auditor, cloud and local agents pass through the DataInbox Governance Runtime, which checks identity, context, policy, authority, approval and evidence before allowing, warning, requesting approval or blocking access to business systems

The governed solution

One checkpoint before every agent action.

Agents can still be built with OpenAI, Claude, local models or specialist tools. Instead of connecting each one directly to production, they submit a proposed action to DataInbox.

DataInbox checks the current business context, policy and authority. It can allow, warn, request approval or block. After execution, the decision and outcome return as structured evidence for your organisation and its GRC platform.

Build agents anywhere. Operate them as one accountable organisation.

Provider development · 29 September 2026

Website access is not business approval.

OpenAI reports that its public-beta Agents API can now use an OpenAI-hosted browser; the application handles website-access approvals and sign-in. This confirms a browser capability and its access boundary. It does not authorize a refund, change a customer record, or establish a DataInbox integration.

For a service owner, an order exception illustrates the proposed DataInbox boundary. Before: an agent signs in, finds the order and clicks a refund control, with the approval and evidence assembled later. After: the agent proposes the refund; DataInbox would check current order state, amount, customer identity and the owner's approval rule before any permitted action, then record the result. That governed sequence is a design to pilot, not a newly released product flow.

A pilot could test fewer manual handoffs, less rework after an incorrect action, and faster evidence retrieval. Measure completed cases, approval waiting time, corrections, failed browser steps and total tool plus model cost. It needs a scoped identity, stable website access, an authoritative order source, an accountable approver and a safe recovery path.

Five controls

Govern the path from authority to evidence.

Authority

Define which agent, person, or service may request an operation and for which purpose.

Minimum context

Expose only the message fields, references, and history required for the current task.

Permitted action

Validate the proposed operation against schemas, policy, limits, and current business state.

Approval

Require an expert or accountable owner where judgment, risk, or policy demands it.

Evidence

Record the request, context, decision path, action, outcome, and override as structured messages.

One subject, four pages

Use the page that answers the question you have.

Governance should not become one giant collection of generic controls. Each product surface has a specific job.

Start with one decision

Define what an agent may do before connecting the tool.

Bring one proposed action, the required context, and the accountable owner. We map the authority, exception path, and evidence around it.