AI Governance & Compliance

Approvals, logging and traceability for everything agents do, built in from the start rather than retrofitted once the first incident happens or the EU AI Act asks.

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Hands typing on a keyboard at a grey desk, a blank white badge on a lanyard and an orange notebook lying in front of the monitor. A woman in a blazer taps a tablet on a high table in a glass meeting room while a man with folded arms watches, an orange stool beside the table. Hands lift the top sheet from a stack of paper in the output tray of an office printer, an orange folder resting on the machine.
What we look at

From open questions to evidence you can export.

Agents get identities

Their own accounts with limited rights instead of shared API keys. What an agent reads, writes and decides is attributable to it, which is the basis of any control.

Approvals follow the risk

Routine steps run autonomously, while sensitive operations such as discounts, deletions or external communication need a human approval. You set the thresholds, not the model.

And the evidence is created in operation

Logged decisions, documented changes, analysable incidents. When an audit, the works council or the EU AI Act asks, the answer is an export rather than a project.

What you receive

Four things that keep AI accountable.

Approval & permission model

Agents with their own identities and limited rights, with sensitive steps requiring human approval.

Logging & audit trails

Every action attributable and retrievable, for internal control as well as external review.

EU AI Act classification

Your use cases classified by risk, obligations derived and anchored in the platform.

Policies & enablement

Understandable rules for teams working with agents, trained rather than merely published.

FAQ

Frequently asked questions about AI Governance & Compliance

What does the EU AI Act require from us?

That depends on the risk class of your use cases, from transparency obligations to documented human oversight. We classify your use cases and anchor the obligations in the platform, as operating practice rather than a folder.

Does governance not slow the agents down?

Built properly it speeds them up: clear guardrails make approvals predictable and take the debate of principle out of every single use case. Without rules, every new agent becomes an individual case for compliance.

How does this relate to the Agentic Operating Model?

The Agentic Operating Model sets the rules, covering roles, responsibility and escalation. AI Governance & Compliance enforces them technically and keeps them in operation.

What exactly is logged?

Per agent: data read and changed, decisions taken with reasoning, approvals and escalations, plus every change to instructions and rights. Attributable, because agents have their own identities.

Who supplies the evidence in an audit?

The platform: logs, permission states and change history are retrievable. Continuous monitoring keeps the data current, so an audit becomes an export rather than a project.

Other Automate services

Three more services in Automate

If Automate is not the right starting point for you, explore the other phases of the Agentic Growth Stack as well.

AI Agents & Copilots

Agents that take on tasks instead of merely answering: qualifying leads, preparing quotes, resolving tickets.

Read more

AI Workflow Automation

End-to-end processes across system boundaries, with AI at the points where fixed rules are not enough.

Read more

Agent Monitoring & Optimization

What agents do is measured: quality, cost and escalations in view, with clear handovers to people.

Read more
first step

The first step towards an agent-native company.

In the Enterprise Discovery Workshop we develop a clear target picture and a business case that holds up, in a matter of days. Fixed price, no open-ended day rates.

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