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.
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.
Frequently asked questions about Agent Governance & Oversight
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.
Process Redesign for Agents
The process taken apart before an agent runs it: what falls away, what the agent does and what stays a human decision.
Custom Agent Development
Agents that take on tasks instead of merely answering: qualifying leads, preparing quotes, resolving tickets.
Industry Agent Library
Proven agents for construction, building materials and mechanical engineering, configured to your systems instead of built from scratch.
