Methodology
A disciplined method, not a black box.
We assess one workflow, design where people stay in control, build with review built in, and then operate. You see how the work happens at every step.
Assess
We map one workflow, its data, and its risk and approval points in a fixed-scope audit.
Design
We design where AI assists, where a person approves, and what evidence they see before approving.
Build
We build the workflow with human approval gates and a reviewable action trail, in a defined window.
Operate
We monitor, review exceptions, and improve the workflow over time.
Where humans stay in control
Approval before important actions.
We identify the moments where an action carries real consequences, and we put a person in the loop there. AI prepares and proposes. A person approves before the action happens, with the source evidence in view.
What gets recorded
A reviewable action trail.
Important actions are recorded so your team can trace what happened later: what was prepared, what was approved, and by whom. This supports review by your own team and, where appropriate, by the people you answer to. It records what happened in the workflow. It does not claim to prove that any decision was correct.
What this is not
Honest boundaries.
This is not a guarantee of accuracy, compliance, fairness, or safety, and it does not remove the need for your team’s judgment. It is a way to make AI-assisted work faster while keeping it reviewable and under human control.
Start with one workflow
Start with an assessment.
See the method applied to one of your workflows, with a fixed-scope audit.
Start with an AI Workflow Audit