Data science
The numbers are clear, but who signs off, and where that decision is kept, is not.
AI council
It reads well, but nothing shows which systems it covers or who does the reviewing.
Agent platform
It’s one settings change, and the human check your policy promises is gone.
How it works todayWhat it needs to be
- How it works today
Principles agreed, then filed as a policy
What it needs to bePrinciples worked into how each system is reviewed
- How it works today
One ethics review, whatever the use
What it needs to beScrutiny that rises with the stakes for the people affected
- How it works today
Model cards that describe the first version
What it needs to beDocumentation that changes when the model does
- How it works today
Oversight designed for AI that only advises
What it needs to beHuman checks that still hold once agents can act
Won’t more process just push teams around it?
Not if the depth fits the stakes. Your reviewers classify each system, and a low-stakes tool gets fewer controls than one that decides about people. Builders answer what applies to them, and the deep review sits where your principles say it should.
We already test models in our own tools. Is this duplicate work?
No. Keep testing where your data scientists work. Enzai holds what follows: attach the bias test report, a completed form or metrics recorded on the system or its models as evidence for the control it supports, and a reviewer approves it. Your tools produce the results, and Enzai keeps the proof and who accepted it.
Does automation ever take a person out of the loop?
Only where your own rules say a review doesn’t apply. Each sign-off waits for a named reviewer, and the record shows who decided and when. For agents connected to Enzai, an action left out of an agent’s approved tools is blocked before it runs. The agent can ask for access with a reason, and a person decides.
Will our sensitive test data end up in Enzai?
No. Attach what proves the control, such as a test report or the metrics you choose to record, and the raw data stays where it is. Enzai keeps the record of what was tested, what it showed and who approved it, not the data the test ran on.
Our principles are agreed. What do we do first?
Write them up as a framework of your own, with its own controls and classifications, and run it on the few systems with the most at stake. Attach the evidence you already hold, give each control an owner and widen it system by system. When your principles change, you choose when each system moves to the new version.
When someone asks how we know, can we show them?
Each control carries its evidence and the reviewer who approved it. Each risk carries two ratings from your reviewers, before and after treatment, and the mitigations that explain the gap. Internal and external reports come straight from that record. Whether it meets a regulator’s bar is theirs to judge, but nobody has to rebuild the story.
Where to start
