AI governance for regulated businesses
Before AI touches customer, patient or policyholder data, someone has to approve it and be able to defend that decision later. We help compliance, operations and legal leads set the rules, review the vendors and test the tools.
What it covers
Four parts of a defensible AI process
AI use policy
A written policy for how your team may use AI: which tools, for what work, with which data, and who signs off. Short enough that people actually read it.
Vendor review
A structured review of the AI tools you use or are considering, from any vendor, so you know what you're buying before you sign.
Evaluation and testing
Tests on your own documents and cases that show how accurate a model or tool is, where it fails, and how you'd find out when it's wrong.
Data handling review
Where your data goes, who can see it, how long it's kept, and whether a model provider can keep or train on it.
Vendor review
Four questions to ask any AI vendor
Every vendor review starts here. If a vendor can't answer all four clearly, that tells you most of what you need to know.
- 1
Where does the model run, and where does our data go?
If a vendor can't draw the path your data takes, assume it goes further than you'd like.
- 2
How do you evaluate it?
Ask for results on cases like yours, not a demo. "It's very accurate" is not an answer.
- 3
Can our team change what the model sees?
If only the vendor can adjust the inputs and rules, every fix waits on their schedule.
- 4
Can it show where every answer came from?
An answer you can't trace back to a source is one you can't defend to an auditor or a regulator.
For more on building AI for regulated industries, watch Josh Tang's talk at Columbus AI Week 2026.
Governance from people who build
Our view of safe AI comes from building it. The question we ask of every workflow is the one at the center of our AI maturity model: when the AI is wrong, how do you find out?
It's also why we don't build autonomous agents for regulated work. A system that acts on its own with no one checking is hard to govern, however good the model is. Read our position.
FAQ
AI governance: common questions
What is AI governance?
The rules and checks that decide which AI tools your company uses, for what work, with which data, and how you know they're working.
Do we need it if we only use ChatGPT or Copilot?
That's where much of the risk is: what people paste in. A use policy and a data handling review are the place to start.
Do you only review AI that Endstation builds?
No. We review the tools you already use or are considering, from any vendor.
Who does the work?
The same engineers who build Endstation's AI systems for insurance, healthcare and other regulated teams. We know where these systems break because we build them. Meet the team
Have an AI decision to make?
Bring the tool, the policy question or the vendor you're weighing to a free 30-minute call.
Book a Free 30-Min Consultation