Stop sensitive data from leaving in an AI prompt.
The paste is faster than the policy. Records, case files, and client data go into prompts on the strength of a deadline, and agents now send requests no human reviews at all.
Decided while it's still on your machine.
Enforcement here means the request is handled before it leaves. Your policy reads what's about to go, hides the values you've flagged, and refuses outright what you've banned. That's AI policy enforcement in the literal sense, running where the data is rather than reporting on where it went. By the time anything reaches a governed provider, it's already the version you allowed.
What AI policy enforcement catches
It's the difference between reading about the leak tomorrow and preventing it today. Here's what your rules do the instant a request is made.
List what your regulator cares about: social security numbers, card numbers, record identifiers. They're replaced in the request before it goes.
Some things shouldn't leave at all. A banned request ends at the device, and the provider never sees it.
A recruiter's chat tool and an engineer's coding agent can run under different rules, each strict exactly where its risk lives.
A request an agent fires on its own meets the same screen a person's paste does, so autonomy never becomes an exemption.
Catching leaks is common. Preventing them isn't.
The standard playbook inspects traffic for shapes it recognizes and tells you when something got out. That leaves you running a race you can only lose slowly. Verillian puts the decision ahead of the exit, on the endpoint, while the data is still yours alone.
In a regulated environment that's the whole case: an identifier that never reaches a provider is one you never have to explain.
The paste will happen.
The leak doesn't have to.
Bring the paste that scares you most and watch the rules decide, live, on a machine you own.