AI governance platform for regulated institutions
Runtime AI governance is the control layer that lets an institution use AI inside the obligations it already answers to, with evidence the controls held. Verillian is that layer: runtime AI governance, enforced at the device the moment a tool or agent acts, with every captured interaction sealed into the chain. Regulated teams use the models changing their field without giving up control, or the evidence that the controls held.
Where the control sits
Every request takes the same path. The decision happens on the device, before anything crosses the boundary.
data flow: device to boundary to record
What happens to every request?
Once a tool or agent is under policy, every request it makes resolves to one of three decisions: ALLOW, REDACT, or BLOCK. Each decision is signed into the chain as it is made, so enforcement and evidence arrive together.
Cleared by your policy and forwarded to the provider. Signed into the chain.
Sensitive data detected in the request is masked or removed before the prompt is forwarded.
Denied by your policy. Never forwarded, and the attempt is sealed in the chain.
Around the decision sit the controls that make it yours: tool-call analytics to build policy from real usage, and an org-wide stop that halts all AI traffic across the fleet at once.
What can you show your board?
The numbers leadership asks for: risk prevented and fleet coverage, with the per-user evidence underneath and proof the controls were on the whole time.
board dashboard, representative view
What runtime AI governance looks like
Operate AI inside the controls your regulator already expects, with the evidence to show you did.
- Frontier access, governed
- Give staff and agents the frontier models your field is adopting, with policy enforced as they act and evidence around every captured interaction.
- Board-ready numbers
- Risk prevented, fleet coverage, and AI usage evidence in the terms leadership reports upward, with the per-user record underneath when there is cause to look.
- Proof the controls held
- Evidence that policy was enforced the whole time, not a snapshot assembled after an incident.
- Accountable change
- Policy changes require justification and multiple approvers, with a full, cryptographically backed history.
- Obligations mapped to controls
- Your AI acceptable use policy and each control your regulator names become policies the sentinel enforces and entries in the record that show they held. Built to CJIS Security Policy v6.0, HIPAA, and NIST 800-53. Aligned, not certified.
- Built for where federal AI policy is heading
- The June 2, 2026 Executive Order, Promoting Advanced Artificial Intelligence Innovation and Security, points toward expectations around covered models and benchmarking, with detail expected later in 2026. Verillian is designed to support that direction: control the action, hold the evidence. See the compliance mappings for detail.
Use frontier AI. Keep the boundary.
Adoption with the controls on from day one, and the evidence to show your board they stayed on. We work with our first institutions on their own endpoints, against their own policies. Thirty minutes shows more than a slide deck ever will.