Deterministic control over consequential AI agent actions.
Before AI agents modify protected code, access sensitive resources, deploy infrastructure, or perform production actions, Arbiter evaluates policy and returns a signed ALLOW, DENY, or ESCALATE decision.
Request a pilotThe Problem
AI agents are being deployed into environments containing:
- customer data
- payment systems
- regulated data
- production infrastructure
Many governance tools explain what happened after the fact.
Regulated organizations need deterministic control before consequential actions occur.
How It Works
- Agent requests action.
- Arbiter evaluates policy.
- Arbiter returns ALLOW, DENY, or ESCALATE.
- Signed authorization receipt produced.
Policy evaluation is deterministic- there are no LLMs in the enforcement path.
Each decision creates a verifiable record of the policy, evidence, actor, and action evaluated.
Arbiter Control
Authorization engine and signed decision receipts.
Arbiter Runtime
Deterministic runtime for controlled agent execution.
What Arbiter Controls
Start with the points where agent actions cross consequential boundaries.
- PR promotion authorization
- Secret access authorization
- Deployment authorization
- Infrastructure change authorization
- Production action authorization