Runtime Authority
The infrastructure layer that determines whether an autonomous AI agent is authorized to perform a real-world action, evaluated before that action executes.
AI agents are moving from generating information to taking actions
An agent that drafts an email carries limited downside if it's wrong. An agent that initiates a payment, submits a procurement order, modifies a contract, updates an ERP record, changes infrastructure configuration, or makes a healthcare-adjacent recommendation carries the same consequences a human employee acting outside their authority would carry -- except it can act at machine speed, at machine scale, and without the institutional friction that normally slows a person down long enough for someone to notice.
Enterprises already have governance structures built for exactly this problem: Delegation of Authority, approval limits, separation of duties, role hierarchies, accountability models. None of them were written with a machine actor in mind, and none of them are currently enforced at the moment an AI agent decides to act.
A policy that isn't evaluated at the moment of action isn't enforced
Logging, monitoring, and after-the-fact review tell you what an agent did. They do not stop it from doing the wrong thing first. Runtime authorization moves the check to before execution: the agent's intent is evaluated against the organization's actual authority structure, and the action only proceeds if that structure permits it. This is the same principle every mature access-control system already applies to people and services -- extended to autonomous agents, at the speed they operate.
Every intent passes through the same deterministic path
An agent submits a cryptographically signed intent. Runtime Authority evaluates it against the Authority Graph -- who this agent is acting on behalf of, and what that principal is entitled to delegate -- and the active Runtime Policies compiled from your governance documents. Evaluation is sub-millisecond and deterministic: no model makes a judgment call at this stage. For the exact request and response shape, see Runtime API in the Developers section.
Three outcomes. No fourth path.
Allow
The intent falls within delegated authority, approval limits, and active policy. Execution proceeds without a human in the loop.
Deny
The intent falls outside authority or violates a constraint. Execution is blocked before it happens, not flagged after.
Human Review
The intent is inside a defined escalation boundary. A named accountable reviewer resolves it; the resolution is itself recorded.
What changes for the organization operating it
Deterministic, fail-closed
The same intent, evaluated against the same policy, produces the same decision. When evaluation cannot complete, the default is deny, not allow.
Your governance, not a new one
Delegation of Authority, approval matrices, and role hierarchies you already operate become the evaluated policy. Nothing is invented on your behalf.
Before execution, not after
Evaluation happens at the moment the agent forms an intent, ahead of any real-world effect -- not as a downstream audit of what already happened.
Every decision is evidence
Allow, Deny, and Human Review all produce a signed record. There is no path from agent intent to action that bypasses evaluation or leaves nothing behind.
See Runtime Authority evaluate a real intent
Bring an existing approval policy. We'll show you the decision, in real time, before anything executes.