PRODUCT · RUNTIME CONTROL

CONTROLS WHAT YOUR AI DOES.

Let your AI agents act on their own. Stop the one action that should never happen. Every action an agent proposes is checked against rules written in plain English before it runs, and returns ALLOW, HOLD, or BLOCK. The model still decides. The action does not run until it has been checked.

What it does

Rules in plain English, written by whoever owns the risk, with no code to change one. HOLD is an option you switch on for the actions that need a person, with the approver and the timeout declared in advance; everything else runs at full speed. Every decision is logged, who, what, when, why, on an append-only record. Model and runtime agnostic: the first published runs are on Hermes, the autonomous agent from Nous Research, and the same control reaches hosted assistants, open-weight models on your own hardware and custom agents.

Every AI system we can govern, and the ones we cannot yet

The scenario

This summer a vendor updated the hosted model behind our demo agent to chain tools more persistently, and the agent tried things nobody had seen, more than 140 attempts in a single run. Every new attempt was stopped the day it appeared, and nothing on our side changed. In the ungoverned lane of the same run, every one of them completed.

The July run, recorded, with the two actions we had no policy for

One policy, as you would write it

Take an agent a security team would build: an AI vendor risk analyst that runs a full vendor review end to end. It reads SOC 2 reports and questionnaires, extracts the controls, assigns risk ratings, opens remediation tickets and sends approval recommendations. Its policy, as written:

Policy

ALLOW: read SOC 2 reports, bridge letters and vendor questionnaires; create draft risk assessments.
HOLD for the named approver: approve a high-risk vendor; accept a compensating control; close a remediation finding.
BLOCK: modify a security policy; change a risk rating above threshold; delete audit evidence. No approval path. Log every attempt.

The agent reads and drafts freely. The moment it moves to approve a high-risk vendor, the action holds for a person. The moment it moves to delete evidence, the action never runs, and the attempt is on the record. That is the policy behind the Optimo AI run.

Why HOLD is the third outcome, and where it belongs

The ask

A 30-day paid proof of concept on your agents and your action set, in your environment, not ours. Then one flat annual price for the organization, with no per-agent count. Tests published, misses included, before anyone signs.

Book 30 minutes and bring the agent you cannot let run on its own yet

Every published test, on one page →

Proof

Four things with a published run behind them.

Tests published, misses included. The Recorded Run Protocol →

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