ClarityGRC for AI Agents
Hold your AI agents to the same rules as your people.
As your company builds with AI agents and automations, they begin taking real actions on your behalf: sending mail, filing records, touching customer data. Give them one check to call before they act, answered from your own policies, obligations, and approval gates, with every request and verdict on the record.
An add-on to ClarityGRC. The same policies, obligations, and gates your team already maintains, now enforced at machine speed.
Why now
The next thing your examiner asks about is already running.
Agents do not wait for a meeting. They send, file, and decide in milliseconds, at a scale no reviewer can watch after the fact. Governance for AI agents has to happen at the moment of action, grounded in the program you already run, or it does not happen at all.
The check
A check your agents call before they act.
Before an agent takes a consequential action, it asks ClarityGRC a plain question: may I do this? The answer is grounded in your live program, your approved policies, open obligations, applicable regulations, and the gate status of any system the agent names.
- Proceed, proceed with conditions, or stop, each with the policies and obligations behind it
- An action that names an AI system you have not approved is stopped, every time
- Guidance only: an agent never approves itself, and nothing lands approved without a person
Connect it
REST and MCP, scoped to one company.
Agents and pipelines connect with a company-scoped key. A REST API and a Model Context Protocol server expose the same governed actions, so an agent can check an action, read its obligations and approved policies, file evidence, submit an AI intake, or report an incident, all bounded to its own company.
- Company-scoped keys, so an agent can never reach another company record
- An MCP server, so AI assistants get the same governed tools natively
- File and request only: the interface submits work for human review, never approval
The record
Every agent action, on the record.
Each request an agent makes and each answer it receives is written to an append-only activity log: what it asked, what it was told, and the verdict. A metrics view shows volume, verdict mix, and where agents keep hitting policy limits, so machine activity is as auditable as human activity.
- Append-only record of every ask and answer, readable by the company, editable by no one
- Verdict mix and daily volume, so you can see where agents bump into the rules
- The answer ready when an examiner or customer asks how your AI is governed
How it works
Three steps, one endpoint.
- 1
The agent asks
Before a consequential action, the agent calls one endpoint with what it intends to do.
- 2
ClarityGRC answers
A verdict grounded in your live program comes back in plain terms, with the policies and obligations behind it.
- 3
It goes on the record
The ask, the answer, and the verdict are written to an append-only log you can hand to an examiner.
An add-on to ClarityGRC
Because agent traffic runs on its own compute, governance for AI agents is a separate subscription on top of your ClarityGRC program. There is nothing new to define: the policies, obligations, and gates you already maintain are exactly what the agents are checked against.
Govern the agents before they act, not after.
Bring the automation you are most nervous about to the demo, and we will run a real action through the check live.
Self-serve signup with published pricing is coming. Early access runs through demos.