AI control towers
Approved once. Accountable the whole time it runs.
AI control towers give governance and risk teams a single place to intake, assess, and approve new AI initiatives — real oversight, at the moment a project starts. FaburAI covers what happens next: a continuously updated record of what each approved AI actor actually reached, so oversight does not end when the ticket closes.
A governance program needs all three answered.
Approval, enforcement and evidence sound like the same thing from a distance. They are answered by different mechanisms, at different points in an initiative's life, and a program that only has the first one is exposed for as long as the initiative runs.
Approval answers: should this exist
A control tower's job is done once the initiative is reviewed and the ticket closes.
Enforcement answers: is it still behaving
Every call an approved AI actor makes is checked against policy, for as long as it runs — not once, at the start.
Evidence answers: can you prove it
A decision record exists because enforcement happened, not because a report was scheduled — the artifact a regulator or auditor actually asks for.
Six questions, asked the same way every time.
Every cell below states what that category actually does for that row — not a checkmark, not an X, and not left out to make the comparison look one-sided.
| Criterion | AI control tower | FaburAI |
|---|---|---|
| Discovery model | Governs what is registered in it. An agent or server nobody added to the tower is invisible to it. | Governs what is registered and what is observed calling in. An AI actor nobody registered still appears the moment it makes a call. |
| What it governs | A request for a new AI initiative, agent, or use case — the paperwork around it. | Every call an AI actor makes to a tool, resource, or data system, down to the column. |
| When it acts | At intake, once per initiative — before or alongside approval. | Continuously, at the moment of every governed call, for as long as the AI actor runs. |
| What it produces | A ticket, a risk rating, and an approval status in a system of record. | A decision record: the AI actor, the user role behind it, what it reached, the outcome, and the rule that decided. |
| Data residency | Governance data lives in the tower vendor's own cloud platform. | Governance data stays inside the customer's own environment and never leaves it. |
| Where enforcement happens | Nowhere — a control tower has no enforcement point of its own. It governs the request, not the runtime call. | Inside the customer's environment, at the moment of the call, evaluated locally against policy already retrieved. |
One gate, crossed once. One decision, made every time.
Laid out side by side, the gap is exposure time. A gate crossed once leaves everything after it ungoverned until someone happens to look again — a continuous decision does not.
Someone requests a new AI use case, agent, or integration.
A questionnaire, a risk rating, a human reviewer.
Status changes in the system of record. The tower's job is done.
The approved agent reaches for a tool, a resource, or a column.
Against policy already in place, inside the customer's environment. Allow or deny.
Not once — again on the next call, and the one after that.
The initiative is approved once. The calls it makes are not — each one is decided on its own, which is what lets FaburAI catch a call the original intake never anticipated.
FaburAI can connect to your AI control tower.
It becomes one more observed source in the same estate graph as every other AI surface FaburAI governs — no rip-and-replace, and nothing about the tower itself has to change.