A guardian for agentic AI

The trust gate for AI agents.

No agent acts alone.

Your agents have started to act — deploying code, moving data, making commitments. Trust Gate stands in front of the consequential ones: no agent takes an irreversible action until independent minds agree — and you see exactly where they didn’t.

Mind Aapproves
Mind Bapproves
Mind Capproves
cohered
Action clears.The agent proceeds — with a logged, auditable record of the vote.

When the minds cohere, the gate clears. When they genuinely disagree, it holds — and escalates to a human.

Your agents can act. You can’t trust them to act alone.

The reflex when an agent misbehaves is to cage it — narrow the scope, put a human in the loop. Today the vast majority of production agents hand every output to a person, and only a small fraction of teams fully trust one to act autonomously. That’s the right instinct — and it doesn’t scale. You cannot put a human in the loop on a million agent actions. The cage is a tax on the very autonomy that makes an agent worth deploying.

Verify, so you can safely widen the cage.

Trust Gate is not the removal of oversight. It’s the auditable proof that lets you grant an agent more autonomy over time — one earned step at a time. Earned autonomy, not blind autonomy. Every action carries a record of who agreed, who didn’t, and how sure the room was.

Quorum

Not a single judge

A panel of independent minds reviews the pending action — not one model grading itself. One judge can be wrong the same way the agent is.

Coherence

Agreement, measured

Sheaf computes whether they actually agree, with its coherence layer — real mathematics, not a vibe score. Cohere and it clears; diverge and it holds.

Glass box

The seams shown

Every decision returns where the minds split and how severely — so a human reviews the few contested actions, not all of them.

Why a quorum beats a single AI judge.

One mind can hide its own blind spot. A room can’t.

The industry is converging on a single “LLM-as-judge” to check agent actions — one more fallible mind, prone to the same errors as the first. Sheaf runs a quorum of independent minds and measures their disagreement — the H¹ coherence layer, with a published paper and a patent behind it. “The models agreed” is a claim anyone can make. “Here is the measured disagreement, and the gate held because of it” is proof. See the math →

Anyone can add a second opinion. Sheaf tells you whether the room actually agreed — and stops the action when it didn’t.

Built on an engine that already runs.

Trust Gate isn’t a new stack — it’s Sheaf Pod, pointed at the moment before an agent acts. The same panels, the same coherence audit, the same sync / stream / async API you can call today. Drop it in front of the actions that would hurt to get wrong.

The category, for the record. Gartner calls this a guardian agent — and specifically a “protector,” an AI with the authority to block another AI’s action — and projects it at 10–15% of the agentic-AI market by 2030. Sheaf brings the piece the category is missing: a quorum with its disagreement measured, instead of one model’s say-so.

No agent acts alone.

Verify before it acts. Widen the cage when it earns it. See exactly where the minds split.