AI agents are moving from answering questions to taking actions — sending, committing, deciding. Claire makes those agents provably trustworthy: governed at every gate, sealed in a tamper-evident record, and open to inspection. We hold ourselves to it first.
How GATE℠ works See the record — we operate in glassAn agent that drafts a reply is a convenience. An agent that sends it — that moves money, changes a record, or commits your company — is a liability, unless someone can prove what it did, why, and that a qualified human stood behind it. That proof is Agentic Trust. It is the bottleneck on every serious deployment, and it is the whole of what Claire builds.
GATE is the operating system of trust beneath a deployment. Agents produce; a gate holds the action; a qualified human — never the one who submitted it — approves; the decision is sealed in a tamper-evident ledger. Autonomy is earned, gate by gate, never assumed. It works across agent frameworks and model providers.
An agent drafts an action — a message, a term, a record change. Nothing leaves the gate.
The action is held, scoped, and checked against the limits you set.
A qualified human — not the submitter — signs off, edits, or hands it back.
The decision is written to a hash-chained record: who, what, when, and why.
Autonomy is proposed only when the evidence clears the bar — and can be revoked.
GATE earns its keep wherever an agent's action carries real consequence and someone will later be asked to prove it was sound. Nowhere is that sharper than regulated financial services — lending, fintech, banking, insurance. It's the domain of our reference install, and it's where we start. You'll get the most from GATE if:
Approvals, borrower and customer communications, pricing and terms, servicing, collections — an agent that does something, not one that writes internal copy a human was going to rewrite anyway.
Funds move, a commitment is made, a limit is waived — and a regulator, auditor, or partner can later ask "who approved this, and why?" You need the answer already on the record.
You operate where accountability is existential and evidence beats assurances. GATE's record maps to the logging and human-oversight standards your examiners already use.
You're scaling an AI workforce, and the trust layer is what stands between a promising demo and something you can actually let touch a customer or a ledger.
If your agents only draft low-stakes internal text, and nothing they do moves money, commits the company, or has to be defended later, GATE still works — but it's built to earn its keep where the stakes are higher. We'd rather tell you than oversell.
The proof an underwriter or examiner accepts in finance is what every high-consequence domain will need next — healthcare, legal, insurance operations. Finance is simply where the need is sharpest today. So it's where we begin.
We don't ask you to take governance on faith. Claire runs its own AI workforce under GATE, in glass — and so does LoanCirrus, a regulated fintech we also own, held to the same governance as any tenant. Two live installs you can inspect, not a demo.
Claire's own sales and marketing agents operate entirely under GATE. Every draft, approval, correction, and revert is recorded. If our own governance failed, you would be able to see it — which is exactly the point.
LoanCirrus, a lending-technology company operating across 25+ countries under common ownership, runs its AI agent workforce under GATE — held to the same standard as any other tenant, in a domain where audit and accountability are existential.
LoanCirrus and Claire share common ownership through their founder. LoanCirrus is a governed GATE tenant — not part of Claire — and receives no preferential treatment. We name the relationship in plain sight because a trust company that hides one isn't one.
GATE's record maps to the logging and human-oversight requirements that regulators and procurement teams are already converging on — applied to high-risk-grade rigor by choice, ahead of requirement. We borrow recognition rather than inventing our own.
GATE's hash-chained record maps to Article 12 (automatic logging) and Article 14 (human oversight) for high-risk AI.
The world's first AI management-system standard — increasingly a procurement precondition. GATE supplies the evidence layer.
GATE operationalizes the framework's accountability lineage: every action traceable to a responsible human.
"The name carries ai at its centre — embedded inside something human, discovered on second glance. And clair means clear. A trust company has exactly one product: clarity about what a machine did, and who stood behind it."
We make AI agents provably trustworthy enough to act. Our first product, GATE℠, governs every agent action, records it in a tamper-evident ledger, and lets autonomy be earned rather than assumed. Trust is the product; software is how we deliver it.
The Governed Agent Trust Engine. Agents draft an action; a gate holds it; a qualified human — never the one who submitted it — approves; and the decision is sealed in a hash-chained record of who did what, when, and why. It runs across agent frameworks and model providers. See how GATE works →
Regulated financial services, first — lenders, fintechs, banks, and insurers deploying AI agents that take consequential actions: approvals, borrower and customer communications, pricing and terms, servicing, collections. GATE earns its keep where a wrong action moves money or triggers compliance exposure and someone will later be asked to prove it was sound. If your agents only draft low-stakes internal text, it's a smaller fit — and we'll say so. See who it's for →
No. GATE's governance is model- and framework-agnostic. It governs agents built anywhere, on any model, and the trust layer survives even if every model underneath is swapped. That independence is deliberate: a trust layer tied to one vendor isn't a trust layer.
We operate the governance we sell, transparently. Claire's own agents and LoanCirrus — a regulated fintech under common ownership — both run under GATE, and we show how. A trust company should be the first thing it inspects. See the proof →
We map GATE to the Act's logging (Article 12) and human-oversight (Article 14) requirements and apply high-risk-grade controls by choice, ahead of requirement. We don't make a blanket compliance claim — obligations depend on your specific use case, and we'll tell you plainly where a control helps and where you need your own counsel. See the mapping →
Whether you're a lender, fintech, bank, or insurer installing an AI workforce or governing one you already run, it begins with a conversation about what your agents do and what proof you need. Founding engagements are open.
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