The five questions every executive asks.
Plain answers, before the call.

How does this help my company?

The AI you’re deploying now answers your customers and takes actions — approving, paying, sending, changing records. The exposure isn’t that AI makes a mistake. It’s that nobody independent checked before the mistake went out under your name.

Veridect is that independent check, built in at the moment it matters. It verifies what your AI says — four frontier models from four vendors cross-examine the answer and return a confidence you can defend. It governs what your agents do — before an action executes it is cleared, held for a person, or blocked: out-of-scope actions are blocked, and the risky-but-authorized ones go to a human. And it proves both in a signed, tamper-evident record anyone can check.

What that buys you: AI allowed into the workflows that matter — money, customers, patients, regulators — because there is an independent check and a record, not a hope.

How do I integrate it?

One REST endpoint. Your engineers replace one AI call with a call to Veridect — typically a 10–20 line change — and the answer comes back verified, with the record attached. Agents connect the same way: a gateway that sits in the path of MCP tool calls, adapters for OpenAI Assistants and Anthropic Computer Use, or a single call wrapped around each high-stakes action in a custom framework.

It runs where you say — AWS, Azure, GCP, or on-premises — on your own keys and the model providers you already use. Nothing is ripped out. The models stay swappable, and swapping one later is a configuration change, not a re-engineering effort.

How long does it take?

Today: run the live system yourself. Nothing to install, no one’s approval needed. A private sandbox — your own tenant, your policy thresholds, your data — takes a day once you say go. Production is typically about two weeks, and that clock runs mostly on your side: security review, key provisioning, access approvals. Our side is ready on day one.

Once we’re working together, a mutual NDA opens a private integration document built to your specs, followed by hands-on working sessions to wire Veridect into your stack.

How will this make me money?

Three ways — and we won’t invent a number for a business we haven’t seen.

• Revenue you’ve been holding back. The highest-value agent work — anything that touches money, customer data, or a record — only ships when someone can sign off on it. An independent check plus a signed record is what lets it ship.
• Cost you stop paying. Routine calls settle on a fast quorum; the hard rules — money over a limit, personal data, health data, protected-class factors — run in plain code at zero model cost; only the risky slice goes to a person, so your people review the exceptions, not every call. Four models isn’t four times the bill — it’s a few cents of extra checking on the one action that could really hurt you — and one engine across departments replaces a vendor per function, so total AI spend nets down, not up.
• Losses you don’t take. The out-of-scope action blocked before it executes; the risky one held for a human; the incident, fine, or breach that doesn’t happen. And when the audit, the security review, or procurement asks was this genuinely checked?, the evidence is already built — a signed record, not weeks of reconstruction.

Your own number comes out of the sandbox, on your own workflows.

Why you, and not a big, well-known company?

Because the big names can’t stand where this layer has to stand. A model vendor can’t be the independent check on its own model — that’s a model grading its own work, and bundled “governance” is self-governance. The large security names check the edges — was the prompt safe, was the response safe — not whether the answer was right, whether the agent was allowed to act, or whether there’s proof afterward. Nobody sold all of it as one control plane — verify, govern, prove, and see risk across a whole fleet — so we built it. The engine behind it is proven in education and in production under Fortune 100 contracts in regulated industries.

And the size question, answered by design rather than by promise: Veridect runs in your environment, on your keys and your providers; the models are swappable, and so are the agent frameworks — the fleet and fabric layers govern many agent harnesses at once, holding agents built on different frameworks to one policy in one ledger for every action they send through Veridect; and every decision record verifies offline against a published key, with no call to us. Your dependency on any vendor — including us — is bounded on purpose.

Don’t take the claim on trust. A credentialed Fortune 100 model-risk reviewer ran live adversarial scenarios against the production system, and every one matched pre-stated behavior; a separate deterministic test suite holds 4,697 policy scenarios at 100% conformance; the open findings are published next to the results. And you can see it live in a minute.