For AI that acts

Runtime proof for AI operations.

Runtime AI governance with a receipt. Regulayer records what an AI did, under what boundary, as it happened. Built in, not bolted on.

AI entered operations before it entered evidence.

Any consequential AI action can now produce a signed runtime receipt: what happened, under what boundary, and whether the record still holds.

surfaceAI claims agent
actionDECIDE · deny
boundaryHuman-review required
verdictFlagged · escalated
time2026-06-10 22:41:07Z
sealeda1525ce3a2342bd60a7d784d…
signedEd25519 · SHA3-256

Sealed, and checkable by anyone.

The output is no longer the only artifact.

Regulayer creates the missing second object: a signed record of the operation itself. The output can travel. The record stays, and it holds up later without taking anyone's word for it.

Governance moves into the path, not a dashboard.

The control point is the moment the AI acts.

The operation is evaluated against the governing boundary before the record is emitted, not reviewed on a screen after the fact. A bad action caught a week later is a postmortem. Caught in the path, it is governance.

The rest of the market detects after the fact, from the cloud. Regulayer governs before the action, on your machine, and proves it. That is a category, not a feature.

A short path from operation to evidence.

1The system identifies the operation, its context, and the boundary that applies.
2Regulayer verifies whether the operation stays inside that boundary.
3The record states what happened, under what condition, and whether governance held.

The output can be disputed. The receipt can be checked.

Regulation is the wedge. Proof is the category.

The first buyers are high-consequence. The category is everything: an answer, a ranking, an approval, a denial. Each one can carry a receipt.

Intelligence does not require infrastructure.

Regulayer lets AI run where data cannot leave, where nothing can call home, and where the record must survive scrutiny. Sealed, local, and yours. See how it stays in the building.

What you actually install.

A small, signed application your IT installs on the machines where the AI already runs, macOS and Windows, code-signed, with a bill of materials. No account, no server on our side, no change to the model you use. It sits beside the AI, evaluates each governed action against its boundary, and writes the signed receipt locally. Install it, run your network monitor, watch nothing leave. The full security posture.

The difference.

Others observe after. Regulayer governs at the moment of output.

Validation is a moment. Deployment is a continuum. A model that passed its checks in January is a different system under June's load, and the record has to live where the work lives: inside the moment, not after it.

We did not write rules. We built physics.

The moment, and the memory.

Every receipt becomes part of one memory.

The receipt seals one consequential moment. The Witness keeps all of them: one sealed, content-free memory you can ask in plain English and hand over as a packet. The receipt is the moment. The Witness is the answer.

When a record is not enough

Some actions you stop, not just record.

A record proves what happened. But some actions you cannot afford to let happen at all, a payment, a delete, a send that cannot be taken back. So the same layer can also stop the action before it runs, or hold an output before it is released. The brake sits outside the AI, where the AI cannot reach in and switch it off.

It is built to fail toward stop. If the system fails, stalls, or goes silent, the action does not slip through, it stops. Once stopped, it stays stopped until a person re-arms it. And the stop is not silent: it is sealed into the same signed record, so you can show exactly what was held, and when.

How it fits your stack

It sits beside the model, not inside it.

Regulayer runs out of process, next to the AI you already run, not inside it. No change to your model, your prompts, or your pipeline.

It is light enough to run on ordinary hardware, local, with no outbound call. One small component to install, not a platform to stand up.

Where it applies

One kernel, across the work that carries liability.

Privileged AIGovernance, attestation, and a forensic record for AI used inside legal work product. The pilot vertical.
Clinical decision AISurgical robotics, diagnostic support, drug discovery. Operator state, instrument drift, and behavioral drift held in one record.
Underwriting and claimsProvable, auditable cognition behind every risk decision. Continuous evidence, not an after-the-fact appeal.
Decision automationCredit, AML, and trading models bound to a kernel that records what the system did, when, and on whose authority.
Provenance and authorshipA signature of human contribution per session. Article 50 disclosure built into the artifact, not declared beside it.
Embodied systemsRobotics, autonomous platforms, industrial control. Software governance that can also stop hardware is the only kind that counts.

Why the usual safety fails

The sandbox does not hold.

Bolted-on guardrails sit outside the model and can be routed around. A guardrail that lives at the boundary is not a boundary at all.

A model that passes evaluation degrades quietly in production. Most deployed models drift from their validated behavior within months, and the certificate at launch does not certify a billion downstream inferences.

The operator drifts too. Error rates rise under fatigue, and the model cannot perceive operator state. Without continuous evidence, the system leans on a human whose judgement may no longer be reliable.

And litigation has no defense without a record. Every public AI dispute shares one missing artifact: a signed, tamper-evident record of what the system did, when, and on whose authority. Without it, the operator owns the liability outright.

Clean answers.

The questions buyers ask first.

What is Regulayer?

The runtime governance layer for AI. It sits on the path from the model's output to the action, judges each consequential output as it happens, and produces a signed, verifiable receipt as the byproduct.

How is it different from monitoring or observability?

Monitoring sees what already happened. Regulayer governs at the moment of output. The receipt is the act of governance itself, not a report assembled after the fact.

How is it different from content filters or guardrails?

Filters and guardrails sit outside the model and can be talked past or switched off. Regulayer sits on the route from output to action, so the model cannot bypass it. The route is the control.

How is it different from Heartbeat Attested?

Regulayer is the whole estate, the full layer across an organization's AI. Heartbeat Attested is the lightest way in, the same proof scoped to a single AI surface. Same foundation, different scope.

Does it slow the model down?

No. The governing runs alongside the inference. The added time is imperceptible against the model's own response.

Can the model escape it?

No. If the model tries to act outside the layer, it stops producing output. Removing it does not give you an ungoverned model, it gives you no model.

Is it model-agnostic?

Yes. It governs the output, not the architecture that produced it. It works with any model from any vendor.

Does my data have to leave the building?

No. It runs sealed and local with the governed system, with no shared memory or storage with the model, and no outbound call. Your data never moves.

Where are the receipts stored?

With you, never with us. Each operator keeps their own signed record inside their own infrastructure. Regulayer holds nothing, by design, so we can never be the breach surface. What is licensed is the receipt format and the verification, not your data.

Does it help with the law I answer to?

It maps signed, tamper-evident evidence to the specific regulation you answer to. The full register, with penalties and timelines, is available under NDA.

Can I run it alongside my existing AI safety stack?

Yes. It is the layer beneath the rest. It does not replace your filter, your observability, or your evaluation. It makes them auditable.

Who owns the IP?

The estate is inventor-held, patent pending. Specific claim coverage is held under counsel and shared with qualified parties under non-disclosure.

How do I get started?

By introduction. Tell us the problem and the AI behind it, and we reply with a written scope before any call.

The answer travels. The receipt proves what governed it.