The physics layer of AI in regulated manufacturing — where a non-compliant output physically cannot execute. On-premises, zero-egress, neutral across every silicon and cloud vendor. The AI advises. A named human decides. Every time, with the evidence a regulator actually asks for.
The deterministic core — the P→D Bridge, the HITL Gate, the ALCOA+ Chain — is identical everywhere it runs. What changes is the deployment shape and the proof that matters to you.
PCCP-aligned change control, GAMP 5 validation evidence, named Quality Unit sign-off on every AI-influenced record.
→ Apply for a 2-week Shadow Audit FOOD & BEVERAGEHACCP-aligned preventive controls, trajectory-to-limit catches logged as provable arithmetic, not a reviewer's guess.
→ Apply for a 2-week Shadow Audit INDUSTRIALS & AUTOMATIONCatches the semantic and procedural violations your interlocks can't see — a recipe change inside limits but outside the validated design space.
→ Scope a shadow-mode line pilot SILICON & ROBOTICSGoverns GenAI running on OpenVINO, Kleidi, eIQ, or ONNX runtimes — makes your silicon admissible in regulated sockets without you owning certification.
→ Request a dev-kit workshop SYSTEMS INTEGRATORSThe governance engine and Evidence Pack methodology underneath a regulated-AI delivery practice you own and bill.
→ Start a practice-build conversation CLOUD PARTNERSRuns at the customer's edge; evidence rolls up to your cloud for oversight — without asking a regulated customer to move production data.
→ Scope a marketplace listingEvery one of these is a real question an inspector, an auditor, or a board asks after something goes wrong — not a hypothetical.
Three things happen before any AI-influenced production action proceeds — identical logic, regardless of which segment above you're in.
Every AI recommendation passes deterministic physics-based enforcement before it can influence production — trajectory mathematics that catches a drift toward a limit while the reading is still in spec. The AI advises. Physics decides whether a human must be asked.
A named Qualified Person authorizes or overrides any AI-influenced HOLD or KILL — a cryptographically signed governance event with identity, timestamp, and decision, not a checkbox.
Every recommendation, every threshold check, every human decision — written to a tamper-evident, sequence-numbered record in real time. Three clicks to any event, no batch number required.
Four ways the engine is actually used — before you change anything about how your line runs today.
The engine runs in parallel against your real facility data for two weeks — producing real, chain-logged verdicts with zero authority over your line. You see exactly what it would have caught, and keep the full audit trail either way.
A digital bench for your own process data — upload readings, run capability experiments, and watch the same deterministic engine that governs production catch a drift while the batch is still in spec. Isolated from live systems; findings promote to production only through governed change control.
Replay months of your historical data through the engine and see your real exposure — every event it would have flagged, with the evidence pack to show for it — before committing any budget or integration.
A spoken, on-premise briefing agent. "What changed overnight?" answered from the chain-logged record, citing the actual clause or event — zero bytes leave the building to produce it.
The Gate is deliberately built on decades of certifiable deterministic-enforcement precedent — not novel ML on the safety path. NVIDIA's Halos (June 2026) proved buyers pay for deterministic enforcement between AI and actuation — for the NVIDIA stack. The neutral, evidence-native equivalent the rest of the ecosystem needs is the layer Kaelox occupies. History says that layer ends up independent: silicon vendors don't certify their own safety layers.
Graduated Envelope Authority: autonomy measured as the fraction of decision space deterministically pre-authorized on evidence — never the fraction of decisions a model is trusted to make. Envelopes expand only through signed, chain-logged change control gated on adjudicated shadow evidence; they contract automatically and instantly on any drift or KILL. The human touches ever fewer decisions. The AI never gains authority. Design specified and governed today; implementation sequenced on our funded roadmap — stated plainly, like everything else here.
Every figure below is drawn from a public benchmark dataset or this build's own verified test suite — sourced, reproducible, and stated with its limits attached, not rounded up.
Full methodology, including where a claim can and can't be made from the underlying dataset, available on request.
CONFIGURING FOR: MEDTECH & PHARMA — FDA / QMSR · change →
Select what applies to your facility. This produces a real specification and connects you to an engineer who will price it — not an automated instant quote.
Illustrative preview, based on this build's verified test data — not a live production feed.
Brochures download directly, no email required. The three research briefings below are longer-form and go out by email since they're built for a slower, offline read.
The full Medtech & Pharma brochure — proof, features, and outputs, no form required.
↓ Download PDFThe full Food & Beverage brochure — proof, features, and outputs, no form required.
↓ Download PDFSegment-specific brochures for the other four paths aren't built yet — the positioning papers they're based on are available on request.
AI is already autonomous in your competitors' factories. Human command is the only variable still in your hands.
Reserve PDF →Why AI cannot enter regulated manufacturing without a governance layer — and why every other approach fails to close it.
Reserve PDF →A US, UK, and EU comparison of AI-assisted reshoring compliance risk.
Reserve PDF →