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TRUST PIPELINE / EVIDENCE, NOT OPINION

Review any codebase.
Prove the parts that matter.
Ship a certificate that travels.

AI proposes, the checker certifies, the certificate travels — a provenance-graded, re-checkable trust layer that sits above any pipeline (SAW, Cryptol, Verus, Dafny, Lean, or plain static analysis).

We check and certify — we never generate-and-trust.

BUILT ABOVE YOUR CHECKERSSAWCryptolVerusDafnyLeanStatic analysis

HOW IT WORKS

A signal path. Not a leap of faith.

ONE CLAIM → TRACEABLE EVIDENCE
  1. 01

    PROPOSE

    AI drafts

  2. 02

    CHECK

    Named methods

  3. 03

    CERTIFY

    Record the scope

  4. 04

    TRAVEL

    Anyone re-checks

A human defines the property and assumptions. Named checks produce evidence; the certificate preserves the method, source revision and limits. Re-checking depends on the method and available artifacts.

THE PRODUCT

Five tiers.
The same certificate throughout.

From broad review to deep assurance. Expand the evidence, not the claim. Current capabilities and planned workflows are distinguished below.

01

Scan

Any repo → graded review + proactive CI findings (breadth).

Bounded public-GitHub review available; proactive CI planned.

02

Certify

Critical cores → AI-extracted invariants, machine-checked, sealed certificate (the moat).

Selected recorded proofs and certificate demos available; automated extraction and sealing planned.

03

Guard

A proven property → CI gate that blocks any regressing PR with the counterexample.

Planned workflow · production CI gate not connected.

04

Modernize

Legacy → new: parity-oracle + refinement proof on extractable cores.

Planned workflow · no autonomous rewrite or refinement runner.

05

Attest

Auditor/regulator-facing re-checkable attestation.

Evidence exports available; auditor attestation service planned.

Explore current repository assurance

EVERY CLAIM IS GRADED

Know exactly how much a claim is worth.

Unlike AI reviewers that emit opinions, every Trust Pipeline claim records its provenance and the evidence needed for independent re-checking. An opinion never wears a proof’s clothes.

AI-suggested

A proposal to review, not an earned verdict.

tool-asserted

A named tool reports a result; its trust and scope are explicit.

machine-proved

A checker proved the stated property under the recorded model and assumptions.

refuted

The property fails, with a counterexample where the method supplies one.

Green-but-wrong is the enemy. A proof is only as strong as the model’s fidelity to the code. Record fidelity gaps, assumptions and unresolved bridges; a digest binds bytes, not their truth or sender.

WHO IT’S FOR

For teams where correctness matters.

01

Enterprise legacy modernization

Prove the rewrite preserves behavior, slice by slice.

02

AI-native platforms

A trust layer over AI-written code.

03

High-assurance / crypto / infra

Real machine-checked proofs on critical cores.

WHAT THIS IS

  • A portable, re-checkable certificate layer.
  • Machine-checked proofs on extractable cores.
  • Claims graded by provenance.

WHAT THIS IS NOT

  • A new prover.
  • A claim that AI proves whole codebases.
  • “Generate and trust.”

MAKE THE EVIDENCE TRAVEL

Build with your checkers.
Ship with a clearer trust story.

Get started

Start with one bounded property. Keep every assumption in view.