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Use case — Verifiable AI

Prove AI model integrity across version changes, retroactively.

When you update an AI model (v3.5 → v4.0, etc.), you often need to verify later whether past decisions are reproducible or whether the results change. Lemma commits each point-in-time modelId and policyHash at decision time, so past decision logic stays cryptographically traceable even after the model updates.

Finance / FinTech · AI adoption (cross-industry) · AI governance Plan Lemma Critical
01 · THE PROBLEM

Three voices from the front line.

  • AI engineering / operations

    “After a model update, we end up needing to reproduce and verify past decisions retroactively”

  • Audit / regulatory

    “We want to prove we ran "that policy" on "that model" at the time”

  • Legal

    “We want to clarify accountability for past AI decisions after the fact”

02 · THE SHIFT

Hand over the source, or just the facts?

Nothing changes on the floor. Everything changes for the receiver.

① Your team just saves, as always.

Your team's existing screen
The usual step
Fill in the record and save
On save
A proof is attached (API, behind the scenes)
The document itself
never sent

② They just open a link.

Their browser — verification
Not tampered
Proven fact
the same decision before and after a model change (or the diff)
the model internals, parameters and training data
not shown
Login / keys
not needed
Why Lemma
  • The document stays private — the record itself is never sent or disclosed.
  • Independent verification — the receiver just opens a link. No account, no keys.
  • Edits are detected — even a one-character edit fails verification.

At the moment of decision, modelId@timestamp and policyHash are pinned and committed together with the input/output commitments and satisfiesPolicy. This record stays immutable even after the model updates, so past decisions can be verified retroactively against "that model, that policy." Without disclosing model internals or parameters, the integrity of a decision can be independently shown.

See the technical details ↗
03 · HOW TO CHOOSE

Why the usual methods fall short.

Only work that needs all three at once — pass without exposing, independent verification, tamper-evidence — is Lemma's domain.

Method Pass without exposing Independent verification Tamper-evident What happens
Access control / permissions“Someone inside could have edited it” remains possible
Masking / redacted copiesRedaction work grows; the original is still unproven
Encrypt and store / sendTo verify, the receiver needs it disclosed after all
Lemma (ZK proof)the only one with all 3 The receiver just opens a link
04 · HOW IT WORKS

How it works — and how to start.

What you prove
Provethe same decision before and after a model change (or the diff)
Keep hiddenthe model internals, parameters and training data
01 — youChoose the record to prove Start with the one flow where hand-offs cost you the most explaining.
Issue the proof
Senthash only
The documentnever sent
Issued 0x68d4…9f01
02 — you → themAdd issuance Call the API once when the record is finalized. The document itself is never sent.
The verifier's screen
Not tampered
SignatureIntegrityIssuer
03 — themLet the receiver verify They open a link — no account, no keys.

We help design disclosure scope and retention, run the PoC, and support production.

Start with a 30-minute call.

Tell us one AI system worried about explaining past decisions after a model update, in the first 30 minutes. No disclosure of model internals required.

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