AI Audit Log Proof
Lemma seals each AI decision's attribution with a ZK proof at the moment it is made, so the original rationale stays recoverable and accountable even after the model is updated.
Three voices from the front line.
- Internal audit / compliance
“To reconstruct the basis of an AI decision later, we need a trail of the inputs, model and process”
- Legal / executives
“We can't explain AI-driven decisions to regulators or shareholders”
- CISO / security
“We can't detect tampering of AI decisions, so accountability is blurred”
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.
- 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.
- Proven fact
- the output came from authorized instructions and inputs
- the prompt, input data and model internals
- not shown
- Login / keys
- not needed
- 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 the AI decides, the model used, the facts input, the criteria applied, and the final conclusion are fixed as one verifiable trail. The raw data stays in-house; what leaves is only the fact of "when, which model, on what basis, decided what." Past decisions stay immutable even as the model updates, and regulators, auditors and claimants can independently verify the same trail without disclosing the original data.
See the technical details ↗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 copies | △ | ✗ | ✗ | Redaction work grows; the original is still unproven |
| Encrypt and store / send | ✓ | ✗ | ✗ | To verify, the receiver needs it disclosed after all |
| Logging / monitoring only | △ | ✗ | ✗ | Detection only — the receiver still cannot verify independently |
| Lemma (ZK proof)the only one with all 3 | ✓ | ✓ | ✓ | The receiver just opens a link |
How it works — and how to start.
We help design disclosure scope and retention, run the PoC, and support production.
Start with a 30-minute call.
Tell us one AI decisioning system where accountability risk concentrates, in the first 30 minutes. No model implementation details or sensitive information required.
Related Use Cases
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