Prove AI model integrity across version changes, retroactively.
When you update an AI model (v3.5 → v4.0, etc.), you want to verify later whether past decisions are reproducible or whether results change. Lemma commits each point-in-time modelId and policyHash at decision time, keeping past decision logic cryptographically traceable even after the model updates.
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”
Hand over the source, or just the facts?
Change what reaches the AI, and the leakage risk goes with it.
- decision_id:
- D-001
- model:
- claude-3.7-sonnet
- old_model:
- gpt-4-turbo
- policy:
- ? (unknown at the time)
- output:
- approved
- agent:
- did:lemma:agent-decision-001
- modelId:
- claude-3.7-sonnet@2024-08-15
- policyHash:
- 0x71c5…
- inputCommitment:
- 0xb4e2…
- outputCommitment:
- approved
- satisfiesPolicy:
- true
- recordedAt:
- 2024-08-15T10:23:00Z
- ZK verified:
- ✓ VALID
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 ↗Choose on three criteria.
Only work that needs all three at once — pass without exposing, independent verification, tamper-proof — is Lemma's domain.
| Method | Pass without exposing | Independent verification | Tamper-proof |
|---|---|---|---|
| Access control only | △ | ✗ | ✗ |
| Masking / anonymization | △ | ✗ | ✗ |
| Encryption only | ✓ | ✗ | ✗ |
| Lemma (ZK proof)the only one with all 3 | ✓ | ✓ | ✓ |
What's next
We enter through version-pinning schema design and a PoC, and stay alongside you through to operations.
- A 30-minute review — identify the AI systems and decision types where a model change is expected.
- Design the version-pinning schema — define the modelId@timestamp + policyHash combination.
- Connect proof issuance at decision time — attach a commitment to every AI inference result.
- Prove one system via a PoC — roll out to one decision flow in 4 weeks, confirming retroactive verification after a model update.
- Hands-on support through operations — existing plan tiers (Civic / Critical / Compliance) serve only as a cost reference; the setup and pricing are designed together.
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.
The bigger picture
The bigger picture this use case belongs to.
We map use scenarios across industries and workflows by the four axes.
See use scenarios for Verifiable AI in Solutions →TRY LEMMA
Run it yourself.
No sales call needed — start hands-on with Lemma's products.