You can't expose secrets. You can't audit decisions. You can't pass regulation. AI agents can't be trusted with work. The last hurdle of AI adoption isn't model quality — it's the proof layer. Lemma resolves it structurally with a data-less design.
● live in production since 2025 · Compatible standards: MCP / A2A / x402 / C2PA / W3C VC · ETHGlobal AI Agents 2026 Finalist
Four use scenarios
01 · Verifiable Origin
Source and integrity
Encrypt originals, pass only docHash and CID to AI. Secure provenance of RAG sources, training data, and IoT sensors—at the origin. Poisoned data never arrives.
P1 Verifiable Origin →02 · Agent Authority Proof
In-scope work runs
Agents run autonomous transactions with scope constraints ("≤ ¥100k", "jurisdiction:JP") via x402—at runtime. Drive expense approvals, procurement, and cross-agent transactions 24/7. Out-of-scope actions blocked before execution.
P3 Agent Authority Proof →03 · Regulatory Attribute Proof
Regulatory attribute compliance
Prove attributes required by KYC, AML, CBAM, EUDR, AI Act—selectively, without disclosing originals. Block AI-generated fraud (synthetic IDs) at the same layer.
P4 Regulatory Attribute Proof →04 · Verifiable AI
Operational integrity / compliance
Independently verify AI inputs, outputs, and behavior—without revealing content. Detect prompt tampering and output integrity at the same layer.
P2 Verifiable AI →Implementation scenarios indexed by industry and operational line. The 'how to integrate' details live in each Use Case.
Preserve inputs, model, and output of AI decisions as tamper-evident evidence.
Disclose only regulatory attributes as cryptographic proofs — no raw data.
Record multi-tier supplier provenance as a tamper-evident chain.
Preserve internal RAG document provenance; make AI citations auditable.
Independently verify civic eligibility without disclosing citizen attributes.
Browse implementation patterns by industry and operational line.
Conceptual structure → Trust Infrastructure (Why) →
Existing systems keep running. Coexistence design: drop the trust infrastructure in front.
Review Lemma's capabilities, fit, and the key questions in 30 minutes. Detailed scoping happens in the PoC phase.
Implement the trust infrastructure for one target scenario, end-to-end through internal validation.
Promote the PoC configuration as-is. Keep existing systems running; the trust infrastructure sits in front.
// Add this in front of your existing AI call import { prover } from '@lemmaoracle/sdk' const { proof } = await prover.prove(claim) // Pass the proof to AI. The original never leaves. SDK launches soon. Enterprise customers can start with a preliminary PoC. Custom integrations are designed in the Discovery Call.
Check each item that applies. Three or more means it's worth a serious look at integrating Lemma.
Threats in the field
Critical Brief structures the regulations, incidents, and attack patterns that shape AI today—the context behind the "run" guides above.
Confidentiality, accountability, regulatory compliance — integrating from the proof layer first sets AI adoption's next move in motion.