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) →
Threats in the field
Critical Brief structures the regulations, incidents, and attack patterns that shape AI today—the context behind the "run" guides above.