Why Lemma

Four pillars of verifiable trust.

Data provenance, AI decisions, agent transactions, regulatory compliance — bound by ZK proofs.

P1

Verifiable Origin

Cryptographically valid ≠ semantically right
Data is copied. Provenance is carved.
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P2

Verifiable AI

Finds bugs ≠ proves decisions
Models change. Proofs remain.
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P3

Agent Trust Chain

Pays ≠ trustworthy
Authority can be delegated. Only provable authority should be.
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P4

Regulatory Attribute Proof

Compliance promised ≠ compliance proven
Data stays. Proofs travel.
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Guides
Technical documentation.

Implementation guides for each layer of the Lemma architecture.

Guides 2026.02.28

Define Your Domain as a Schema

Model how your AI retrieves and clusters knowledge — bucket ages, risk scores, regions — with typed schemas and normalization. Register ZK circuits and generators so every fact traces back to its source.

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Guides 2026.02.28

Disclose Only What AI Needs

Selective disclosure lets holders reveal just the attributes your model requires, while the link to the original issuer signature stays intact.

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Guides 2026.02.28

Encrypt Everything, Expose Nothing

How Lemma keeps every document AES-GCM encrypted so your AI never touches raw PII — only docHash and CID are exposed as stable anchors for provenance.

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Guides 2026.02.28

Prove Facts with Zero Knowledge

Turn business rules like 'over 18' or 'revenue above threshold' into machine-checkable facts. Each proof is permanently recorded with its circuit and generator.

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Guides 2026.02.28

Provenance That Never Disappears

Document commitments, schemas, issuers, and ZK verification results are anchored on-chain. Your RAG index can be rebuilt, your embeddings re-computed — the provenance layer stays permanent.

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Guides 2026.02.28

Query Verified Attributes

Ask 'users over 18 in Japan' and get back attributes with full provenance — proof status, schema, issuer, generator, and verification method — ready for your RAG policy layer.

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Foundations

Lemma Oracle Specs

A cryptographically verified truth layer enabling AI to reason over confidential data via zero‑knowledge proofs, selective disclosure, and on‑chain provenance — all while keeping raw content encrypted.

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