Implementation guides for each layer of the Lemma architecture.
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.
Read →Selective disclosure lets holders reveal just the attributes your model requires, while the link to the original issuer signature stays intact.
Read →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.
Read →Turn business rules like 'over 18' or 'revenue above threshold' into machine-checkable facts. Each proof is permanently recorded with its circuit and generator.
Read →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.
Read →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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