Blog

Essays, changelog, and field notes.

Essays

2026.04.16
Business Strategy

"Explainable Management" Powered by Cryptographic Proofs

As AI decision-making becomes widespread, 'explainability'—the ability to retrospectively prove the basis for decisions, not just the outcomes—has become a critical management issue. Against the backdrop of strengthening regulations like the EU AI Act, this article explains the management risks posed by the technical black-box problem. Furthermore, it explores an architecture for 'provable management' and its practical KPIs, utilizing Lemma's Zero-Knowledge Proofs (ZK proofs) and blockchain technology to permanently record AI decision logic and data as a tamper-proof audit trail.
"Explainable Management" Powered by Cryptographic Proofs
2026.04.07
Human Impact

Verified Attributes in Travel and Public Services

Travel and public services suffer from an inefficient structure where the same personal information is repeatedly submitted and stored across multiple organizations. Passport copies, income certificates, and medical records spread across systems, increasing breach exposure. Lemma proposes a third option: 'Do not share raw data — circulate only verified facts.' This article explores a practical approach to streamlining hotel KYC, visa processing, and public benefit eligibility checks using ZK proofs, all while protecting privacy.
Verified Attributes in Travel and Public Services
2026.04.01
Business Strategy

Privacy-Preserving Attribute Marketing: Lemma Verifiable AI's Practical Approach

As data sharing within corporate groups becomes restricted by regulations, Lemma Verifiable AI uses Zero-Knowledge Proof technology to verify attributes without disclosing data, enabling secure marketing collaboration. This article explains the technical approach to attribute marketing based on ZK proofs, implementation details, and expected KPI improvements.
Privacy-Preserving Attribute Marketing: Lemma Verifiable AI's Practical Approach
2026.03.26
Business Strategy

Verifiable AI KYC/AML Without Data Sharing: Lemma's Practical Approach

In KYC/AML operations for financial institutions, balancing privacy protection and rapid verification poses the biggest dilemma. Lemma Verifiable AI, built on ZK-proof foundations, offers a solution. This article explains the practical approach of verifying attributes without data sharing while ensuring AI transparency, covering technical design to business impact.
Verifiable AI KYC/AML Without Data Sharing: Lemma's Practical Approach
2026.03.18
Human Impact

From Data Sharing to Verification Sharing: The Evolution of Supply Chain Trust Infrastructure

Traditionally, supply chains have faced a trade-off between data sharing and third-party audits for building trust. Lemma proposes a third option—'verification sharing'—using zero-knowledge proofs to verify facts without sharing the underlying data. This enables real-time automated verification while preserving privacy, allowing AI agents to make autonomous procurement decisions.
From Data Sharing to Verification Sharing: The Evolution of Supply Chain Trust Infrastructure
2026.03.12
Business Strategy

Cryptographic Trust Chains Between Agents: How A2A Collaboration Will Transform the API Economy

As AI agent-to-agent (A2A) collaboration expands, ensuring trustworthiness has become the paramount challenge. Lemma proposes a cryptographic trust chain consisting of three layers: organizational identity signatures, zero-knowledge proofs of policy attributes, and verifiable authority scopes. This approach solves structural problems in the API economy, enabling protocol-level automation of KYC/AML compliance and establishing trust metrics at the management level.
Cryptographic Trust Chains Between Agents: How A2A Collaboration Will Transform the API Economy
2026.03.04
Tech Insight

Verifiable AI: A New RAG Design that Demonstrates Trust Origins with Cryptography

Addressing the trust challenges of AI agents and RAG systems, we propose a novel design that leverages cryptographic technologies (zero-knowledge proofs, selective disclosure, and provenance tracking). This approach builds a verification layer for data origins and condition compliance before AI reads the data, ensuring the overall reliability of the system.
Verifiable AI: A New RAG Design that Demonstrates Trust Origins with Cryptography
2026.02.28
Guides

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.
2026.02.28
Guides

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.
2026.02.28
Guides

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.
2026.02.28
Guides

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.
2026.02.28
Guides

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.
2026.02.28
Guides

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.
2026.02.24
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.

FAQ

2026-03-12
FAQ

Lemma FAQ — AI Trust & Verifiability

Frequently asked questions about Lemma and Verifiable AI