Lemma is the Trust Layer for AI — making every data point, every decision, and every agent action verifiable by cryptographic proof. Today, that gap is the real bottleneck for enterprise AI.
Generative AI is deployed but doesn't deliver results. The top challenges all converge on one thing — data.
| Challenge Category | Content |
|---|---|
| Confidentiality & Privacy | Concerns about handling confidential and personal information |
| System Integration | Complexity of integrating with existing systems |
| Data Quality | Not getting expected responses (data quality issues) |
| Accountability | Unclear output basis and inference process |
These appear as separate challenges, but the root converges on one point: data that AI can trust and use is not prepared.
Sensor values, business logs, and contract records are exposed to loss and tampering risks as they pass through multiple points. Feeding them directly to AI induces hallucinations and distorts business reasoning.
Handing over all data necessary for business automation to external parties is not permitted under personal information protection laws and confidentiality management. The contradiction of 'wanting to prove but not show contents' blocks AI utilization.
If agent AI executes autonomously, humans must be able to verify and explain 'why that decision was made.' Traceability of processing grounds becomes a prerequisite for AI adoption.
Lemma's Trust Layer is built on four cryptographic capabilities. Each one addresses one of the data problems above.
Prove where data came from, without revealing what it is.
Prove what an AI saw, and what it decided.
Prove that an agent was authorized to act.
Prove compliance, without disclosing the underlying data.
Six critical operations — transformed from manual to cryptographically verified.
If even one applies, Lemma is effective.
Have operations that proceed based on external fact verification for approval, payment, or next process
Spending manpower, time, and costs on that verification work
Considering AI adoption but concerned about internal data quality and confidentiality management
Need to prove traceability across supply chains
Required to prove 'who did what when' for audit and compliance
Reluctant to disclose confidential information when proving to trading partners or government
Four entry points, one cryptographic foundation. Pick the segment that matches your domain.
Pick one of six bundled samples — financial, manufacturing, or agent — and hit Verify. Real cryptographic primitives, fully client-side. No data leaves your browser.
Open the demo →From ZKP, DID, provenance management technical specifications to PoC design steps that can start in as little as a few weeks. We've compiled 'next actions' for those considering adoption.
ZKP, DID, provenance management technical specifications and implementation approach
Application scenarios for manufacturing, supply chain, and IP management
PoC design, evaluation metrics, and shortest verification steps
Adoption decision checklist and recommended actions