The problem isn’t that AI is wrong.
It’s that we believe it’s right.
AI hallucination lawsuits up 570% ↑ in eight months. Billions in damages. Most were preventable with verification.
ZH-1 catches fabricated citations, verifies regulatory eligibility, and scans documents for hallucinated facts — so you never file, submit, or publish something that isn’t real.
Results are computed from encoded rules, not AI generation. External data sources are subject to standard validation.
This is what happens when you trust AI without verification.
Lawyers sanctioned. Patients endangered. Businesses fined. These are real stories — and they happened because nobody checked whether the AI’s answer was actually true.
Stories sourced from public news coverage. Cost descriptions are editorial characterizations, not direct quotes.
AI lawsuits up 570% ↑ Real costs. Real consequences.
From $85K court sanctions to $250M fraud schemes — we documented every case so you don’t become the next one.
We don’t guess. We compute.
Most AI tools generate probable answers. ZH-1 looks up the actual rules and computes the actual answer. Same question, same rules, same result — every single time.
See the difference for yourself.
Run a compliance test to see ZH-1 vs. LLMs, or scan a document for hallucination patterns.
— compliance tests. Live results.
ZH-1 is a deterministic engine — it computes answers from rules. The models below generate answers probabilistically. This demonstrates why deterministic verification exists.
ZH-1 is a rule-based engine, not a language model. Its accuracy reflects currently encoded rulesets and does not guarantee regulatory completeness. AI model scores reflect their responses to the same compliance scenarios. Results update as rulesets are expanded.
Results from deterministic testing of — compliance scenarios. Cards marked EST. show scores derived from published benchmarks; all others reflect live testing against the ZH engine. See Terms of Service.
AI alone scores ~2%. With ZH-M: 70%.
ZH-M is a deterministic verification layer for mathematics. It amplifies frontier AI models on the FrontierMath benchmark — problems that took professional mathematicians hours to solve — pushing convergence from ~2% to 70%+ with zero hallucinations.
Convergence by Model (37 FrontierMath problems)
Full Results
| Model | Converged | 1st Attempt | Avg Iter | Tokens | Cost | Halluc. | Runtime |
|---|---|---|---|---|---|---|---|
| CSonnet 4.6 | 26/37 (70.3%) | 26 | 1.0 | 115K | $1.73 | 0.0% | ~37 min |
| COpus 4.6 | 26/37 (70.3%) | 23 | 1.2 | 115K | $8.64 | 0.0% | ~28 min |
| XGrok 4.1 | 26/37 (70.3%) | 25 | 1.0 | 507K | $15.22 | 0.0% | ~118 min |
| GGemini 3 Pro | 25/37 (67.6%) | 25 | 1.0 | 601K | $2.10 | 0.0% | ~22 min |
| LlMaverick 4 | 25/37 (67.6%) | 20 | 1.3 | 98K | $0.05 | 0.0% | ~25 min |
FrontierMath contains problems that took professional mathematicians hours to solve. Frontier AI models score ~2% alone. ZH-M’s deterministic verification loop pushes convergence to 70% with zero hallucinations.
Results from testing 37 FrontierMath problems. “Converged” means the model produced a verified correct answer within the iteration limit.
Real answers for the questions that matter most.
Built for regulated industries.
Here’s exactly what we do and don’t do with your data and our architecture.
- No document content stored after processing
- No training on customer data
- Encrypted in transit and at rest
- Architecture designed toward SOC 2 Type II readiness
- SHA-256 report hashing
- Every decision cites specific rules
- Report integrity verification
- Deterministic outputs for auditors
- Full processing integrity evidence
- Federal rule updates tracked and encoded
- Patent pending (US utility application filed)
Built in public. Verified in production.
The ZH Standard is live and processing real compliance checks. We’re currently onboarding early adopters across housing authorities, benefits agencies, grant compliance teams, and academic institutions.
Start free. Scale when you’re ready.
Every plan includes citation verification, hallucination scanning, and regulatory checks.
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