ProveCheck
A formal-verification-as-a-service for fintech and medtech teams shipping AI-generated or AI-assisted code: submit a function, get a machine-checked proof that its key safety properties hold, plus a customer-facing certificate auditors and regulators can attach to filings.
Engineering leads at fintech and medtech companies using AI coding tools in compliance-sensitive code paths
- Pre-built property library for common AI-generated patterns ('never returns negative payout', 'dosage scales linearly with weight')
- Plain-English property editor so PMs and compliance reviewers can suggest rules in natural language
- Drop-in verification pipelines targeting Dafny/Verus output from popular AI coders
- Signed PDF certificate suitable for SOC 2, FDA, and FCA-style submissions
AI-written code is flooding regulated industries faster than reviewers can audit it; turning formal verification into a service is the only credible answer to 'how do you know the AI didn't break this'.
Multiple 2025 articles document regulated firms racing to verify AI-generated code at compliance-grade rigor, and one market report sizes the 'Formal Verification Copilot' category at $1.8B in 2025 growing to $6.2B by 2034 (14.7% CAGR); strong but the report is a single paid-research source and adjacent to (not directly measuring) the AI-coded-fintech niche.Formal Verification Copilot Market Research Report 2034 ↗AI Powered Development in Regulated Industries | Compliance Challenges 2025 ↗
Direct 'FV-as-a-service for AI-written fintech/medtech code with auditor-facing certificates' is not found; closest incumbents (Certora, Runtime Verification) target smart contracts and Galois targets defense/secure systems, leaving the AI-generated code + audit certificate niche underserved but not a green field.Certora vs Runtime Verification: Formal Verification Comparison ↗Galois - Formal Verification Benchmarks Are the Key to Ironclad Software Infrastructure ↗
Enterprise willingness to pay for formal-verification services is established in crypto (Certora) and defense (Galois), but there is no evidence yet that bank/medical-device auditors or regulators accept machine-checked proofs as a substitute for traditional review, so unit economics are plausible ($50K–$500K+ contracts) but the customer-facing certificate value-prop is unproven.Prover - Certora ↗All formal verification tools for smart contracts ↗
Regulatory pressure is structural and rising (FDA AI/ML guidance, EU AI Act, NIST AI RMF, SR 11-7 in banking) and formal methods have a multi-decade academic foundation; tempered only because auditor/regulator acceptance of machine-checked proofs as compliance artifacts is still an open question.Galois - Formal Verification Benchmarks Are the Key to Ironclad Software Infrastructure ↗AI-Generated Code in Regulated Industries: Balancing Innovation and Compliance ↗
Building reliable, scalable FV pipelines atop Lean 4/Coq/Isabelle that produce regulator-accepted certificates is genuinely hard — proof engineering still demands scarce expertise, LLM auto-formalization is bleeding-edge research, and turning 'function submitted' into an auditor-accepted artifact adds a non-trivial certification layer on top.Galois - Formal Verification Benchmarks Are the Key to Ironclad Software Infrastructure ↗