Formal Verification for Regulatory Compliance

We translate regulatory requirements (e.g., MiCA, FATF Travel Rule) and business logic into machine-verifiable formal specifications using TLA+ and Coq. This creates an immutable, auditable proof that your protocol's behavior matches its legal obligations.

Prove critical properties like fund solvency, access control invariants, and transaction finality. We verify that your Solidity/Vyper contracts cannot violate defined compliance rules, eliminating entire classes of regulatory risk.

Formally verify interactions between your protocol, oracles (e.g., Chainlink), and bridging solutions. We provide end-to-end proofs that data inputs and cross-chain messages maintain compliance across the entire stack.

Proactively address compliance requirements with machine-verified proof of contract behavior. Reduce review cycles with regulators by providing irrefutable evidence that your logic adheres to MiCA, FATF Travel Rule, or other financial regulations.

Prevent vulnerabilities that lead to fund loss, reputational damage, and regulatory penalties. Formal verification mathematically proves the absence of entire classes of bugs, providing a higher assurance level than manual audits alone.

Differentiate your DeFi protocol, exchange, or institutional product with verifiable security. Publicly share formal verification reports to attract sophisticated users, institutional capital, and partners who demand provable safety.

Lower recurring security overhead. Formally verified code requires less intensive manual review, can lead to reduced smart contract insurance premiums, and minimizes the need for costly emergency patches and post-mortems.

Ensure upgrade safety and maintain compliance as regulations evolve. Our verification frameworks create a living specification, making it safer to modify code and prove that new features don't violate core security properties or compliance rules.

Provide developers with a precise, machine-checkable specification of the system's intended behavior. This reduces human error during development and maintenance, accelerating feature development within a proven-safe boundary.