AI-Driven Smart Contract Testing & Simulation

Proprietary AI models trained on 10,000+ verified exploits automatically detect logic flaws, reentrancy, and economic attacks that traditional tools miss.

Execute transactions in a sandboxed fork of Ethereum, Polygon, or Arbitrum mainnet. Test complex interactions with live protocols like Uniswap and Aave without spending gas.

Mathematically prove critical contract properties (e.g., "total supply is constant") using symbolic execution and custom invariant suites, providing absolute security guarantees.

Detailed gas reports and execution traces identify optimization opportunities, reducing user costs by up to 30% and preventing out-of-gas reverts in production.

Simulate extreme market conditions, oracle failures, and coordinated attacks with customizable bots to stress-test your protocol's economic resilience.

Seamless integration with GitHub Actions and GitLab CI. Automated testing on every pull request with detailed reports, ensuring regressions are caught immediately.

Our AI engine scans for 100+ known vulnerability patterns (reentrancy, overflow, access control) and uncovers novel, protocol-specific risks that traditional tools miss.

We profile every function to identify and eliminate gas inefficiencies, reducing operational costs for your users and improving contract scalability.

Mathematically prove critical invariants and simulate thousands of transaction sequences to ensure contract logic holds under all market conditions and edge cases.

Design and test secure upgrade paths using proxies (UUPS/Transparent) and ensure flawless integration with oracles, bridges, and other DeFi primitives.

Receive meticulously commented code, a full test suite with >95% coverage, and a detailed technical specification document to streamline third-party security audits.

We guide you through the final deployment checklist, multisig configuration, and initial monitoring setup to ensure a smooth, secure launch.

We analyze your smart contract architecture and business logic to identify critical vulnerabilities and define test objectives. This includes threat modeling and establishing key security metrics.

Our proprietary AI engine generates thousands of adversarial test cases, including edge cases and complex attack vectors that manual testing misses. We target reentrancy, oracle manipulation, and logic flaws.

We execute tests in a high-fidelity, forked mainnet environment. Advanced fuzzing explores the state space to uncover deep logical errors and quantify gas inefficiencies under load.

You receive a prioritized vulnerability report with exploit PoCs, gas optimization insights, and actionable remediation guidance. We support your team through the fix-verify cycle.