Code Intelligence offers an AI‑driven fuzz testing platform that automatically generates high‑coverage test cases for C/C++, Java, and JavaScript code and integrates into CI/CD pipelines. The solution provides AI assistants for creating test harnesses, parallel execution for scaling, and precise, zero‑false‑positive bug reports with source locations, helping development and security teams find critical vulnerabilities early without hardware dependencies.
Funding
$11.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
4OFounders
Product
Problem
Software developers and security teams often lack efficient, automated methods to discover deep bugs and security vulnerabilities early in the development cycle, especially for embedded and safety‑critical code that must meet industry standards such as ISO 21434 and IEC 62443. Traditional testing requires extensive manual effort, hardware dependencies, and can miss critical issues that only appear with unexpected inputs.
Solution
Code Intelligence provides an AI‑driven fuzz testing platform that automatically generates high‑coverage test cases for C/C++, Java, and JavaScript code. Its CI Fuzz engine integrates with CI/CD pipelines to run coverage‑guided fuzzing on each code change, delivering reproducible bug reports with exact source locations and zero false positives. The platform includes AI assistants (CI Spark) that detect entry points and create test harnesses, a parallel execution manager (CI Sense) for scaling across large codebases, and a cloud‑hosted analytics service (CI Sense dashboard) that tracks coverage, regression detection, and compliance with standards. By eliminating hardware dependencies and manual test authoring, developers can find and fix critical issues within minutes rather than weeks.
Target Audience
Primary customers are software development and security teams in industries with stringent safety and regulatory requirements, such as automotive, medical devices, and embedded systems, as well as any organization seeking automated, high‑coverage security testing for native and managed code.
Features
- AI‑guided, coverage‑directed fuzzing that automatically creates and mutates inputs to maximize code coverage
- Integration with popular CI/CD systems and IDEs for continuous security testing on every code commit
- Parallel test execution (CI Sense) to scale fuzzing across multiple projects and large codebases
- AI assistant (CI Spark) that identifies test entry points and generates test harnesses without manual effort
- Precise bug reports with reproducible inputs, stack traces, and direct links to the offending source line
- Zero false‑positive results through white‑box analysis and exact location reporting
- Support for automotive and medical device compliance, providing evidence for ISO 21434, IEC 62443, and related standards
- Open‑source fuzzing engines (Jazzer & Jazzer.js) for Java and JavaScript, extending coverage to managed languages