Fairy for Code.
AI generates code. Fairy determines whether it is ready for production.
Security vulnerabilities, logic errors, architecture issues, and dependency risk — verified before they reach your users. Continuous oversight after they ship.
The platform
AI + Fairy = production-ready code.
AI coding tools are fast. They are not infallible. Every AI-generated codebase carries risk that grows invisible over time — until it shows up in production.
Fairy is the operating layer between your AI and your users. Software continuously monitors what ships. Senior engineers step in when risk, complexity, or confidence requires judgment. The platform learns your codebase and improves with every review.
What we verify
- Security vulnerabilities (OWASP Top 10, injection, XSS, CSRF)
- Authentication and authorization flaws
- Insecure dependencies and supply chain risk
- Logic errors and edge case failures
- Race conditions and concurrency issues
- Missing error handling and silent failures
- Architecture and design pattern issues
- Performance bottlenecks in hot paths
- Data exposure and PII handling
- Missing tests for critical paths
What's at risk
AI doesn't know what it doesn't know.
The same speed that makes AI coding tools valuable makes their failure modes hard to spot. Issues compound quietly until they don't.
Production outage
An unhandled edge case or race condition takes down a live system.
Security breach
An auth bypass or injection vulnerability exposes user data.
Compliance violation
PII mishandling triggers GDPR, HIPAA, or SOC 2 exposure.
Technical debt
Architectural issues compound over time, slowing every future change.
How it works
From AI commit to production confidence.
Connect your repo
Install the Fairy GitHub App. Point it at the repositories where your AI tools operate. Takes under 60 seconds.
Fairy monitors every change
Each pull request is analyzed automatically. Software catches obvious issues immediately. When confidence requires it, a senior engineer reviews with full context.
Verified verdict, continuously
Clear findings by severity, a signed verdict, and continuous oversight after merge. The platform learns your codebase and gets more valuable over time.
FAQ
Common questions.
What does Fairy check in AI-generated code?
Fairy checks for security vulnerabilities (OWASP Top 10, injection, auth bypass, insecure dependencies), logic errors, architecture issues, missing error handling, race conditions, and anything that creates real-world risk in production. It combines automated software analysis with senior engineer verification when confidence requires it.
How quickly can Fairy verify AI-generated code?
Fairy offers instant verification (typically under 30 minutes, paged to a senior engineer), standard 4-hour turnaround, and 24-hour async review. Speed is configurable per submission.
What AI coding tools does Fairy work with?
Fairy works with any AI coding tool: Claude Code, Cursor, GitHub Copilot, Devin, and any agent that produces code in a GitHub repository. Integration is via GitHub pull request — no new tools to learn.
What happens when Fairy finds a critical issue?
Fairy returns a structured verdict with findings by severity. Critical and high-severity issues include a clear description of the risk, the affected code location, and a recommended fix. The submission is not signed off until issues are resolved or explicitly accepted with documented rationale.
Does Fairy replace code review?
Fairy is the operating layer between AI output and production — it replaces the manual review burden for AI-generated code. For human-written code, it acts as a safety net. The platform handles the majority automatically; a senior expert signs off when judgment is required.
Is my code kept confidential?
Yes. Code submitted to Fairy is never used for training, never shared with third parties, and reviewed only by the assigned expert under strict confidentiality. Enterprise agreements with additional data handling requirements are available.