Ensure AI-generated code is production-ready
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Ensure AI-generated code is production-ready
Sonar's actionable code intelligence and AI Code Assurance capabilities ensure that all code, regardless of its origin, meets the highest quality and security standards, which is essential for building better software faster.
- Integrate with AI coding assistants, IDEs, and CI/CD pipelines
- Automatically detect AI-generated code from GitHub Copilot
- Detect bugs, vulnerabilities, and quality issues in all code
- Validate AI-generated code with AI Code Assurance
- Generate code fix suggestions in a single click with AI CodeFix
世界中で 700 万人以上の開発者に信頼されています
Code quality assurance for AI generated code
Sonar AI Code Assurance is a robust and streamlined process for validating AI-generated code through a structured and comprehensive analysis. This ensures that every new piece of code meets the highest standards of quality and security before it moves to production.
Code quality assurance for AI generated code
Sonar AI Code Assurance is a robust and streamlined process for validating AI-generated code through a structured and comprehensive analysis. This ensures that every new piece of code meets the highest standards of quality and security before it moves to production.
Fix bugs, vulnerabilities, and quality issues with a click
Sonar AI CodeFix is a powerful capability that suggests code fixes for issues discovered by our code analysis solutions SonarQube Server and SonarQube Cloud. By automating the resolution of common coding problems, Sonar AI CodeFix significantly boosts developer speed and productivity.


主な利点
実用的なコードインテリジェンスを活用し、AI生成コードの品質とセキュリティを継続的に向上させながら、開発者の負担を軽減します。
速度向上
DevOpsパイプライン内でAIコーディングの問題を解決し、リリースサイクルを加速。市場投入までの時間を短縮します。
高品質
AI生成コードがビルドやテスト前に高い基準を満たすようにし、デバッグや手直しにかかる時間を削減します。
安心感
SonarQubeによる自動コードレビューで問題を排除し、生成AIコードベースへの信頼性を高めましょう。
“Sonar helps our development team confidently make both AI-assisted and human-developed code fit for production by reviewing and establishing rules of good programming practices to achieve better code and avoid typical errors. It also assists us in gauging the code coverage for each project, allowing us to identify areas that still require testing.”
Dario Flores, Technical Quality Specialist