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Gitar is built with a security-first architecture designed for enterprise-grade environments. Gitar does not retain any code or data after processing. Everything is deleted once an agent run completes. Neither we nor our LLM providers train on your code or data. Your repositories remain completely private. Enterprise customers can bring their own Anthropic API key to route all LLM calls through their own account. Gitar follows SOC 2 Type II and ISO 27001 standards for data protection, encryption, and access management.

You could, but you'd be rebuilding years of deep systems and integration work. Gitar isn't a thin wrapper over an LLM. It's a full AI orchestration layer built specifically for developer workflows and CI/CD environments.

We've built tight integrations with GitHub, GitLab, and major CI systems to give agents direct, secure access to build data, code reviews, and workflow events.

Under the hood, Gitar handles context management, state persistence, and multi-agent coordination across repositories, allowing teams to collaborate through shared workflows rather than one-off prompts.

Our team brings decades of experience building developer tools and workflows for large, enterprise-scale engineering organizations — experience that's reflected in Gitar's reliability, scalability, and developer experience.

And the part that is hardest to build is not the review - it's the precision. Tuning an agent to flag only what's real, across your conventions and your codebase, is the difference between a tool your developers use and a bot they mute.

Most coding assistants stop at writing code. Gitar's agents go further: They understand and act across your CI and code-review workflows with full codebase context.

They root-cause failures, propose and apply fixes, and handle review comments automatically.

Our system combines deterministic build signals with AI reasoning, delivering accuracy, context, and confidence no generic coding or review assistant can match.

Yes. Sign up and get a 14-day free trial of the Pro plan — full access to AI code review, auto-fixes, CI failure diagnosis, agentic workflows, and more. No credit card required to start.

Nothing changes in how Gitar works today. Your existing integrations, CI connections, and configurations remain in place. Over time, Sonar will deepen the integration between Gitar and SonarQube, giving you a more complete view of code quality, security, and review status in one place. If you have questions about your account, contact support.

They are designed to complement each other. SonarQube provides structured, consistent, algorithmic review across 40+ languages, covering code quality, security vulnerabilities, architectural drift, and technical debt. It is fast, auditable, and operates in a zero-trust way with respect to LLMs. It does not assume AI-generated code is correct, and verifies it against defined quality profiles and gates regardless of how the code was written.

Gitar works alongside SonarQube and brings AI-native intelligence to the entire verification workflow. It reads code the way AI reads it, with awareness of context, intent, and the logic of the change as a whole, extending coverage to functional bugs, logic errors, and behavioral issues by reviewing what the code is actually trying to do.

Together, the combination is greater than the sum of its parts. SonarQube's deterministic precision and Gitar's contextual intelligence reinforce each other. Issues one approach catches inform the other, and the coverage they provide jointly closes gaps neither could alone. A CI pass alone does not mean code is production-safe. Layering both approaches means more of what matters gets caught before it ships. Together, they provide a highly comprehensive and accurate review and verification of your code.

No. Gitar and SonarQube bring different review lenses to the same codebase. SonarQube uses mathematical reasoning approaches to verify code against a wide range of known issues: security vulnerabilities, reliability problems, maintainability concerns, and architectural drift. It does this looking at data flows, control flows, syntax, and a range of other topics. On top of that, it applies defined quality profiles and gates consistently to every change, ensuring you can enforce your standards in your codebases. Gitar uses generative AI to review the logic and intent of the change in context, extending coverage to functional and behavioral issues that emerge from understanding what the code is trying to do.

The two are additive and complementary. Used together, they provide deeper and more accurate review than either delivers alone, covering both the known issue catalog that deterministic analysis excels at and the context-dependent logic that AI review is built for.