Air-Gapped AI Code Review: Which Tools Support Self-Hosted LLMs?
Hello Devs 👋 AI code review sounds pretty straightforward until you work on a project where the source code cannot leave your company's network. You might want an AI tool to review pull requests, catch bugs, check coding standards, and help developers fix issues before merging. But if you're working in a regulated industry, handling sensitive intellectual property, or building software inside a…
Air-gapped AI code review presents a challenge when source code must remain within a company's network. While AI tools can review pull requests, catch bugs and enforce coding standards, connecting to external AI services is often not feasible in regulated industries or restricted networks.
The key differences to consider are self-hosted and air-gapped deployment models. Self-hosted means the review service runs on your own infrastructure, though it may still connect to an external model. Air-gapped goes further, requiring the entire review engine, model, codebase indexing, Git integration and other components to function within an isolated network without internet access.
Factors to evaluate before choosing a tool include your Git provider, model configuration, code review components, and installation/update process. Qodo is highlighted as a tool that offers full on-premises and air-gapped AI code review. Qodo 3.0 supports self-hosted models like NVIDIA Nemotron and integrates with major Git platforms. Its advanced features like Software Map and PR Triage provide additional value for reviewing complex codebases within air-gapped environments.
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