Guardian gives small engineering teams a desktop release gate for AI-generated code. It combines local code review, policy enforcement, release approvals, and updater-ready desktop delivery in one workflow, so teams can catch risky changes before they ship instead of after.
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Maker
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We built Guardian because AI coding tools make teams faster, but they also make it easier to ship insecure, low-signal, or poorly reviewed changes. Most small teams do not have the time or process overhead for enterprise-style release controls, so we wanted a simpler approach: local-first code review, policy-based release gating, human approval for risky changes, and a desktop app that fits into an actual engineering workflow.
While building this launch, the product evolved from “AI critique for code changes” into a fuller release control system. The biggest shift was treating AI output as something that needs governance, not just generation. That led us to add approval tracking, audit compatibility, updater signing, cross-platform desktop releases, and a workflow that keeps humans in control at the final release step.
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This is becoming more and more necessary. We use AI coding agents daily and the amount of code that gets generated without proper review is honestly scary. Can you define custom policies, like "never ship code that touches auth without a manual approval" or is it more of a general quality check?
Yes. Guardian is policy-driven, not just a generic code quality check. You can define rules for sensitive areas like auth, payments, or infrastructure, and require manual approval before anything touching those parts ships.
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Security in the IDE is where it should be caught - not after deployment. What languages and frameworks do you support? Would love to try this.
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Maker
@sharmila_rangasamy Absolutely. Guardian is strongest today with modern web and desktop stacks like TypeScript/JavaScript, React, Next.js, and Rust/Tauri, and it also understands common config and security-sensitive files. The policy layer is framework-agnostic, so you can enforce rules like manual approval for auth, payment, or release-related changes. If you share your stack, I can tell you how well it’s covered.
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Do you also analyze prompt context and generation metadata etc or only the final code diff?
Guardian is diff-first, but it can also use surrounding context when available, such as prompt context, approval history, and release metadata. The core decision is based on the final code change, with extra context used to make the review more accurate.
This is becoming more and more necessary. We use AI coding agents daily and the amount of code that gets generated without proper review is honestly scary. Can you define custom policies, like "never ship code that touches auth without a manual approval" or is it more of a general quality check?
@ben_gend
Yes. Guardian is policy-driven, not just a generic code quality check. You can define rules for sensitive areas like auth, payments, or infrastructure, and require manual approval before anything touching those parts ships.
Security in the IDE is where it should be caught - not after deployment. What languages and frameworks do you support? Would love to try this.
@sharmila_rangasamy
Absolutely. Guardian is strongest today with modern web and desktop stacks like TypeScript/JavaScript, React, Next.js, and Rust/Tauri, and it also understands common config and security-sensitive files. The policy layer is framework-agnostic, so you can enforce rules like manual approval for auth, payment, or release-related changes. If you share your stack, I can tell you how well it’s covered.
Do you also analyze prompt context and generation metadata etc or only the final code diff?
@lak7
Guardian is diff-first, but it can also use surrounding context when available, such as prompt context, approval history, and release metadata. The core decision is based on the final code change, with extra context used to make the review more accurate.