What makes diffray different from other AI code review tools?

diffray uses multi-agent intelligence instead of single-model AI. Multiple specialized agents work together - Security Agent, Performance Agent, Architecture Agent, and Consistency Agent - each expert in their domain. This coordinated approach reduces false positives by 87% and catches 3x more real bugs compared to traditional single-agent tools like GitHub Copilot or CodeRabbit.

How does multi-agent AI code review work?

Multi-agent AI code review deploys specialized agents that work in parallel, each focused on a specific domain: security vulnerabilities, performance bottlenecks, architectural patterns, and code consistency. Unlike single-model approaches that suffer from context dilution, each agent maintains deep expertise in its area. Research shows this approach improves bug detection by 3x while reducing noise.

Is diffray free for open source projects?

Yes, diffray is completely free forever for open source projects. We support the open source community with full access to our multi-agent code review platform, including all specialized agents, unlimited reviews, and priority support.

What programming languages does diffray support?

diffray supports all major programming languages including TypeScript, JavaScript, Python, Go, Rust, Java, C#, Ruby, PHP, and more. The multi-agent system is language-agnostic and adapts its analysis to language-specific patterns and best practices.

How does diffray integrate with GitHub?

diffray integrates seamlessly with GitHub through a GitHub App. Once installed, it automatically reviews every pull request, posting actionable comments directly on the PR. Setup takes less than 2 minutes with no configuration required. Enterprise teams can also use diffray CLI for local reviews before pushing code.

What is the difference between diffray and CodeRabbit or GitHub Copilot?

While CodeRabbit and GitHub Copilot use single-model AI that can hallucinate and produce false positives, diffray employs multi-agent intelligence where specialized agents cross-validate findings. This results in 87% fewer false positives. Additionally, diffray provides full codebase awareness, custom rule support, and agent memory that learns from your team's patterns.

Can diffray detect security vulnerabilities?

Yes, diffray's Security Agent is specifically trained to detect OWASP Top 10 vulnerabilities, injection attacks, authentication flaws, and sensitive data exposure. It analyzes code in context of your entire codebase, reducing false positives while catching real security issues that static analysis tools miss.

How much does diffray reduce code review time?

According to our customer data, teams using diffray reduce PR review time by 73% on average - from 45 minutes to 12 minutes per week. This is because diffray's multi-agent system produces 87% fewer false positives, so developers spend time on real issues instead of filtering noise.

What is the developer action rate on diffray comments?

diffray achieves a 98% developer action rate on its comments, compared to industry average of 15-20% for traditional AI code review tools. This high engagement is due to our multi-agent approach that eliminates noise and surfaces only actionable findings with confidence scores.

How does diffray handle duplicate comments?

diffray guarantees zero duplicate comments through its intelligent deduplication system. Unlike single-agent tools that often flag the same issue multiple times across a PR, diffray's agents coordinate to consolidate findings and present each issue exactly once with full context.

Does diffray store my code?

No, diffray never stores your source code. Code is processed in memory during the review and immediately discarded. We are SOC 2 compliant and your code is never used for AI training. Enterprise customers can also use our on-premise deployment option for complete data sovereignty.

How does diffray compare to GitHub Copilot code review?

While GitHub Copilot uses a single AI model for code review, diffray employs specialized multi-agent intelligence. Research shows multi-agent systems catch 3x more real bugs while producing 87% fewer false positives. diffray also provides full codebase awareness, custom rules, and agent memory - features not available in Copilot's code review.

diffray 如何帮助开源维护者？

diffray 自动审查每个 PR——从首次贡献者到常客。它检查安全问题、项目约定和代码质量，在您查看 PR 之前就给您一个初步审查。

它能检测恶意贡献吗？

是的。安全代理专门寻找供应链攻击模式——混淆代码、意外的网络调用、凭据收集和后门。它标记可疑的 PR 以供人工审查。

它有助于改善贡献者体验吗？

绝对有。贡献者获得即时、有用的反馈，而不是等待数天才能得到审查。AI 解释为什么某些内容不符合项目标准，使成功贡献变得更容易。

开源项目免费吗？

diffray 为开源项目提供免费计划。请查看我们的定价页面，了解符合条件的项目和使用限制的详细信息。

适用于开源维护者

审查贡献
而不倦怠

你在业余时间维护开源。diffray 24/7 审查 PR，捕获安全问题，帮助贡献者成功 — 让你专注于重要的事情。

开源免费

维护者的困境

你想要热情好客。你也需要保护你的项目。

审查积压

当你有日常工作时 PR 堆积。贡献者等待数周。有些人放弃离开。

安全警惕

每个外部贡献都可能是供应链攻击。你不能错过一个。

守门人形象

执行标准感觉像是不友好。但降低标准会伤害项目。

倦怠

维护开源是无薪工作。审查疲劳是真实的。许多维护者退出。

你的 AI 共同维护者

diffray 处理重复性工作，让你专注于重要的代码

24/7 初步审查

每个 PR 都能获得即时、有帮助的反馈。贡献者不用等待。你审查预过滤的 PR。

贡献者在几分钟内获得反馈，而不是几天

安全筛查

AI 扫描供应链攻击模式 — 混淆代码、意外网络调用、凭证收集。

恶意 PR 在你查看之前被标记

友好的执行

AI 礼貌地解释你项目的约定。不是你拒绝别人 — 是机器人帮助他们成功。

无戏剧性地执行标准

一致的质量

凌晨 2 点和下午 2 点相同的审查质量。对首次贡献者和常客相同的反馈。

对每个人公平、无偏见的审查

对贡献者也更好

快乐的贡献者 = 健康的项目

没有 diffray

1.周一提交 PR
2.等待 5 天审查
3.收到简短的拒绝：'不遵循风格指南'
4.放弃，再也不贡献

有 diffray

1.周一提交 PR
2.5 分钟内获得有帮助的 AI 反馈
3.通过清晰的解释修复问题
4.维护者快速批准，贡献者感到受欢迎

常见问题

继续维护。
而不倦怠。

diffray 对符合条件的开源项目免费。专注于构建，而不是看管 PR。

免费开始

审查贡献而不倦怠