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 如何帮助微服务？

diffray 理解服务边界和 API 契约。当 PR 更改服务的公共 API 时，它会标记对下游消费者的潜在破坏性更改，并建议向后兼容的替代方案。

它能检测 API 破坏性更改吗？

是的。它分析 API 定义（OpenAPI、GraphQL 模式、protobuf）并捕获删除、类型更改、添加必需字段——任何可能破坏消费者的内容。

它如何执行服务边界？

您定义哪些服务可以通信以及如何通信。diffray 标记服务之间的直接数据库访问、不当耦合和边界违规。

它与我们的 API 版本控制策略兼容吗？

diffray 适应您的版本控制方法——URL 版本控制、Header 版本控制或语义版本控制。它确保更改遵守您的版本控制策略。

适用于分布式架构

微服务
尽在掌控

API 会变化。消费者会中断。契约会漂移。diffray 通过在 PR 阶段捕获破坏性更改来维护分布式系统的秩序。

开始免费试用

分布式困境

服务越多，出问题的方式越多

破坏性更改

改变一个服务的 API 响应，破坏 5 个消费者。没人知道他们依赖那个字段。

边界违规

服务绕过 API 直接访问彼此的数据库。'这样更快' 变成技术债务。

契约漂移

API 文档说的是一回事。代码做的是另一回事。消费者依赖未记录的行为。

级联故障

缺少错误处理、没有熔断器、重试风暴。一个服务宕机，所有服务宕机。

无需会议的治理

AI 在每个 PR 上执行您的架构决策

契约验证

AI 分析 OpenAPI 规范、GraphQL 模式和 protobuf。捕获删除、类型更改和破坏性修改。

"从 UserResponse 中删除 'email' 将破坏 OrderService 和 NotificationService。"

边界执行

定义哪些服务可以通信以及如何通信。标记直接数据库访问和不适当的耦合。

"PaymentService 不应从 UserService 内部导入。请使用公共 API。"

弹性模式

确保服务间调用中有适当的错误处理、超时、重试和熔断器。

"此 HTTP 调用没有超时。添加超时以防止级联故障。"

版本合规

执行您的 API 版本策略。确保更改遵守向后兼容规则。

"检测到破坏性更改。要么增加 API 版本，要么使此更改具有增量性。"

破坏性更改检测

在发布前就知道

删除字段破坏性

更改字段类型破坏性

添加必填字段破坏性

添加可选字段安全

添加新端点安全

弃用字段警告

常见问题

分布式系统。
集中质量控制。

让您的微服务保持同步。