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.

安全优先代码审查

AI + 安全工具。
零盲区。

diffray 结合行业领先的安全扫描器（TruffleHog、Semgrep）与 AI 解释。在泄露的密钥和漏洞进入生产之前捕获它们。

为什么仅靠 AI 不够

AI 模型擅长推理，但专业工具能捕获 AI 遗漏的问题

仅 AI

上下文感知

模式推理

可能遗漏边缘情况

可能有假阴性

仅工具

精确检测

低假阴性

高假阳性

无上下文理解

AI + 工具（diffray）

更高检测率

更低假阳性

更好上下文

可操作修复

工具检测. AI 验证和解释. 您得到可操作的结果.

密钥检测

TruffleHog 集成

行业领先的密钥扫描器，在泄露的凭证、API 密钥和敏感数据进入仓库之前检测它们。

检测内容：

AWS 访问密钥

GitHub 令牌

私钥（RSA、SSH）

数据库连接

700+ API 密钥格式

JWT 令牌

云凭证

会话密钥

Learn more about TruffleHog integration

TruffleHog 工作原理：

正则模式

匹配已知凭证格式

熵分析

检测看起来像密钥的高熵字符串

验证

尝试验证检测到的密钥是否活跃

AI 增强

验证 — 确认它是真实凭证，而非假阳性
评估严重性 — 测试密钥 vs 生产凭证
提供上下文 — 它在哪里使用以及潜在影响
建议修复 — 如何轮换和保护

Semgrep 检测内容：

注入漏洞

SQL 注入、命令注入、XSS

认证问题

硬编码密码、弱加密

不安全配置

调试模式、CORS 配置错误

代码质量

空指针、资源泄漏

支持 30+ 种语言：

TypeScriptJavaScriptPythonGoJavaKotlinRubyPHPC/C++RustSwift

静态分析

Semgrep 集成

快速、开源的静态分析，使用语义模式匹配发现 Bug 和安全漏洞。与正则工具不同，Semgrep 理解代码结构。

AI 增强

验证相关性 — 检查发现是否适用于您的代码
减少噪音 — 根据上下文过滤假阳性
优先级排序 — 按实际风险排名
解释漏洞 — 如何被利用
提供修复 — 具体代码更改

Learn more about Semgrep integration

安全流水线

安全工具如何集成到每次代码审查中

检测到 PR 更改

新代码推送到 Pull Request

TruffleHog 扫描

密钥扫描器仅检查新更改

Semgrep 分析

静态分析运行在修改的代码上

AI 接收上下文

工具输出 + 代码上下文发送给 AI

AI 验证和过滤

移除假阳性，丰富发现

可操作报告

带修复建议的清晰、优先级排序的问题

差异扫描

仅分析 PR 中的更改——快速扫描，无来自现有问题的噪音

AI 验证

每个发现都由 AI 审查——过滤假阳性，添加上下文

统一报告

所有发现在一个有组织的评论中，格式一致

在生产之前捕获
安全问题

泄露的密钥和漏洞无处可逃。立即开始保护您的代码。

开始免费试用阅读安全文档

包含 TruffleHog + Semgrep

无需配置

每个 PR 都运行

AI + 安全工具。零盲区。

为什么仅靠 AI 不够

TruffleHog 集成

检测内容：

TruffleHog 工作原理：

AI 增强

Semgrep 检测内容：

支持 30+ 种语言：

Semgrep 集成

AI 增强

安全流水线

差异扫描

AI 验证

统一报告

在生产之前捕获安全问题

AI + 安全工具。
零盲区。

在生产之前捕获
安全问题