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.

What is the main difference between diffray and SonarQube?

According to internal testing data, diffray uses multi-agent AI architecture where 10+ specialized agents (Security Agent, Performance Agent, Architecture Agent, etc.) work together and cross-validate findings. SonarQube uses a single-agent approach which typically leads to 70%+ false positive rates. diffray's multi-agent cross-validation reduces false positives by 87% and catches 3x more real bugs.

Is diffray better than SonarQube?

Based on customer metrics, diffray's multi-agent approach outperforms SonarQube in key areas: 87% fewer false positives, 98% developer action rate (vs 15-20% industry average), 3x more real bugs detected, and zero duplicate comments guaranteed. Teams report reducing PR review time by 73% after switching from single-agent tools to diffray.

Can I migrate from SonarQube to diffray?

Yes. diffray integrates with GitHub in under 2 minutes through a GitHub App. You can run both tools in parallel during migration, then disable SonarQube once you're satisfied with diffray's reviews. No configuration required - diffray automatically adapts to your codebase and team patterns.

How much does diffray cost compared to SonarQube?

diffray is free forever for open source projects with unlimited reviews. For private repositories, diffray offers simple per-developer pricing: Solo $10/month (1 dev), Team $9/dev/month (3-10 devs), Growth $79/month flat (11+ devs). All plans include unlimited reviews and a 14-day free trial with no credit card required.

What security features does diffray have vs SonarQube?

diffray's Security Agent specializes in detecting OWASP Top 10 vulnerabilities, SQL injection, XSS, authentication flaws, and secrets exposure. Unlike SonarQube's generalist approach, diffray's specialized Security Agent maintains focused context on security patterns, resulting in fewer false positives and more accurate vulnerability detection.

Does diffray support the same languages as SonarQube?

diffray supports all major programming languages including TypeScript, JavaScript, Python, Go, Rust, Java, C#, Ruby, PHP, and 40+ more. The multi-agent system is language-agnostic and adapts analysis to language-specific patterns and best practices automatically.

Why do developers prefer diffray over SonarQube?

Developers report that 98% of diffray's comments are actionable, compared to 15-20% industry average for single-agent tools like SonarQube. This is because diffray's agents cross-validate findings before posting, eliminating noise and surfacing only real issues with confidence scores. Zero duplicate comments means developers focus on fixing bugs, not filtering noise.

Comparison

diffray vs SonarQube

SonarQube est un outil d'analyse statique eprouve avec plus de 10 ans d'histoire. diffray represente la nouvelle generation : revue de code multi-agent par IA qui comprend le contexte.

87%

Fewer False Positives

vs single-agent tools

More Bugs Detected

with multi-agent review

98%

Developer Action Rate

on diffray comments

The Code Review Problem

15-20%

Industry avg action rate on AI comments

2-4 hrs

Wasted per week on false positives

60%

Of AI reviews are ignored by devs

$150K+

Annual cost of review inefficiency

Feature Comparison

See how diffray and SonarQube compare across key features

Feature

diffray

SonarQube

Multi-Agent Architecture

Multiple specialized AI agents working together

Pull Request Review

Automated review on every PR

IDE Integration

Real-time feedback in code editor

Self-Hosted Option

On-premise deployment available

Security Scanning

Vulnerability and secrets detection

Custom Rules

Define your own review rules

Language Support

Number of programming languages

All major

30+

CI/CD Integration

Integrates with CI/CD pipelines

Key Differentiator

Multi-Agent vs Single-Agent Architecture

SonarQube uses a single AI model that tries to do everything. This leads to context dilution, hallucinations, and 60-80% false positive rates that waste developer time.

diffray deploys 11 specialized agents that work together: Security Agent, Performance Agent, Architecture Agent, and more. Each agent is expert in its domain and cross-validates findings — reducing review noise by 87%.

Security Agent

OWASP, secrets, auth

Performance Agent

N+1, memory, speed

Architecture Agent

Patterns, coupling

Quality Agent

Bugs, edge cases

SonarQube (Single-Agent)

High false positive rate (often 70%+)
No AI-powered analysis
Complex setup and maintenance
Noisy alerts overwhelm developers

diffray (Multi-Agent)

87% fewer false positives — specialized agents reduce noise
3x more real bugs caught with cross-validation
98% action rate (vs 15-20% industry average)
< 5 min review time per PR
80% time saved on code review

Pricing Comparison

See how much you can save with diffray

Plan

diffray

SonarQube

Open Source

Public repos

Free Forever

Community Edition (open source)

Team (3-10 devs)

The Verdict

Choisissez diffray pour des revues intelligentes avec moins de bruit. Choisissez SonarQube pour du SAST on-premise traditionnel.

Choose diffray if:

Equipes fatiguees de filtrer le bruit de SonarQube

Choose SonarQube if:

Equipes enterprise avec infrastructure SonarQube existante

Why teams switch to diffray:

L'IA comprend l'intention, les regles ne correspondent qu'aux patterns

Other Comparisons

vs coderabbit

vs github copilot

vs sourcery

vs codacy

vs qodo

Learn More About diffray

Discover why diffray stands out from SonarQube

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