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.

How long does a code review take with diffray?

diffray provides comprehensive code reviews quickly. The multi-agent system works in parallel to analyze your code efficiently while maintaining thorough analysis.

Is diffray free for open source projects?

Yes, diffray is free forever for open source projects. We support the open source community with full access to our multi-agent code review platform.

AI Code Review That Actually Thinks™

Multi-agent intelligence. Not single-model guessing.

While other tools fire a single AI and hope for the best, diffray deploys a coordinated team of specialized agents.

Setup in a few clicksFree for open sourceNo credit card

Context Aware

Understands your entire codebase

Real Bugs

Not style nitpicks

Culture as Code

Make your engineering standards a rule

Code never stored·No AI training·SOC 2 Infra

87%

Fewer False Positives

More Real Bugs Caught

98%

Developer Action Rate

Zero

Duplicate Comments

*Based on internal testing

Are You Ignoring Your AI Code Reviewer?

You're not alone. Here's what developers told us about traditional AI review tools:

😤

Too Much Noise

"18 comments per PR. I read maybe 2. Most are just style nitpicks I don't care about."

— Mid-level dev, 50-person startup

😬

Misses Real Issues

"It suggests renaming `e` to `error` but completely misses SQL injection vulnerabilities. Every. Single. Time."

— Senior engineer, fintech

😅

Zero Context

"Suggests refactoring patterns we already decided against 3 months ago. Has no memory of our decisions."

— Tech lead, Series B company

The problem isn't AI.

The problem is single-agent AI.

Speculation vs Investigation

See how diffray handles a real scenario: a function signature change in your PR

Single LLM

AI Response:

"This changes the return type. Make sure callers are updated."

Generic advice

No specific locations

Leaves work to you

diffray Agent

Agent Investigation:

1. Searched for all usages of getUserData()

2. Found 3 call sites with type mismatches

3. Checked test coverage — 2 tests need updates

4. Impact: api/users.ts:47, hooks/useUser.ts:23

Concrete file paths and line numbers

Verified against actual codebase

Actionable findings you can fix now

The difference? Investigation, not speculation.

How to Start

See how easy it is to set up diffray and get your first multi-agent code review

Sign In with GitHub

Connect your GitHub account in one click. No complex setup required — just authorize and you're ready to go.

Install the GitHub App

Add diffray to your organization or personal repositories. Choose which repos to enable — you have full control.

Configure Your Repository

Customize review settings, enable specific agents, and set up your team's coding guidelines.

Get Intelligent Reviews

Open a pull request and watch the magic happen. Receive focused, actionable feedback within minutes.

Real Issues. Real PRs.

Not mock examples — actual findings from production code reviews

diffray detecting duplicate library - moment-timezone when dayjs already exists

Understands Your Project Context

Detected moment-timezone being added when the project already uses dayjs. A linter can't catch this — it requires understanding the existing codebase.

diffray detecting non-transactional Stripe and Prisma updates

Catches Data Consistency Bugs

Found Stripe and database updates that aren't atomic. If one fails, payment data becomes inconsistent. Critical for fintech reliability.

diffray detecting race condition in concurrent promo code application

Finds Concurrency Issues

Concurrent requests can read stale data and overwrite each other. Suggests Prisma transactions with optimistic locking.

diffray detecting missing test coverage for new component

Catches Meaningless Tests

Found tests that exist but don't actually test the component. The test file looks complete, but the assertions are empty.

Real findings from cal.com open-source code reviews

How diffray's Multi-Agent System Works

Multiple specialized stages working together to find what actually matters

Traditional Tools

Single-Agent Approach

One LLM tries to do everything

Applies ALL rules to ALL files

No memory of past decisions

Can't detect duplicate issues

No codebase context

Shows uncertain findings as fact

Result: 18 comments, 16 ignored

Diffray Multi-Agent

Coordinated Intelligence

Specialized agents for each domain

Dynamic guideline selection

Learns your team's patterns

Issue deduplication

Full codebase awareness

Confidence scoring filters noise

Result: 3 comments, 3 fixed

Teams That Switched to diffray

"We reduced PR review time from 45 minutes to 12 minutes per week. The team actually trusts AI feedback now."

— Engineering Manager, 35-person SaaS startup

"CodeRabbit was giving us 20+ comments per PR. We ignored most. diffray gives us 3-4 that are always spot-on."

— Tech Lead, Series B fintech

"The codebase-aware analysis is a game-changer. It caught a duplicate implementation that would've cost us 2 days."

— CTO, AI startup (20 engineers)

Stop Ignoring AI Code Reviews

Try diffray free for 14 days. No credit card. Setup in a few clicks.

Start Free Trial Book a Demo

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