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Join 2,500+ teams shipping faster with AI code review
Fits Into Your Existing Workflow
2-minute setup. No config changes. Works where your team already lives.
GitHub
Native GitHub App. Auto-reviews on every PR. Comments inline. Free for public repos.
One-Click InstallGitLab
Full GitLab CI/CD integration. Self-hosted and cloud supported.
Coming Q1Bitbucket
Atlassian ecosystem integration. Works with Jira issue linking.
Coming Q2Slack
Real-time review notifications. Summarized findings in channels.
AvailableVS Code
Review findings directly in your editor. One-click fixes.
BetaJira
Auto-link findings to issues. Sprint-level code quality tracking.
Coming Q14 Daily Pain Points Every Dev Team Faces
Review Cycles Too Long, PRs Piling Up
20+ PRs waiting each week, developers waiting 2+ days for feedback, urgent fixes can't ship fast, release cycles delayed.
Senior Engineers Stuck Reviewing Code
Tech Leads spend 3 hours daily on reviews, can't focus on architecture, technical challenges, or mentoring team members.
Missing Security Flaws & Critical Bugs
SQL injection, N+1 queries, race conditions... Human reviewers get fatigued and miss issues. Production incidents follow.
Code Standards Hard to Enforce
Different reviewers, different standards. New hires don't know what "good code" looks like. Team style inconsistent.
How DeepReview Solves These 4 Problems
PRs Piling Up, Reviews Too Slow
48-hour average wait, urgent fixes stuck
15-Minute Auto Deep Reviews
Every PR auto-triggers review, detailed report in 15 minutes, no waiting for human scheduling
Senior Time Consumed by Reviews
Tech Lead spends 3 hrs/day reviewing code
AI Handles 80% of Routine Issues
Auto-check security, performance, code style. Seniors focus only on architecture and business logic
Missing Critical Issues
Human fatigue leads to missed security flaws
Full Codebase Context + ReAct Reasoning
Reads beyond diffs, traces function calls, fetches docs, reasons deeply about issues
Inconsistent Code Standards
Different reviewers, different standards
Custom Rules + Team Style Learning
Define custom review rules, AI learns your codebase patterns, consistent feedback every time
Beyond static analysis
Active AI exploration
Full Context Awareness
Unlike tools that only see diffs, our AI reads your entire PR context — files changed, commit history, project structure, and related code dependencies.
ReAct Reasoning Engine
Powered by Think → Act → Observe loops. The AI reasons about what information it needs, actively retrieves it, then iterates until fully informed.
Smart Tool Integration
Automatically reads files, searches code patterns, explores directories, and even fetches third-party library docs when needed.
Structured Reports
Get detailed reports, executive summaries, and actionable suggestion lists — each with severity levels and concrete fix recommendations.
ReAct: Reasoning + Action
Our AI doesn't just scan — it thinks, explores, and iterates
Think
AI analyzes the diff and reasons about what context is needed to fully understand the changes.
Act
Actively explores: reads related files, searches code patterns, traces function calls, fetches docs.
Observe
Incorporates findings, decides if more info is needed, then loops back or generates the final report.
See it in action
Real AI feedback across different scenarios
42 async function authenticateUser(req: Request) {
43 const { username, password } = req.body;
44
45 // Query user from database
46 const query = `SELECT * FROM users WHERE username = '${username}'`;
47 const user = await db.query(query);
48
49 for (let i = 0; i < users.length; i++) {
50 for (let j = 0; j < permissions.length; j++) {
51 if (users[i].id === permissions[j].userId) {
52 // ... 80+ more lines of validation logicDeepReview analyzes your entire codebase context — not just the diff. It traces function calls, checks dependencies, and reads documentation to provide deep insights.
Why DeepReview
Over Other Tools?
| Capability |
Recommended
DeepReview
|
Traditional Linters | Other AI Tools |
|---|---|---|---|
| Context Understanding |
Full Codebase Context
Reads related files, traces dependencies |
Single File Only
No cross-file analysis |
PR Diff Only
Misses full context |
| Reasoning Ability |
ReAct Engine
Think → Act → Observe loops |
Rule Matching
No reasoning capability |
Single-Pass
No iterative exploration |
| Issue Depth |
Deep Logic Issues
Architecture flaws, race conditions |
Surface Syntax
Formatting, naming only |
Common Issues
Misses complex problems |
| Review Speed |
15 Minutes
Deep analysis automated |
< 1 Minute
But shallow analysis |
5-10 Minutes
Varies by PR size |
| Security Detection |
Auto Detection
SQLi, XSS, auth issues |
Basic Rules
Manual config required |
Model Dependent
Inconsistent accuracy |
| Performance Issues |
N+1, Memory Leaks
Complexity analysis |
Cannot Detect
Static analysis only |
Surface Issues
Limited depth |
| Learning Curve |
Zero Config
Works out of the box |
Complex Setup
Steep learning curve |
Easy Setup
2-min install |
| Customization |
Custom Rules
Learns team style |
Config Files
Manual rule writing |
No Customization
Fixed patterns |
ReAct Reasoning Engine
Active thinking → exploration → iteration, not passive rule matching
Full Codebase Context
Reads entire project, understands dependencies and business logic
Depth + Speed Together
15 minutes to complete what takes senior engineers 2 hours
What Your Team Gets
After Using DeepReview
Time Saved
Tech Lead review time
AI handles 80% issues
Issues Found
Human review finds
AI deep analysis
Review Speed
Avg wait time
Automated review
Cost Savings
10-person team
40% time cost saved
Simple, transparent pricing
Start free, upgrade when you need more
Free
Perfect for open source
- ✓ 1 public repository
- ✓ Full AI review capability
- ✓ Security + performance checks
- ✓ Community support
- ✕ Private repos
No credit card required
Pro
For growing teams
- ✓ Unlimited repositories
- ✓ Private repos included
- ✓ Full codebase context analysis
- ✓ Custom review rules
- ✓ Team analytics dashboard
- ✓ Priority support (24h SLA)
Saves ~$3,000/month for a 10-person team
Enterprise
For security-first orgs
- ✓ Everything in Pro
- ✓ SSO / SAML authentication
- ✓ Audit logs & compliance
- ✓ Custom AI model fine-tuning
- ✓ Self-hosted option
- ✓ Dedicated success manager
SOC 2 & GDPR compliant
Common Questions
Is my code secure? Where does it go?
Your code never leaves your infrastructure for review. DeepReview uses a read-only GitHub App that processes code in isolated, ephemeral environments. We're SOC 2 Type II certified and GDPR compliant. Enterprise customers can opt for self-hosted deployment.
How is this different from GitHub Copilot or ChatGPT?
Unlike chat-based tools that only see what you paste, DeepReview automatically reads your entire codebase context — imports, dependencies, related files. It uses ReAct reasoning to actively explore your code, not just pattern-match on diffs.
Will AI reviews replace human reviewers?
No — DeepReview handles 80% of routine issues (security, performance, style) so your senior engineers can focus on architecture, business logic, and mentoring. It's a force multiplier, not a replacement.
What languages and frameworks do you support?
We support all major languages: TypeScript/JavaScript, Python, Go, Java, Rust, C/C++, Ruby, PHP, and more. Framework-specific patterns (React, Django, Rails, Spring) are understood contextually.
How accurate is the AI? Does it produce false positives?
Our precision rate is 94%+ thanks to full codebase context. Unlike simple linters, we understand intent and avoid flagging intentional patterns. You can also train custom rules to match your team's standards.
Can I try it on a private repo before buying?
Yes! Pro plan includes a 14-day free trial with full features on unlimited private repos. No credit card required to start. Most teams see value within the first 3 PRs.
Install in 2 Minutes, Experience AI Deep Review Now
1 repo free forever · No credit card · Cancel anytime
Install on GitHub FreeTrusted by 2500+ teams
SQL Injection Vulnerability
This query is vulnerable to SQL injection. Use parameterized queries instead:
O(n²) Complexity Detected
This nested loop could be slow with large datasets. Consider using a hash map for O(n) lookup.
Function Too Long (87 lines)
Consider extracting validation logic into a separate function to improve readability and testability.