Code reviews are an important part of your job for maintaining high-quality software, but as your projects grow, managing them can become more complex. If you’re relying on tools like Graphite, you may find them lacking as your codebase expands.

The global market for code review tools is expected to reach USD 5.3 billion by 2032. As the market grows, you need tools that offer full-repository context, real-time feedback, and better scalability.
In this blog, we’ll explore the top Graphite alternatives that can enhance your code review process. So let’s begin!

Key Takeaways

• AI code review tools automate feedback and fix common issues instantly.

• While Graphite is suitable for smaller teams, it lacks scalability and deep context for larger codebases.

• Several Graphite alternative tools offer full-repository context, real-time feedback, and strong security, making it ideal for you.

• When selecting a tool, consider integration, customization, and security features.

• Tools like Entelligence AI provide real-time insights and deep context, optimizing code review cycles and boosting productivity without compromising quality.

What Is Graphite?

Graphite is an open-source code review tool primarily used for monitoring and metrics. It helps you assess code quality, but its use has limitations, especially for modern, large-scale developments. Its key features focus on basic pull request management and metric tracking.

While Graphite works well for small to medium-sized codebases, it becomes less effective when scaled, especially with regard to deep code analysis.

Why Graphite May Not Be Enough:

• Limited to GitHub: Graphite's functionality is currently restricted to GitHub, making it less versatile for teams that use other platforms like GitLab or Bitbucket.

• Lacks Deep Cross-File Context: The tool struggles to provide a full understanding across large codebases, which can hinder comprehensive code reviews.

• No Conversational AI for Query Resolution: Unlike more modern tools, Graphite doesn't include an interactive, AI-driven query system to help you understand feedback.

• Pricing & Feature Scalability Issues: As your workload and your teams grow, Graphite’s pricing model and feature set may not scale well with increased code complexity and user volume.

To address these limitations, you may need tools that provide comprehensive code analysis and better context for larger codebases.

Also Read: What is a Secure Code Review? Process and Best Practices

Key Criteria for Evaluating AI Code Review Tools

Before diving into specific tools, you must establish the criteria that matter most when selecting an AI code review tool:

1. Contextual Awareness

Does the tool understand the full repository or just isolated changes? A tool that indexes the entire codebase offers better insights and a more accurate review process.

2. Customizability

The tool's adaptability to your coding guidelines and workflows is important. The more customizable the tool, the better it fits into your unique development practices.

3. Speed & Efficiency

The tool you choose must quickly identify issues that are important for maintaining development flow. This is extremely important when you are working with rapid release cycles. Speed ensures that problems are caught early, preventing delays.

4. Security Compliance

Does the tool follow best practices for security, such as SOC 2 compliance or on-premises deployment? Security should always be a top priority when selecting a code review tool, especially for large organizations.

5. Cost-Effectiveness

How does the tool’s pricing model align with your budget and needs? Consider whether the tool charges per user, per file changed, or based on the amount of code processed.

6. Integration with Existing Tools

The tool should integrate seamlessly with platforms you already use, such as GitHub, GitLab, Bitbucket, CI/CD pipelines, and IDEs. This ensures a smooth workflow without disrupting existing processes.

7. Real-time Feedback

The tool should also provide immediate feedback during coding to catch issues as soon as they arise. Real-time feedback helps identify and fix problems early, preventing bugs from reaching production.

Also Read: Understanding Velocity in Agile Software Development

Top Graphite Alternatives: A Deep Dive

The top alternatives to Graphite offer AI-powered code reviews with enhanced context, scalability, and integration features. Let’s check out a few of these alternatives now!

1. Entelligence AI

Entelligence AI is an AI-powered engineering intelligence platform designed to automate code reviews, enhance team productivity, and provide deep insights into codebases.

Best For: You, if you are looking to automate code reviews and gain deeper insights into your codebases.

Key Features:

• Deep Codebase Understanding: Analyzes entire codebases to provide comprehensive insights.

• Automated Code Reviews: Uses AI to automate code reviews, saving time and reducing errors.

• Smart Comments: Provides intelligent comments and suggestions during code reviews.

• Performance Insights: Tracks team performance and code quality metrics.

• Self-Updating Documentation: Automatically generates and updates documentation as code changes.

Pricing: 14 Days Free Trial; paid plans starting at $40/Month.

Strengths: AI-driven code reviews, deep codebase analysis, and seamless integration with development workflows.

Limitations: Pricing may be expensive for small teams; limited features in the free plan

2. Bito AI Code Review Agent

Bito AI provides full-repository context, real-time feedback, and customizable AI-driven code reviews, making it ideal for a review process with deep insights.

Best For: You and your team, if you are looking for full-repository context, real-time feedback, and customizable AI-driven code reviews.

Key Features:

• Full repository indexing: Provides context-aware reviews, catching hidden side effects and suggesting secure patterns.

• One-click fixes: Automatically handles mechanical changes and common bugs.

• Security, performance, and style checks: Embedded security with SOC 2 compliance.

• Real-time analytics: Tracks trends and performance across projects.

• Chat with AI: Clarifies complex issues and provides instant answers.

Pricing: Free for basic features; paid plans starting at $15/user/month.

Strengths: High-level customization, multi-host support (GitHub, GitLab, Bitbucket), and an easy-to-integrate setup.

Limitations: Pricing may be expensive for small teams, limited free-tier features, and non-Git platform integrations require additional setup.

3. Greptile

Greptile is ideal for large teams managing complex codebases. It offers deep cross-file analysis, providing valuable insights and fixes across multiple files. The tool is perfect for you and your team working with polyglot architectures.

Best For: You and your large teams with complex codebases needing deep, cross-file analysis.

Key Features:

• Cross-file code analysis: Uses a language-agnostic graph to understand relationships across multiple files.

• Automatic quick-fix patches: Provide inline suggestions for fixing issues.

• Support for 30+ languages: Ideal for polyglot teams working with different languages.

• On-prem deployment: Provides additional security options for enterprise needs.

• SOC 2 compliant: Ensures that data privacy and security standards are met.

Pricing: Plans start from $30/active dev/month.

Strengths: Polyglot support, advanced AI-driven fixes, and scalable for large codebases.

Limitations: Pricing may be expensive for small teams, limited free-tier features, and non-Git platform integrations require additional setup.

4. CodeRabbit

CodeRabbit is designed for developers like you who require quick, contextual feedback on pull requests. It offers real-time code-graph context and natural language summaries, making it ideal for handling large and complex PRs efficiently.

Best For: You and your team needing quick checks and contextual feedback on PRs, especially when working with large, complex PRs.

Key Features:

• Code-graph context: Precise feedback on complex code changes, even across large codebases.

• Natural language PR summaries: Easily digestible feedback that aligns with your coding standards.

• One-click fixes: Quickly address common issues, saving time for you.

• GitHub and GitLab integration: Seamless integration with existing workflows.

Pricing: Free for basic summaries; paid plans starting at $15/user/month.

Strengths: Rapid PR processing with deep context for multi-module changes.

Limitations: Pricing may be expensive for small teams, limited free-tier features, and non-Git platform integrations require additional setup.

5. Qodo Merge

Qodo Merge is perfect for open-source projects, providing a customizable, budget-friendly AI code review solution that automates PR descriptions and ensures compliance.

Best For: Open-source projects and small teams needing a budget-friendly, customizable tool.

Key Features:

• AI-generated PR descriptions: Automatically create structured PR descriptions to ensure compliance and clarity.

• Guided PR reviews: Offers repository-specific learning for better accuracy.

• Compliance checks: Ensures ticket references and issue linking are properly managed.

• Open-source core: Offers transparency and the ability to self-host.

Pricing: Free for individuals; team plans start at $30/user/month.

Strengths: Open-source, repository-specific learning, and easy self-hosting options.

Limitations: Pricing may be expensive for large teams, limited advanced features in the free-tier, and some integrations may require additional configuration.

6. Trag

Trag is ideal for you if you are looking to enforce customized coding rules, with the flexibility to define rules in plain English and instant feedback on pull requests.

Best For: You and your team seeking customized rule enforcement based on existing coding standards.

Key Features:

• Custom rule enforcement: Uses plain English to define coding patterns (e.g., “never log user passwords”).

• IDE and PR integration: Provides instant feedback on pull requests and code quality.

• Works with any language: Universally applicable across various programming languages.

• Self-hosting options: Provides additional flexibility for enterprises.

Pricing: Free for basic summaries; team plans start at $20 per engineer/month.

Strengths: Simple rule customization and fast, real-time feedback.

Limitations: Pricing may be expensive for small teams, limited free-tier features, and self-hosting requires additional setup and maintenance.

 7. SonarQube

SonarQube is a comprehensive static code analysis tool that helps you detect code quality issues, security vulnerabilities, and maintainability concerns across various programming languages.

Best For: You and your team, if you are seeking robust code quality and security analysis across multiple languages.

Key Features:

• Multi-language support: Analyzes over 30 programming languages, including Java, C#, JavaScript, Python, and more.

• Quality Gates: Enforces quality standards by setting thresholds for code quality metrics.

• Security Vulnerability Detection: Identifies potential security issues and vulnerabilities in the codebase.

• CI/CD Integration: Seamlessly integrates with continuous integration and continuous deployment pipelines.

• IDE Integration: Provides plugins for popular IDEs like IntelliJ IDEA, Visual Studio, and Eclipse.

Pricing: Developer plan starts at $720 annually. 

Strengths: Extensive language support, robust security analysis, and seamless integration with CI/CD pipelines.

Limitations: Advanced features require paid editions; they may require additional configuration for optimal performance.

A Comparative Analysis of Alternatives

To help you make a more informed decision, we’ve put together a comparison of the top Graphite alternatives based on the key criteria discussed. This will allow you to evaluate each tool's features, strengths, and limitations in relation to your needs:

Overcoming the Top Challenges When Switching to a New AI Code Review Tool

When considering a switch to AI-driven code review tools, you can expect challenges such as workflow disruption, security issues, and resistance to change. Here’s how to mitigate those concerns and ensure a smooth transition.

Concern 1: "Switching to a new tool will disrupt our workflow."

Adopting a new tool often means adjusting to unfamiliar workflows, which can lead to delays, confusion, and resistance from your team members. The potential disruption to established processes can be a daunting prospect for many.

Solution:

Start with a free trial to assess how the new tool integrates with your current system. Use it on a few real pull requests to test the tool’s effectiveness without committing to a full transition. This will help you identify potential bottlenecks and areas for improvement before going all in.

Concern 2: "Do I need to worry about security?"

Security concerns are heightened when introducing AI tools into your development process. You need to ensure that sensitive data, especially proprietary code, remains protected and that the tool adheres to compliance standards.

Solution:

Look for tools that offer SOC 2 compliance, on-premises hosting options, and clear data privacy policies. These features ensure that the AI tool operates securely within your organization’s data protection framework. Transparent security practices are essential to prevent data breaches and maintain regulatory compliance.

Concern 3: "Graphite is good enough for us, why change?"

Many individuals rely on Graphite because it provides basic code review functionality. The fear of change can make you hesitate to switch to a new tool, especially if you believe Graphite is meeting your current needs.

Solution:

Graphite might work for basic code reviews, but tools like Entelligence AI and Greptile provide deeper insights, scalability, and flexibility to manage complex codebases.

Also Read: Sprint Review Guide: Definition, Goals, and Tips

How to Make Your Final Decision?

When selecting an AI code review tool, consider how well it aligns with your workflow, goals, and security requirements. Additionally, consider the following factors:

• Size and Complexity of Your Codebase: Choose a tool that can handle the scale of your codebase and provides deep context analysis.

• Integration Needs: Ensure that the tool integrates seamlessly with your existing GitHub, GitLab, Bitbucket, and CI/CD pipelines.

• Security and Compliance: Select a tool that adheres to industry-standard security practices.

• Pricing: Consider the tool’s pricing model and ensure it aligns with your needs.

• Trial Period: Many tools offer free trials. Test them with real pull requests to ensure the tool fits your workflow.

Conclusion

Choosing the right AI code review tool is essential for improving your efficiency and code quality. Each tool offers unique features to help streamline your development process, whether it’s real-time feedback, deeper code insights, or custom rules.

Entelligence AI is the perfect solution for you if you are looking to enhance your code reviews. It provides full-context reviews, real-time feedback, and built-in security checks, all while fitting seamlessly into your existing workflow. With easy integration and customizable options, it helps you and your team work faster and smarter.

Ready to improve your code reviews? Start a free trial of Entelligence AI today and see how it can make your development process more efficient.

FAQs:

Q. What is the best AI code review tool for large teams?

For large teams, Entelligence AI stands out due to its ability to analyze entire codebases and provide cross-file context. The tool ensures comprehensive code reviews that scale with your team size and complexity.

Q. Can AI code review tools be integrated with GitLab?

Yes, many AI code review tools like Bito AI and Entelligence AI integrate seamlessly with GitLab. This enables efficient and automated code reviews across repositories while ensuring smooth workflows.

Q. Is security a concern with AI code review tools?

Yes, AI code review tools offer strong security measures, such as SOC 2 compliance, to ensure your code is protected and never stored for model training. These tools also have the ability to provide enterprise-grade security throughout your development process.

Q. Are AI-driven code review tools suitable for open-source projects?

Yes, AI-powered tools are open-source-friendly, offering robust features with a customizable, budget-conscious pricing model, making them suitable for working on open-source projects.