Best Web-Based Code Review Tools of 2026 - Page 2

Step away from the hassle of writing essays, as Squire effortlessly generates pull request descriptions on your behalf. This tool ensures your team remains aligned through concise descriptions and comprehensive changelogs. With an efficient workflow, Squire engages your team in reviewing PRs while providing them with complete context from your codebase. It excels at identifying various issues, including significant breaking changes, security vulnerabilities, and even minor typographical errors. By enhancing code quality, Squire facilitates a smoother transition of your PRs into production. As a context-sensitive agent, Squire collaborates with you to craft descriptions, evaluate PRs, and adapt to your preferred review style. It not only understands your team's reviewing habits but also customizes its approach through explicit settings and by learning from your team's interactions. Furthermore, it helps to delineate and organize ownership and accountability throughout your entire engineering infrastructure, while ensuring compliance by implementing and upholding regulations on your engineering elements. Ultimately, Squire is your partner in achieving a more streamlined and efficient development process.

Access immediate code evaluations from qualified engineers, augmented by AI technology. Each time you initiate a pull request, you can seamlessly integrate senior engineers into your workflow. Accelerate the delivery of superior, secure code with the support of AI-driven code assessments. Whether your development team comprises 5 or 5,000 members, PullRequest will elevate your code review system and tailor it to suit your requirements. Our expert reviewers assist in identifying security threats, uncovering concealed bugs, and addressing performance challenges prior to deployment. This entire process is integrated into your current tools for maximum efficiency. Our seasoned reviewers, bolstered by AI analysis, can target critical security vulnerabilities effectively. We employ advanced static analysis that incorporates both open-source resources and proprietary AI, providing reviewers with enhanced insights. Allow your senior personnel to focus on strategic initiatives while making substantial strides in resolving issues and refining code, even as other team members continue to develop. With this innovative approach, your team can maintain productivity while ensuring code quality.

DeepCode AI serves as the foundation of Snyk code, making it the quickest and most precise Static Application Security Testing (SAST) solution available. By harnessing DeepCode AI within the Snyk platform, which leverages various AI models and is honed using data focused on security, Snyk provides users with the advantages of artificial intelligence while mitigating potential downsides. Supporting 11 programming languages, DeepCode AI is crafted to identify and remediate vulnerabilities, as well as address technical debt effectively. This innovative AI also facilitates Snyk's one-click security solutions and extensive application coverage, empowering developers to build swiftly while maintaining robust security measures. Developed and continuously improved by expert researchers, DeepCode AI relies on millions of open-source projects for its training, ensuring no customer data is utilized. Ultimately, DeepCode AI employs a hybrid strategy with multiple models and specialized training sets, all aimed at enhancing application security. This commitment to innovation ensures that developers can confidently deploy applications without compromising safety.

Metabob identifies, interprets, and resolves coding issues arising from both human and AI sources. By leveraging advanced graph neural networks for detection and large language models for explanation and resolution, Metabob merges the strengths of both technologies. The graph neural networks analyze and categorize problematic code while maintaining contextual awareness. This problematic code, enriched with relevant context, is then stored in Metabob's backend system. The information retained in the backend is subsequently utilized by an integrated large language model. This model produces tailored explanations and solutions based on the context provided. Metabob's AI has been trained on an extensive dataset of millions of bug fixes executed by skilled developers. With a deep understanding of code logic and context, Metabob is capable of identifying intricate issues that span multiple codebases, automatically creating suitable fixes. The AI code review feature of Metabob can uncover hundreds of logical issues, including race conditions and unhandled edge cases, which often go unnoticed by conventional static analysis tools. This innovative approach not only enhances debugging efficiency but also elevates the overall quality of the codebase.

Optimize your Git commands and effortlessly manage stacked pull requests directly from your terminal. You can visually create and modify stacked PRs without leaving your integrated development environment, ensuring a seamless workflow. Keep all of your PRs and review requests organized in a single inbox for easy tracking. Receive immediate, actionable insights on each pull request thanks to Graphite's AI, which is aware of the codebase context. Prevent merge conflicts and maintain a clean main branch, regardless of whether your team consists of 10 or 10,000 members. Boost your team's productivity with robust, real-time metrics for developers. Experience a faster, more intuitive Git interface that simplifies the stacking process. Use the command 'gt create' again to add another branch atop your existing changes, eliminating the need to wait for merges into the main branch. Your local stack will automatically sync with remote updates, and you can easily tidy up outdated branches using 'gt sync'. Modify changes across your entire stack with the 'gt modify' command, while Graphite takes care of all the recursive rebasing tasks for you. With 'gt submit', you can create or update PRs for each branch within your stack, ensuring a streamlined and efficient development process. This innovative approach to Git management empowers developers to focus more on coding rather than on handling complex version control issues.

Astronuts is an innovative code review platform powered by AI, aimed at enhancing the development workflow by automating the processes of code reviews and bug corrections. Developers can easily kick off code evaluations with a straightforward command, receiving intelligent, line-by-line feedback and suggestions for automatic fixes. This platform boasts various features, including summaries for pull requests, metrics on code quality, and detailed change logs, all presented within an intuitive interface. By integrating effortlessly with GitHub, Astronuts empowers teams to keep track of pull request sizes and monitor code health metrics, significantly cutting down on the time spent on code reviews while also decreasing the occurrence of bugs. Additionally, the platform facilitates real-time chat for addressing code-related inquiries, offers customizable settings for behavior, and establishes rules to uphold coding standards. Supporting a range of programming languages and build systems, Astronuts is well-equipped to serve various development environments effectively. Moreover, the platform provides a free trial along with $5 in credits, allowing teams to test its features without any upfront investment, making it an attractive option for organizations looking to enhance their coding practices. Overall, Astronuts aims to transform the way development teams approach code quality and efficiency.

Entelligence AI serves as a powerful engineering intelligence platform that leverages artificial intelligence to optimize development processes, foster teamwork, and elevate productivity throughout the software development lifecycle. By utilizing intelligent agents, it automates the tasks of code reviews and pull request (PR) assessments, significantly reducing review durations, identifying bugs at early stages, and enhancing overall engineering efficiency. The platform’s Deep Review functionality analyzes complex issues across multiple files through comprehensive context analysis of the entire codebase, delivering insightful PR summaries, smart comments, and prompt fixes. In addition, Entelligence AI provides valuable performance metrics that monitor team dynamics, sprint advancements, and code quality, offering real-time insights into individual engineer output, review thoroughness, and sprint evaluations. Furthermore, its innovative self-updating documentation capability translates code into easily understandable documentation, automatically refreshing the content with every new commit, ensuring that developers have access to the most current information. This comprehensive set of features positions Entelligence AI as an indispensable tool for modern software development teams aiming for efficiency and clarity.

Macroscope serves as an AI-driven analytics and visibility platform tailored for engineering and product teams, linking seamlessly with a company's codebase, commit history, issue tracking systems like Linear or Jira, and Slack to automatically produce insights regarding the development process. By employing code-walking techniques on the Abstract Syntax Tree (AST), it comprehensively evaluates changes to grasp the relationships and dependencies within the code, ultimately generating summaries for commits, pull requests (which include automated reviews and descriptions), shifts in the overall codebase, and patterns in feature development or bug resolution. Stakeholders can inquire about progress using natural language queries, such as “What did we ship last week?”, gain insights into the allocation of engineering resources, identify significant bugs with a reduced rate of false positives, and monitor productivity and status without the need to scrutinize every single difference in the code. This tool enhances the efficiency of communication among team members by centralizing information and fostering a clearer understanding of project statuses.

The Code Registry is an innovative platform that harnesses AI for code intelligence and analysis, providing companies and non-technical users with complete insight into their software codebase, regardless of their coding experience. By linking your code repository—such as GitHub, GitLab, Bitbucket, or Azure DevOps—or by uploading a compressed archive, the platform establishes a secure "IP Vault" and conducts an extensive automated evaluation of the entire codebase. This analysis generates various reports and dashboards that include a code-complexity score to assess the intricacy and maintainability of the code, an open-source component evaluation that identifies dependencies, licensing issues, and outdated or vulnerable libraries, as well as a security assessment that pinpoints potential vulnerabilities, insecure configurations, or risky dependencies. Additionally, it provides a “cost-to-replicate” valuation, which estimates the resources and effort required to recreate or substitute the software entirely. Ultimately, the platform equips users with the necessary tools to enhance their understanding of code quality and security, thereby fostering more informed decision-making in software development.

Mesa is an innovative platform that leverages artificial intelligence to enhance code review processes, enabling engineering teams to elevate software quality and confidently deploy code by addressing technical debt before it impacts production. The platform's smart agents are capable of understanding the distinct elements of a team's codebase, business logic, and development standards, allowing them to provide reviews that are contextual and precise, surpassing mere linting or generic suggestions from AI. Users have the flexibility to develop custom review agents that focus on specific issues such as security vulnerabilities, performance optimization, and domain-specific logic, while also selecting from a diverse range of foundational models from notable providers like OpenAI, Anthropic, and Google, which can be optimized for various metrics such as speed, cost-efficiency, or intelligence level. Additionally, Mesa produces comprehensive and consistent descriptions for pull requests utilizing team-defined templates, seamlessly integrating into existing CI/CD workflows, and adjusting to different branching strategies to ensure that quality checks are an integral part of daily development activities. This adaptability not only streamlines the review process but also empowers teams to maintain high standards throughout their software development lifecycle.

Sourcery serves as an AI-driven automated code review tool and coding assistant that aims to enhance the quality of code, identify bugs and security vulnerabilities early on, and ensure uniform standards across various projects for developers and engineering teams. It seamlessly integrates with widely-used development platforms like GitHub, GitLab, and integrated development environments (IDEs) such as VS Code and JetBrains, offering immediate, actionable insights on pull requests and in-code edits instead of relying primarily on conventional peer review processes. By leveraging a blend of large language model capabilities and static analysis, Sourcery evaluates code diffs to provide concise summaries, detailed line-by-line recommendations, overarching feedback, and visual representations that clarify suggested modifications, striving to achieve a review standard akin to that of a fellow developer. Within the IDE, it acts as an instant pair programming assistant that highlights possible enhancements, facilitates one-click application of recommendations, and includes an AI chat feature for further support, making it a versatile tool for developers looking to refine their coding practices. Additionally, Sourcery's real-time feedback mechanism fosters a collaborative coding environment, enabling teams to work more efficiently and effectively together.

Kodus is a collaborative, open-source platform that harnesses AI technology for code review, featuring an intelligent agent named Kody that seamlessly integrates with popular Git workflows like GitHub, GitLab, Bitbucket, and Azure DevOps, aimed at assisting engineering teams in automating and enhancing the quality of their code assessments. By performing thorough analyses on each pull request with a deep understanding of the team’s specific codebase, architecture, workflows, coding standards, and business rules, Kody provides targeted feedback focused on quality, security, performance, and style, rather than offering vague recommendations. Teams have the option to create custom review criteria using natural language or select from a collection of pre-validated rules designed to promote best practices and maintain consistent standards; they can also utilize their own API keys to choose and implement any AI model they prefer. Additionally, Kodus transforms unaddressed suggestions into monitored issues, aids in tracking technical debt, and delivers actionable insights in a manner that minimizes distractions, while supporting more than 30 programming languages to ensure broad applicability across different projects. This comprehensive approach not only streamlines the review process but also fosters a culture of continuous improvement within development teams.

Cubic is an AI-driven code review solution that streamlines the analysis of pull requests on GitHub, enabling software development teams to identify bugs, maintain coding standards, and accelerate their release cycles by minimizing manual review delays. It provides immediate, context-aware feedback upon the opening of a pull request by analyzing the entire repository's history and recognized patterns, which leads to inline comments that identify bugs, coding anti-patterns, technical debt, and suggestions for enhancements that human reviewers could overlook, along with one-click fix options for straightforward issues. Additionally, Cubic can produce concise summaries of pull requests that clarify the purpose and effects of changes, intelligently organize complex differences into more manageable segments, and feature a chat interface that allows developers to pose questions or navigate the codebase directly on the platform. Teams have the capability to establish customized review protocols and incorporate business context from issue tracking systems such as Jira, Linear, or Asana, ensuring that code reviews not only assess technical quality but also align with acceptance criteria. With its innovative features, Cubic significantly enhances the efficiency of the code review process, fostering collaboration and improving overall software quality.

Codacy is an automated code review tool. It helps identify problems through static code analysis. This allows engineering teams to save time and tackle technical debt. Codacy seamlessly integrates with your existing workflows on Git provider as well as with Slack and JIRA or using Webhooks. Each commit and pull-request includes notifications about security issues, code coverage, duplicate code, and code complexity. Advanced code metrics provide insight into the health of a project as well as team performance and other metrics. The Codacy CLI allows you to run Codacy code analysis locally. This allows teams to see Codacy results without needing to check their Git provider, or the Codacy app. Codacy supports more than 30 programming languages and is available in free open source and enterprise versions (cloud or self-hosted). For more see https://www.codacy.com/

Enhance your productivity by ensuring only high-quality code is released, as SonarQube Cloud (previously known as SonarCloud) seamlessly evaluates branches and enriches pull requests with insights. Identify subtle bugs to avoid unpredictable behavior that could affect users and address security vulnerabilities that threaten your application while gaining knowledge of application security through the Security Hotspots feature. Within moments, you can begin using the platform right where your code resides, benefiting from immediate access to the most current features and updates. Project dashboards provide vital information on code quality and readiness for release, keeping both teams and stakeholders in the loop. Showcase project badges to demonstrate your commitment to excellence within your communities. Code quality and security are essential across your entire technology stack, encompassing both front-end and back-end development. That’s why we support a wide range of 24 programming languages, including Python, Java, C++, and many more. The demand for transparency in coding practices is on the rise, and we invite you to be a part of this movement; it's completely free for open-source projects, making it an accessible opportunity for all developers! Plus, by participating, you contribute to a larger community dedicated to improving software quality.

Tailor and Enhance Your Peer Review Workflow for Code and Documents Using Collaborator. Recognized as the leading tool for peer review of code and documentation, Collaborator is designed for development teams committed to maintaining high software quality. Its extensive review capabilities allow you to evaluate source code, design documents, requirements, user stories, test plans, and other documentation all within a single platform. To ensure accountability, it offers proof of review through electronic signatures and comprehensive reports that help meet regulatory compliance requirements. It supports a wide variety of Source Code Management (SCM) systems, including Git, SVN, TFS, Perforce, CVS, ClearCase, RTC, and more. Collaborator also seamlessly integrates with popular platforms such as GitHub, GitLab, Bitbucket, Jira, Eclipse, Visual Studio, among others. Additionally, real-time updates and threaded chat facilitate ongoing discussions, highlighting changes and defects to enhance visibility during each review. Recognizing that every team and project has its distinct needs, Collaborator provides customizable review templates and checklists to create tailored peer review frameworks that suit specific requirements, ensuring that your review process is as effective and efficient as possible. This flexibility empowers teams to adopt best practices tailored to their individual workflows.

Quickly assess the overall code quality of your project, examine recent commits, and identify the most problematic files with CodeFactor. This tool will monitor new and resolved issues for every commit and pull request, prioritizing the most critical problems by considering factors like issue code size, frequency of file changes, and overall file size, allowing you to focus on what truly matters. You can easily create and manage issues or comments directly within code files or on the project issues pages. Additionally, CodeFactor provides updates on the status of pull requests for both GitHub and Bitbucket. Users can conveniently toggle the inspection feature for any branch of the repository as needed. Furthermore, CodeFactor integrates with Slack to deliver immediate notifications regarding code quality for every commit made in a branch or pull request. To get started, simply navigate to the repository settings page for installation. The pricing is straightforward and based on the number of private repositories, ensuring transparency with no surprise fees. This makes for a smooth incorporation into your existing workflow, enhancing overall efficiency and collaboration.

Tailor the code review criteria to reflect the standards that matter most to you, enabling you to sidestep minor bugs and focus on significant issues. This allows for code reviews to be conducted without the constant concern of potential security flaws. Codegrip ensures your code remains private during these automated reviews, allowing you to maintain confidentiality. Stay informed about your project's developments as you receive automatic code quality assessments and pull request alerts in a designated Slack channel of your preference. Manage several projects simultaneously with a centralized dashboard that aggregates all relevant information in one location. Monitor the progress of code quality enhancements over time through straightforward metrics and visual representations. The OWASP framework embodies a collective agreement on the foremost security threats faced by web and mobile applications, providing essential guidance to both developers and security experts regarding the most prevalent and easily exploitable vulnerabilities that can arise in web applications. By following these guidelines, you can enhance your awareness and preparedness against security risks.

Codeball is an AI designed for code reviews, providing a scoring system for pull requests that ranges from 0 (indicating a need for thorough examination) to 1. By leveraging Codeball, you can apply labels to prioritize your focus, automate approvals for straightforward PRs, and enhance your review process. Its user-friendly action comes with sensible defaults while offering extensive customization options to fit your specific workflow requirements. You'll be able to label pull requests that require careful scrutiny, ensuring that you remain vigilant and prevent bugs from sneaking through unnoticed. Codeball efficiently identifies, approves, or labels PRs deemed safe, allowing you to save valuable time by expediting the review of simpler contributions. Built to be fully customizable and programmable through GitHub Actions, Codeball Actions consist of various modular components that can be tailored to meet your needs. Utilizing a deep learning model, Codeball analyzes over one million pull requests, taking into account numerous factors for each submission. Its optimization for precision ensures that it only approves those contributions that it has a high level of confidence in, making it a trustworthy assistant in your development workflow. With Codeball in your toolkit, you can streamline your code review process while maintaining high standards of quality in your projects.

Baz provides a comprehensive solution for efficiently reviewing, tracking, and approving code changes, instilling confidence in developers. By enhancing the code review and merging workflow, Baz offers immediate insights and suggestions that allow teams to concentrate on delivering high-quality software. Organizing pull requests into distinct Topics enables a streamlined review process with a well-defined structure. Furthermore, Baz identifies breaking changes across various elements such as APIs, endpoints, and parameters, ensuring a thorough understanding of how all components interconnect. Developers have the flexibility to review, comment, and propose changes wherever necessary, with transparency maintained on both GitHub and Baz. To accurately gauge the implications of a code change, structured impact analysis is essential. By leveraging AI alongside your development tools, Baz analyzes the codebase, maps out dependencies, and delivers actionable reviews that safeguard the stability of your code. You can easily plan your proposed changes and invite team members for their input while assigning relevant reviewers based on their prior contributions to the project. This collaborative approach fosters a more engaged and informed development environment, ultimately leading to better software outcomes.

Panto is an advanced AI-driven code review tool aimed at improving both the quality and security of code by seamlessly integrating into existing development workflows. Its unique AI operating system synchronizes code with relevant business contexts from platforms such as Jira and Confluence, facilitating efficient and context-sensitive code reviews. Supporting more than 30 programming languages, it performs upwards of 30,000 security checks to ensure a thorough examination of codebases. The "Wall of Defense" feature of Panto AI works continuously to identify vulnerabilities and recommend solutions, effectively stopping defective code from being deployed to production environments. Additionally, with its commitment to zero code retention, compliance with CERT-IN standards, and the ability to operate on-premises, Panto emphasizes both data security and regulatory adherence. Developers can take advantage of reviews that offer a high signal-to-noise ratio, thereby minimizing cognitive overload and enabling them to concentrate on essential logic and design considerations. This focus on clarity and efficiency allows teams to enhance their development processes significantly.

Recurse is a sophisticated AI code checker that identifies bugs and potential breaking changes across your entire codebase before deployment. It seamlessly connects to GitHub or runs via the command line interface, enabling developers to catch errors during pull requests or local development. The platform prevents API and library misuse by analyzing code changes and enforcing custom rules tailored to your coding standards. Recurse offers a free forever plan for public repositories and competitively priced plans for private repositories starting at $25 per user per month or $250 annually. By detecting bugs early, it helps teams maintain code quality, reduce regressions, and improve deployment confidence. The tool is backed by a £2.5 million investment led by Seedcamp and Playfair Capital, highlighting strong market validation. Developers trust Recurse to integrate smoothly into their workflows, saving time and effort in debugging. Overall, it offers an intelligent, cost-effective way to squash bugs before they impact production.

Propel serves as an AI-enhanced code review platform, functioning as your team's virtual AI Tech Lead by delivering immediate feedback on pull requests, transforming comments into actionable suggestions, and facilitating quicker, higher-quality merges. The platform continuously adapts based on your team's reviews, enhancing overall code quality, developer experience, and team efficiency over time. In addition, Propel features Security Scanning capabilities that detect potential security vulnerabilities and compliance concerns before they can impact production environments. Teams using Propel can also construct and sustain an evolving knowledge base that captures their coding patterns and best practices. Moreover, Propel automatically generates weekly summaries of all GitHub activities, which are directly sent to Slack, making it an ideal tool for executive updates, fostering team accountability, and ensuring everyone stays in the loop. This comprehensive approach not only streamlines the coding process but also promotes a culture of continuous improvement within development teams.

Gain an in-depth insight into your software through Embold's detailed analysis and user-friendly visuals. With these intuitive graphics, you can clearly grasp the size and quality of each component, allowing for an immediate comprehension of your software's overall condition. Dive into issues at the component level using informative annotations that pinpoint their exact locations within your codebase. Explore the entire web of dependencies among your software components, gaining insight into how they interact and affect one another. Our innovative partitioning algorithms enable you to swiftly identify opportunities for refactoring and breaking down complex components. The EMBOLD SCORE, derived from four key dimensions, highlights which components significantly impact overall quality and should be prioritized for resolution first. Furthermore, assess your code’s structural integrity utilizing our distinctive collection of anti-patterns, applicable at class, functional, and method levels. Embold also incorporates various metrics, including cyclomatic complexity and coupling between objects, to comprehensively evaluate the quality of your software systems. This multifaceted approach ensures that you are equipped with the necessary tools for maintaining high-quality code.

It fosters a sense of community by facilitating the sharing of code, bug reports, translations, and ideas across various projects, regardless of the tools used. Launchpad enables users to exchange bug reports, updates, patches, and comments seamlessly across different project lines. Additionally, it allows for the sharing of bug data with other tracking systems like Bugzilla and Trac. It includes all essential features of a bug tracker, such as web, email, and API interfaces, connections between bugs and their respective fixes, and team-based delegation capabilities. Once users are prepared, they can upload their code branches to Launchpad and propose merging them back into the main codebase. The code review process, accessible through both web and email, provides a public space for discussing and deciding on the acceptance or rejection of merges. Moreover, Launchpad simplifies the translation process for everyone involved, offering translators a user-friendly web interface that provides automatic suggestions from an extensive library of over 16 million strings. This combination of features not only enhances collaboration but also ensures that all contributors, regardless of their background, can participate effectively in the development process.