List of the Top 25 AI Code Review Tools for Java in 2026

ZeroPath is the AI-native SAST that finds vulnerabilities traditional tools miss. We built it because security shouldn't overwhelm developers with noise. Unlike pattern-matching tools that flood you with false positives, ZeroPath understands your code's intent and business logic. We find authentication bypasses, IDORs, broken auth, race conditions, and business logic flaws that actually get exploited and missed by traditional SAST tools. We auto-generate patches and pull requests that match your project's style. 75% fewer false positives, 200k+ scans run per month, and ~120 hours saved per team per week. Over 750 organizations use ZeroPath as their new AI-native SAST. Our research has uncovered critical vulnerabilities in widely-used projects like curl, sudo, OpenSSL, and Better Auth (CVE-2025-61928). These are the kinds of issues off-the-shelf scanners and manual reviews miss, especially in third-party dependencies. ZeroPath is an all-in-solution for your AppSec teams: 1. AI-powered SAST 2. Software Composition Analysis with reachability analysis 3. Secrets detection and validation 4. Infrastructure as Code scanning 5. Automated PR reviews 6. Automated patch generation and more...

Junie, the AI coding agent by JetBrains, revolutionizes the way developers interact with their code by embedding intelligent assistance directly into JetBrains IDEs like WebStorm, RubyMine, and GoLand. Designed to fit naturally into developers’ existing workflows, Junie helps tackle both small and ambitious coding tasks by providing tailored execution plans and automated code generation. It combines the power of AI with IDE capabilities to perform code inspections, syntax checks, and run tests automatically, maintaining code quality without manual intervention. Junie offers two distinct modes: one for executing code tasks and another for interactive querying and planning, allowing developers to seamlessly collaborate with the agent. Its ability to comprehend code relationships and project logic enables it to propose efficient solutions and reduce time spent on debugging. Developers from various fields, including game development and web design, have showcased impressive projects built entirely or partly with Junie’s assistance. The tool supports multi-file edits and integrates version control system (VCS) assistance, making complex refactoring easier and safer. JetBrains offers multiple pricing plans tailored to individuals and organizations, ranging from free tiers to premium AI Ultimate for intensive daily use. By handling repetitive coding chores, Junie frees developers to focus on the creative and strategic aspects of software development. Overall, Junie stands as a powerful AI companion transforming traditional coding into a smarter, more collaborative experience.

Introducing an advanced AI-driven code review system that enhances code quality and identifies vulnerabilities at an early stage. Effortlessly correct issues directly within your Integrated Development Environment (IDE) or through pull requests. Aikido serves as your comprehensive software security hub, covering everything from vulnerability management to penetration testing. Ensure the security of all applications you create, host, and manage. Designed for teams of all sizes, Aikido empowers organizations to deliver secure software solutions, earning the trust of notable companies such as Revolut, Deel, The Premier League, Tines, n8n, SoundCloud, and over 50,000 more. Aikido allows developers to focus on what they do best: building great products.

Windsurf is an innovative IDE built to support developers with AI-powered features that streamline the coding and deployment process. Cascade, the platform’s intelligent assistant, not only fixes issues proactively but also helps developers anticipate potential problems, ensuring a smooth development experience. Windsurf’s features include real-time code previewing, automatic lint error fixing, and memory tracking to maintain project continuity. The platform integrates with essential tools like GitHub, Slack, and Figma, allowing for seamless workflows across different aspects of development. Additionally, its built-in smart suggestions guide developers towards optimal coding practices, improving efficiency and reducing technical debt. Windsurf’s focus on maintaining a flow state and automating repetitive tasks makes it ideal for teams looking to increase productivity and reduce development time. Its enterprise-ready solutions also help improve organizational productivity and onboarding times, making it a valuable tool for scaling development teams.

Qodo, which was previously known as Codium, offers an analysis of your code to detect potential bugs prior to deployment. By mapping out the behaviors inherent in your code, it effectively pinpoints edge cases and highlights any areas of concern. Subsequently, Qodo produces clear and meaningful unit tests that align with your code's functionality. This allows you to observe how your code operates and assess the impact of modifications on the surrounding codebase. With a keen focus on code coverage, it emphasizes the importance of high-quality tests that validate functionality, thereby instilling confidence in your commitment to the code. Instead of spending excessive time on dubious testing, you can redirect your efforts toward developing features that genuinely benefit your users. As you write, Qodo analyzes your code, documentation, and comments to propose tests that can be easily integrated into your suite. Committed to maintaining code integrity, Qodo not only generates tests but also aids in deepening your understanding of the code, exposing edge cases, and identifying any suspicious behaviors, ultimately enhancing the robustness of your software. By using Qodo, you can ensure a more efficient development process, allowing you to prioritize quality alongside productivity.

GitHub Copilot is an AI-powered developer platform designed to enhance productivity across the entire software development workflow. It works directly within IDEs, terminals, and GitHub to assist with coding, debugging, and collaboration. Copilot offers intelligent code completion, explanations, refactoring, and real-time suggestions. Developers can leverage agent-based capabilities to let Copilot autonomously handle tasks like writing code, creating pull requests, and responding to feedback. The platform supports multiple industry-leading AI models, giving teams flexibility in performance and cost optimization. Copilot CLI brings AI assistance to the command line for complex, context-aware workflows. Teams can customize Copilot with organizational knowledge to ensure consistency and shared best practices. Enterprise-grade controls allow administrators to manage access, monitor usage, and enforce governance. Secure MCP integrations help organizations control how external tools connect to Copilot. Copilot scales easily from individual developers to large enterprises. It integrates seamlessly with existing GitHub workflows and tools. GitHub Copilot ultimately helps teams build better software faster with AI as a collaborative partner.

Amp is a frontier coding agent designed to redefine how developers interact with AI during software development. Built for use in terminals and modern editors, Amp allows engineers to orchestrate powerful AI agents that can reason across entire repositories, not just isolated files. It supports advanced workflows such as large-scale refactors, architecture exploration, agent-generated code reviews, and parallel course correction with forced tool usage. Amp integrates leading AI models and layers them with robust context management, subagents, and continuous tooling improvements. Developers can let agents run autonomously, trusting them to produce consistent, high-quality results across complex projects. With strong community adoption, rapid feature releases, and a focus on real engineering use cases, Amp stands out as a premium, agent-first coding platform. It empowers developers to ship faster, explore deeper, and build systems that would otherwise require significantly more time and effort.

Augment Code is a cutting-edge AI coding agent designed to support software engineers working with complex, large-scale codebases. The platform integrates smoothly with major IDEs like Visual Studio Code, IntelliJ IDEA, and Vim, providing a range of powerful tools for SDK migration, code refactoring, and documentation generation. Augment Code stands out by learning from each interaction, adapting to the developer's code style, and persisting this knowledge to improve code generation and explanations over time. This personalized approach allows engineers to write code with the same expertise as senior developers, regardless of their experience level. With over 100 supported native and MCP tools, Augment Code enables seamless integration into existing workflows, whether debugging, refactoring, or managing multiple repositories. The agent also works with popular platforms like GitHub and Slack, ensuring that engineers can collaborate and manage their codebase efficiently without ever leaving their preferred tools. By offering real-time feedback and deep context awareness, Augment Code helps developers tackle complex projects with ease and confidence. The platform’s ability to handle large repositories, debug with images, and generate high-quality code snippets significantly enhances productivity. Trusted by leading companies, Augment Code is the ultimate tool for modern developers aiming to produce high-quality code while saving time and effort.

SonarQube Server functions as a self-managed platform for continuous code quality evaluation, empowering development teams to identify and resolve bugs, security vulnerabilities, and code deficiencies instantly. It offers automated static analysis for various programming languages, ensuring rigorous adherence to quality and security benchmarks throughout the software development lifecycle. Moreover, SonarQube Server seamlessly integrates with existing CI/CD processes, accommodating both on-premise and cloud-based installations. With its advanced reporting features, it aids teams in tackling technical debt, tracking progress, and upholding coding standards. This tool is especially beneficial for organizations that seek thorough oversight of their code quality and security while sustaining optimal performance. In addition, SonarQube promotes a culture of ongoing enhancement within development teams, motivating them to take proactive steps toward improving code reliability over time. Ultimately, the platform not only enhances code quality but also strengthens team collaboration and accountability in software development projects.

Snyk stands at the forefront of developer security, empowering developers globally to create secure applications while also providing security teams with the tools necessary to navigate the complexities of the digital landscape. By prioritizing a developer-centric approach, we enable organizations to safeguard every vital element of their applications, spanning from code to cloud, which results in enhanced productivity for developers, increased revenue, higher customer satisfaction, reduced costs, and a stronger security framework overall. Our platform is designed to seamlessly integrate into developers' workflows and fosters collaboration between security and development teams, ensuring that security is woven into the fabric of application development. Furthermore, Snyk's commitment to innovation continually evolves to meet the changing demands of the security landscape.

GoCodeo serves as an all-encompassing AI platform tailored for developers, designed to expedite the processes of coding, testing, and debugging. By seamlessly integrating with VS Code, it delivers real-time support that ranges from generating code snippets to automatically producing unit tests. The platform’s AI-powered tools further enhance productivity by offering valuable debugging insights, allowing developers to swiftly pinpoint and resolve problems. With its compatibility across various programming languages and frameworks, GoCodeo enables developers to create high-quality, production-ready code with greater ease, optimizing development timelines and improving overall project efficiency. Ultimately, GoCodeo is a vital resource for developers seeking to elevate their coding experience and achieve faster results.

Accelerate the speed and efficiency of software development and delivery by harnessing the power of generative AI, while maintaining strong enterprise security and privacy measures. Gemini Code Assist enhances your coding experience through its ability to complete your code in real-time and generate full code segments or functions upon request. This dynamic coding tool is compatible with a wide range of popular integrated development environments (IDEs) such as Visual Studio Code and various JetBrains IDEs, including IntelliJ, PyCharm, GoLand, and WebStorm, as well as Cloud Workstations and Cloud Shell Editor, supporting over 20 different programming languages like Java, JavaScript, Python, C, C++, Go, PHP, and SQL. With a user-friendly natural language chat interface, Gemini Code Assist allows for seamless interaction, providing answers to your programming questions or offering insights into best coding practices, and this chat feature is available across all supported IDEs. Organizations can customize Gemini Code Assist by integrating their proprietary codebases and knowledge libraries, thus enabling the tool to deliver more tailored assistance that meets unique enterprise requirements. Moreover, Gemini Code Assist is designed to facilitate substantial changes across entire codebases, thereby greatly enhancing the development workflow. This versatile approach not only increases productivity but also empowers teams to innovate at a faster pace in a secure setting, ultimately driving success in software projects. As organizations adapt to evolving technological landscapes, tools like Gemini Code Assist become essential in maintaining a competitive edge.

Amazon CodeGuru is a cutting-edge tool designed for developers that employs machine learning to provide valuable recommendations for improving code quality while identifying the most expensive lines of code within an application. By integrating Amazon CodeGuru into your existing software development workflow, you can take advantage of automated code reviews that help highlight and enhance these costly segments of code, ultimately leading to lower overall expenses. In addition, Amazon CodeGuru Profiler aids developers by pinpointing the most resource-demanding lines of code, offering detailed visual representations and actionable advice for optimizing the code to save costs. Moreover, Amazon CodeGuru Reviewer uses machine learning techniques to uncover critical issues and subtle bugs during the application development process, thus improving the code's overall quality. This all-encompassing strategy not only simplifies the development process but also cultivates a more efficient and economically viable coding environment. By leveraging these tools, developers can significantly enhance both their productivity and the reliability of their applications.

CodeScene offers advanced capabilities that extend well beyond conventional code analysis methods. It allows for the visualization and assessment of various elements that affect software delivery and quality, moving past a mere focus on the code itself. By leveraging CodeScene’s actionable insights and recommendations, users can make informed decisions driven by data. The platform empowers developers and technical leaders to: - Obtain a comprehensive view of their software system's evolution through a unified dashboard. - Recognize, prioritize, and address technical debt while considering the potential return on investment. - Foster a robust codebase utilizing robust CodeHealth™ Metrics, reducing rework and allocating more resources to innovation. - Easily integrate with Pull Requests and development environments to receive actionable code reviews and refactoring suggestions. - Establish improvement objectives and quality thresholds for teams, all while tracking their progress. - Enhance retrospectives by pinpointing areas that require development. - Evaluate performance against customized trends to ensure continuous improvement. - Grasp the social dynamics of the code by measuring socio-technical aspects such as key personnel dependencies, knowledge sharing, and collaboration between teams effectively. Overall, CodeScene not only improves code quality but also enhances team collaboration and project management.

CodeSandbox is designed to simplify the process of expressing and validating your coding ideas while eliminating the complexities associated with setting up development environments and sharing projects. The platform has garnered over 4 million monthly users, including notable organizations such as Shopify and Atlassian, and since its inception, more than 35 million applications have been developed by creators. It plays a vital role in numerous open-source projects, including popular frameworks like React, Vue, and Babel. Users can easily invite friends or team members to collaborate or view their projects through a simple URL, and they have access to over 1 million packages to build robust applications efficiently. Additionally, developers can import and execute repositories straight from GitHub or select from a variety of templates to get started in no time. Furthermore, Boxy, the AI-driven coding assistant from CodeSandbox, is now accessible to all users with Pro subscriptions, enhancing the coding experience even further. This combination of features positions CodeSandbox as a leading tool in the future of web development.

Cody is a sophisticated AI coding assistant created by Sourcegraph to improve software development's efficiency and quality. It works effortlessly within popular Integrated Development Environments (IDEs) such as VS Code, Visual Studio, Eclipse, and various JetBrains tools, offering features like AI-enhanced chat, code autocompletion, and inline editing, all while preserving existing workflows. Tailored forenterprise teams, Cody focuses on maintaining consistency and quality throughout entire codebases by leveraging extensive context and shared prompts. Moreover, it broadens its contextual insights beyond mere code by integrating with platforms like Notion, Linear, and Prometheus, thus creating a comprehensive picture of the development landscape. By utilizing advanced Large Language Models (LLMs), including Claude Sonnet 4 and GPT-4o, Cody provides customized assistance that can be fine-tuned for various applications, striking a balance between speed and performance. Users have reported notable increases in productivity, with some indicating time savings of around 5-6 hours weekly and a doubling of their coding efficiency when utilizing Cody. As developers continue to explore its features, the potential for Cody to transform coding practices becomes increasingly evident.

Cosine possesses the ability to understand both overarching ideas and detailed specifics, providing responses that exceed human performance. Our methodology goes beyond being a simple enhancement to an LLM; it incorporates a variety of techniques such as static analysis and semantic search, among others. When you inquire about implementing a new feature or modifying existing code, simply ask Cosine, and we will deliver a thorough, step-by-step guide tailored to your needs. Cosine carefully organizes your codebase, gaining insights on multiple levels; from the interconnections between files and functions to a detailed semantic analysis of the code itself, guaranteeing that any question related to your codebase can be thoroughly answered. On the other hand, Genie is recognized as the premier AI software engineer, achieving an outstanding evaluation score of 30% on the respected SWE-Bench benchmark. It demonstrates remarkable proficiency in debugging, feature development, and code refactoring, executing these tasks either autonomously or in conjunction with the user, fostering a collaboration that feels like working with a colleague rather than just having a copilot. Both Cosine and Genie revolutionize the expectations for what AI can accomplish in the realm of software engineering, setting a new benchmark for the industry. This evolution in AI capabilities signals a transformative shift in how developers approach coding challenges, ultimately enhancing productivity and innovation.

Metabob specializes in diagnosing, interpreting, and resolving coding problems that may stem from either human errors or artificial intelligence. Utilizing cutting-edge graph neural networks for detection alongside large language models for elucidation and resolution, Metabob effectively combines the advantages of both technologies. The graph neural networks scrutinize and classify problematic code while remaining contextually aware. This code, enriched with pertinent context, is then archived in Metabob's backend system. The stored information is later harnessed by an integrated large language model, which generates customized explanations and solutions informed by the provided context. Trained on a vast dataset comprising millions of bug fixes performed by adept developers, Metabob's AI possesses a profound understanding of coding logic and context, allowing it to pinpoint complex issues across various codebases and autonomously generate appropriate fixes. Furthermore, Metabob's AI code review feature has the capability to reveal numerous logical errors, such as race conditions and overlooked edge cases, that often elude traditional static analysis tools. This groundbreaking methodology not only boosts debugging efficiency but also significantly improves the overall quality of the codebase. As a result, developers can focus more on innovation and less on troubleshooting.

A newly developed framework specifically crafted to address the intricacies of autonomous intelligence is now accessible. You can continue to create software utilizing your existing programming languages, libraries, APIs, datasets, and models. This uniquely designed autonomous product is built to adapt and grow in accordance with your evolving development requirements. One of the standout features of autonomous AI is its ability to simplify the video production process by autonomously generating, editing, and enhancing content, significantly reducing the manual effort required. By integrating AI technologies like Luma AI or OpenAI for video generation and utilizing Azure for scalable text-to-speech capabilities, your autonomous system is set to produce exceptional video content. Additionally, by linking with platforms such as YouTube, your autonomous AI can continuously improve its performance based on user feedback and engagement analytics. We firmly believe that the journey toward achieving Artificial General Intelligence (AGI) hinges on the cooperation of numerous autonomous systems working in tandem. Our passionate team comprises skilled engineers and researchers dedicated to the evolution of autonomous artificial intelligence. Should this innovative idea strike a chord with you, we are excited to discuss and explore collaborative opportunities that could arise. Together, we can push the boundaries of what is possible in the realm of AI.

Enhance the creation of robust and secure software by leveraging AI throughout all stages of the development lifecycle. GitLab Duo acts as an AI-powered ally intricately embedded within the GitLab framework, designed to elevate productivity and improve collaboration among software developers. It delivers intelligent code suggestions, assists with code refactoring and debugging, and streamlines processes by automating repetitive tasks. Moreover, GitLab Duo facilitates natural language queries concerning project management and development analytics, providing developers with a more user-friendly approach to interact with their code repositories. With compatibility with leading IDEs like JetBrains and Neovim, GitLab Duo ensures consistent support in the environments preferred by developers. By merging AI-enhanced productivity with GitLab's extensive DevSecOps functionalities, GitLab Duo equips teams to create exceptional software more swiftly while strengthening collaborative efforts. The introduction of this groundbreaking tool fundamentally changes the methodology teams utilize in software development, paving the way for more innovative practices and efficient workflows.

Fynix operates as an advanced AI-powered platform designed to boost the efficiency of software development by offering intelligent coding assistance and agent-based code evaluations. This innovative tool integrates effortlessly with popular IDEs, including VS Code, and boasts features such as context-aware autocomplete, the ability to input natural language for code corrections and translations, and automatic visual representations of code flow. With its Code Assistant capability, Fynix empowers developers to write cleaner and more efficient code at a faster rate, while the upcoming Code Quality Agent aims to enhance bug detection and maintain coding standards. Supporting multiple programming languages and frameworks, along with compatibility with tools like Jira, Fynix emerges as a versatile solution that promotes better coding practices and encourages team collaboration. As developers continuously seek to refine their skills and produce high-quality code, Fynix has established itself as a vital partner in the evolving realm of software development, ensuring that teams can work more effectively together. Ultimately, the platform represents a significant advancement in the tools available to developers striving for excellence in their craft.

Macroscope is an analytics platform powered by AI, designed specifically for engineering and product teams, that integrates effortlessly with a company's codebase, commit logs, issue tracking systems like Linear or Jira, and Slack to generate insights about the development workflow automatically. Utilizing code-walking methods on the Abstract Syntax Tree (AST), it meticulously assesses code modifications to uncover the interconnections and dependencies within the code, eventually creating summaries for commits and pull requests, which also feature automated reviews and descriptions, along with tracking changes in the codebase and recognizing trends in feature development and bug fixing. Stakeholders are empowered to ask about progress using natural language, such as "What did we ship last week?", allowing them to access valuable insights on engineering resource allocation, detect critical bugs while minimizing false positives, and observe productivity and project status without needing to examine every detail of code changes. Additionally, this tool significantly improves communication efficiency among team members by consolidating information and promoting a more transparent understanding of project developments, ultimately leading to better decision-making within the team. By providing a comprehensive overview of ongoing progress, Macroscope not only streamlines workflows but also enhances collaboration across various roles within the organization.

Mesa is a cutting-edge platform that utilizes artificial intelligence to improve the code review process, allowing engineering teams to enhance software quality and deploy code with greater assurance by tackling technical debt before it affects production. Its intelligent agents understand the unique components of a team’s codebase, business logic, and development standards, thus offering reviews that are both contextual and accurate, going beyond basic linting or generic AI suggestions. Users can create custom review agents tailored to address specific concerns like security vulnerabilities, performance enhancements, and domain-specific logic, while also choosing from a variety of foundational models offered by esteemed providers such as OpenAI, Anthropic, and Google, which can be fine-tuned for different criteria including speed, cost-effectiveness, or level of intelligence. Moreover, Mesa generates thorough and uniform descriptions for pull requests based on templates defined by the team, seamlessly fitting into existing CI/CD workflows and adapting to various branching strategies, ensuring that quality checks become a fundamental aspect of daily development routines. This flexibility not only simplifies the review process but also empowers teams to uphold high standards consistently throughout their software development lifecycle, ultimately leading to more reliable and efficient software delivery. Embracing this technology can significantly enhance collaboration and communication within teams, fostering a culture of continuous improvement.

Sourcery functions as an AI-based automated code review tool and coding assistant dedicated to improving code quality, detecting bugs and security issues early, and maintaining consistent standards across multiple projects for developers and engineering teams. It integrates smoothly with popular development platforms such as GitHub, GitLab, and IDEs like VS Code and JetBrains, providing immediate, actionable insights on pull requests and code modifications rather than depending solely on traditional peer review methods. By combining the capabilities of large language models with static analysis techniques, Sourcery examines code differences to deliver concise summaries, detailed recommendations for individual lines, comprehensive feedback, and visual aids that clarify suggested changes, aiming to replicate the review quality of a fellow developer. Within the integrated development environment, it serves as a real-time pair programming assistant that not only highlights potential improvements but also allows for one-click implementation of suggestions and features an AI chat option for additional guidance, making it an adaptable resource for developers wanting to enhance their coding techniques. Furthermore, Sourcery's feedback in real-time cultivates a cooperative coding atmosphere, enabling teams to collaborate more effectively and streamline their workflows, ultimately leading to improved productivity and code quality. This emphasis on collaboration and efficiency makes Sourcery an invaluable asset for modern development teams.

Kodus is an innovative, collaborative platform that utilizes AI for code reviews, featuring an intelligent assistant named Kody, which integrates flawlessly with major Git services such as GitHub, GitLab, Bitbucket, and Azure DevOps, to support engineering teams in automating and improving the quality of their code evaluations. Kody conducts in-depth analyses of each pull request, considering the specific codebase, architecture, workflows, coding standards, and business rules of the team, thereby providing precise feedback that emphasizes quality, security, performance, and style, avoiding generic suggestions. Teams can customize their review parameters using natural language or opt for a selection of pre-approved rules that encourage best practices and uphold uniform standards; they also have the flexibility to implement their preferred AI models by using their own API keys. Furthermore, Kodus turns unresolved recommendations into tracked issues, helps monitor technical debt, and offers actionable insights in a way that reduces distractions, while accommodating over 30 programming languages to ensure versatility across various projects. This all-encompassing strategy not only simplifies the review process but also promotes a culture of ongoing enhancement within development teams, paving the way for more effective collaboration and higher-quality code outcomes. Ultimately, Kodus empowers teams to maintain a focused and efficient development environment while continuously refining their coding practices.