Best AI Code Review Tools for Kotlin

ZeroPath (YC S24) is an AI-native application security platform that delivers comprehensive code protection beyond traditional SAST. Founded by security engineers from Tesla and Google, ZeroPath combines large language models with deep program analysis to deliver intelligent security testing that finds real vulnerabilities while dramatically reducing false positives. Unlike traditional SAST tools that rely on pattern matching, ZeroPath understands code context, business logic, and developer intent. This enables identification of sophisticated security issues including business logic flaws, broken authentication, authorization bypasses, and complex dependency vulnerabilities. Our comprehensive security suite covers the application security lifecycle: 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... ZeroPath integrates seamlessly with GitHub, GitLab, Bitbucket, Azure DevOps and many more. The platform handles codebases with millions of lines across Python, JavaScript, TypeScript, Java, Go, Ruby, Rust, PHP, Kotlin and more. Our research team has been successful in finding vulnerabilities like critical account takeover in better-auth (CVE-2025-61928, 300k+ weekly downloads), identifying 170+ verified bugs in curl, and discovering 0-days in production systems at Netflix, Hulu, and Salesforce. Trusted by 750+ companies and performing 200k+ code scans monthly.

JetBrains Junie is an innovative AI coding assistant that works inside many JetBrains IDEs to streamline programming efforts and boost efficiency. This agent leverages advanced AI to help developers write, test, and inspect code without leaving their familiar development environment. Junie offers both code execution and interactive collaboration, allowing programmers to switch between automated code writing and brainstorming sessions for features and improvements. By deeply understanding the codebase, Junie identifies the best ways to tackle tasks and ensures all changes meet quality standards through syntax and semantic checks. It also runs tests to minimize errors and keep the project healthy, freeing developers from routine tasks. Many developers have successfully built complex applications and games using Junie, highlighting its flexibility across different languages and frameworks. The AI adapts to each task’s complexity and workflow, making coding less tedious and more focused on creativity. Whether you are building a simple web app or a complex game, Junie offers smart support throughout the development cycle.

Introducing advanced AI-driven code review solutions that ensure code integrity and address vulnerabilities at an early stage. Effortlessly implement fixes directly in your Integrated Development Environment (IDE) or through Pull Requests (PRs). With Aikido, you can safeguard every aspect of your development process—from vulnerability management to penetration testing. Make it your central hub for software security. Aikido is designed to accommodate teams of all sizes, empowering companies to deliver secure software with confidence. It has earned the trust of over 50,000 organizations, including names like Revolut, Deel, The Premier League, Tines, n8n, and SoundCloud. Aikido allows developers to focus on what they do best: creating.

Amp is a next-generation coding agent engineered for developers working at the frontier of software development. It brings powerful AI agents directly into the terminal and code editors, allowing engineers to build, refactor, review, and explore large codebases with minimal friction. Unlike simple code assistants, Amp operates agentically, running subagents, managing context, and making coordinated changes across dozens of files. It supports multiple state-of-the-art models and continuously evolves with frequent updates, new agents, and performance improvements. Features like agentic code review, clickable diagrams, fast search subagents, and context-aware analysis make Amp feel like a true engineering partner rather than a chat tool. By reducing manual overhead and increasing leverage, Amp enables teams to focus on higher-level design and problem solving. The result is faster iteration, cleaner architectures, and more ambitious builds.

Enhance the speed and efficiency of software development and delivery by leveraging generative AI support, all while ensuring robust enterprise security and privacy safeguards. Gemini Code Assist streamlines your coding process by completing your code as you type and can generate entire code blocks or functions upon request. This powerful code assistance tool is compatible with a variety of popular integrated development environments (IDEs) like Visual Studio Code and JetBrains IDEs (including IntelliJ, PyCharm, GoLand, and WebStorm), as well as Cloud Workstations and Cloud Shell Editor, supporting over 20 programming languages such as Java, JavaScript, Python, C, C++, Go, PHP, and SQL. Utilizing a natural language chat interface, you can easily interact with Gemini Code Assist to obtain solutions to your coding queries or gain insights into coding best practices, with chat functionality accessible across all supported IDEs. Organizations have the flexibility to tailor Gemini Code Assist by integrating their private codebases and knowledge repositories, enabling the tool to provide more personalized assistance that aligns with specific enterprise needs. Furthermore, Gemini Code Assist has the capability to facilitate extensive modifications across entire codebases, thereby optimizing the development workflow significantly. This adaptability not only boosts productivity but also empowers teams to innovate more rapidly in a secure environment.

CodeScene's powerful features go beyond traditional code analysis. Visualize and evaluate all the factors that influence software delivery and quality, not just the code itself. Make informed, data-driven decisions based on CodeScene’s actionable insights and recommendations. CodeScene guides developers and technical leaders to: - Get a holistic overview and evolution of your software system in one single dashboard. - Identify, prioritize, and tackle technical debt based on return on investment. - Maintain a healthy codebase with powerful CodeHealth™ Metrics, spend less time on rework and more time on innovation. - Seamlessly integrate with Pull Requests and editors, get actionable code reviews and refactoring recommendations. - Set Improvement goals and quality gates for teams to work towards while monitoring the progress. - Support retrospectives by identifying areas for improvement. - Benchmark performance against personalized trends. - Understand the social side of the code, measure socio-technical factors like key personnel dependencies, knowledge sharing and inter-team coordination.

Codacy is an end-to-end DevSecOps platform designed to enforce code quality, security, and compliance across modern development workflows. It integrates seamlessly with IDEs, repositories, and CI/CD pipelines to provide continuous analysis and real-time feedback. The platform performs static and dynamic testing, dependency scanning, and infrastructure checks to identify vulnerabilities early and throughout the software lifecycle. Codacy’s AI Guardrails feature ensures that both human-written and AI-generated code meet organizational standards by detecting risks and automatically fixing issues. It also offers automated pull request reviews, quality metrics, and test coverage tracking to improve development efficiency. Centralized policies allow organizations to maintain consistent standards across teams and projects. With support for multiple programming languages and easy integration into existing workflows, Codacy simplifies secure coding practices. It helps teams reduce manual review effort while improving code reliability and maintainability. By combining security, quality, and AI protection, Codacy empowers teams to ship faster with confidence.

Cody is an advanced AI coding assistant developed by Sourcegraph to enhance the efficiency and quality of software development. It integrates seamlessly with popular Integrated Development Environments (IDEs) such as VS Code, Visual Studio, Eclipse, and various JetBrains IDEs, providing features like AI-driven chat, code autocompletion, and inline editing without altering existing workflows. Designed to support enterprises, Cody emphasizes consistency and quality across entire codebases by utilizing comprehensive context and shared prompts. It also extends its contextual understanding beyond code by integrating with tools like Notion, Linear, and Prometheus, thereby gathering a holistic view of the development environment. By leveraging the latest Large Language Models (LLMs), including Claude Sonnet 4 and GPT-4o, Cody offers tailored assistance that can be optimized for specific use cases, balancing speed and performance. Developers have reported significant productivity gains, with some noting time savings of approximately 5-6 hours per week and a doubling of coding speed when using Cody.

Accelerate the development of highly secure software with the assistance of AI throughout every phase of the software development process. GitLab Duo serves as an AI-enhanced companion that is seamlessly woven into the GitLab ecosystem, aiming to boost productivity and foster teamwork in software development. It offers smart code recommendations, aids in code refactoring and debugging, and simplifies workflows by automating mundane tasks. Additionally, GitLab Duo allows for natural language inquiries related to project management and development insights, granting developers a more intuitive way to engage with their repositories. With integration into popular IDEs such as JetBrains and Neovim, GitLab Duo provides uninterrupted support within the environments that developers favor. Through the fusion of AI-driven productivity and GitLab’s comprehensive DevSecOps capabilities, GitLab Duo empowers teams to produce superior software at a quicker pace while enhancing collaborative efforts. This innovative tool ultimately transforms the way teams approach software development.

Fynix serves as an AI-driven platform aimed at enhancing software development efficiency by providing smart coding assistance and agent-based code reviews. This tool seamlessly integrates with widely used IDEs such as VS Code, offering features like context-aware autocomplete, natural language inputs for code corrections and translations, along with automatic visualizations of code flow. The Code Assistant feature of Fynix enables developers to produce cleaner and more efficient code at an accelerated pace, and the forthcoming Code Quality Agent promises to streamline bug detection while upholding coding standards. Supporting a variety of programming languages and frameworks, and compatible with tools like Jira, Fynix proves to be a flexible solution for fostering improved coding practices and team collaboration. As developers strive for excellence in their coding endeavors, Fynix stands out as an essential ally in the software development landscape.

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.

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.