cubic
Cubic is an AI-powered code review platform that automatically analyzes pull requests in GitHub to help software teams catch bugs, enforce standards, and ship code faster by reducing manual review bottlenecks. It delivers context-aware feedback seconds after a PR is opened by examining the full repository history and patterns, surfacing inline comments that highlight bugs, anti-patterns, technical debt, and improvement suggestions that human reviewers might miss, and providing one-click fix options for simple issues. Cubic can generate clear PR summaries that explain the intent and impact of changes, intelligently order complex diffs into easier-to-review chunks, and offer a context-aware chat interface that lets developers ask questions or explore the codebase directly within the platform. Teams can define custom review rules and integrate business context from issue trackers like Jira, Linear, or Asana so that code reviews validate acceptance criteria as well as technical quality.
Learn more
Gemini Code Assist
Increase software development and delivery velocity using generative AI assistance, with enterprise security and privacy protection.
Gemini Code Assist completes your code as you write, and generates whole code blocks or functions on demand. Code assistance is available in many popular IDEs, such as Visual Studio Code, JetBrains IDEs (IntelliJ, PyCharm, GoLand, WebStorm, and more), Cloud Workstations, Cloud Shell Editor, and supports 20+ programming languages, including Java, JavaScript, Python, C, C++, Go, PHP, and SQL.
Through a natural language chat interface, you can quickly chat with Gemini Code Assist to get answers to your coding questions, or receive guidance on coding best practices. Chat is available in all supported IDEs.
Enterprises can customize Gemini Code Assist using their organization’s private codebases and knowledge sources so that Gemini Code Assist can offer more tailored assistance.
Gemini Code Assist enables large-scale changes to entire codebases.
Learn more
Recurse
We build machine learning models that find bugs in code. We can be used proactively as part of the development process by both humans and AI agents to eliminate problematic code before it's submitted for review. We can also do checks at time of code review through our GitHub agent that adds comments to PRs (Pull Requests - essentially just submissions of code), to ensure nothing slips through. We allow developers to enforce their own taste on the code that either the AI or their teams contribute to the codebase by providing Recurse Rules. These are written in markdown and are descriptions of bad patterns that you don't want present in your codebase (e.g. the concept of DRY - do not repeat yourself).
Learn more
CodeRabbit
Privacy-focused, contextual pull request reviews with line-by-line code suggestions and interactive chat that gets smarter over time. The diff in the pull request is transformed into a clear summary, helping you understand the intent of the changes. Creates automated release notes, convenient for inclusion in the release documentation. A detailed, line-by-line analysis of the code changes provides precise and actionable suggestions ready to be committed. Ask questions to the bot within your code lines, provide more context, and have it write the code. The more you chat with the bot, the smarter it will become. Shorten cycle time with faster review feedback and high-quality code change suggestions. Your data stays confidential and solely fine-tunes your reviews. The system learns from your interactions, refining the reviews to align with your preferences.
Learn more
