GitHub Copilot
GitHub Copilot is an AI-powered development assistant designed to accelerate software workflows from the editor to the enterprise. It works directly inside popular IDEs, terminals, and GitHub itself to help developers write, understand, and improve code faster. Copilot supports multiple leading large language models, allowing users to optimize for speed, accuracy, or cost. Developers can use Copilot to complete code, explain concepts, propose edits, and validate files in real time. It also enables agent-based workflows where Copilot can autonomously handle issues, write code, and create pull requests. With seamless integration across tools, Copilot keeps developers focused without breaking their flow. GitHub Copilot is built to scale from individual developers to large organizations with enterprise-grade controls.
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Pullflow
Collaborate with each other and AI in the most natural way without leaving your favorite tools - minimizing distraction and context switching. Pullflow synchronizes user identities and code-review activity across GitHub, Slack, and VS Code, enabling you to converse naturally across platforms. Take action from wherever you are, and return to your flow. Pullflow integrates with GitHub Actions, external CI/CD, GitHub apps, and more, to bring you a single view of your pull request from draft and review to test and deploy. Let Pullflow take care of quick actions for you with just a chat mention or IDE keyboard shortcut. Request review, add/remove labels, give feedback, approve, and more, without a trip to GitHub.
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Baz
Baz delivers the context and automation to review, track, and approve code changes with confidence. Baz transforms your code review and merging process by giving instant application insights and suggestions, helping you focus on building and shipping strong software. Baz organizes your pull request into Topics, so you can breeze through reviews with a clear structure. Baz uncovers breaking changes across APIs, endpoints, parameters, and more, analyzing how every piece fits together. Developers can review, comment, and suggest wherever they want. We'll make sure it's fully visible both on GitHub and Baz. The only way to predict the true impact of a code change is through structured impact analysis. Baz integrates AI and your developer tools to analyze your codebase, map dependencies, and provide actionable reviews that ensure your code’s stability. Plan your proposed changes and invite your team to review them. Easily assign relevant reviewers based on past contributions.
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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).
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