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✓ verifiedFreemium
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
775K visits/mo
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CodeRabbit
✓ verifiedPaid
AI code review tool with huge adoption; ~870K visits and 1.4M saves.
870K visits/mo1.5M saves
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Code Autopilot
✓ verifiedFreemium
AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.
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Gitmore
✓ verifiedFreemium
Turns Git commits and PRs into AI-summarized daily or weekly reports delivered to Slack or email, no source access.
7.6K visits/mo
Pricing
No public pricing
Free: $0
Lite: $12
Pro: $24
Enterprise: Talk to us
No public pricing
No public pricing
No public pricing
Free trial available
Core features
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦AI-powered code reviews
- ✦Contextual line-by-line feedback
- ✦Critical change flagging
- ✦Bot interaction
- ✦Direct commit from GitHub
- ✦Integration with Jira & Linear
- ✦Agentic Chat with CodeRabbit
- ✦Product analytics dashboards
- ✦Customizable reports
- ✦Docstrings generation
- ✦Chat inside GitHub issues and PRs
- ✦Task-to-implementation plans with code
- ✦Automatic bug-fix suggestions
- ✦Pull-request summaries for faster review
- ✦Full-codebase context
- ✦GitHub-native integration
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦AI-summarized commit and PR reports
- ✦Daily and weekly scheduled digests
- ✦Slack and email delivery
- ✦One-click OAuth or webhook setup
- ✦GitHub, GitLab and Bitbucket support
- ✦Templates for standups and reports
Use cases
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Automated code review for pull requests
- →Identifying potential bugs and vulnerabilities
- →Improving code quality and consistency
- →Onboarding new developers with AI-driven guidance
- →Speeding up pull-request reviews
- →Implementing features from task descriptions
- →Debugging with AI-proposed solutions
- →Answering questions about a repo
- →Boosting a solo developer's output
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Keep stakeholders updated on what shipped
- →Replace manual status updates and standups
- →Give teams visibility into Git activity
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