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✓ verifiedFreemium
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
👁 775K/mo
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Macroscope
✓ verifiedFreemium
AI tool for engineering teams that automates code review, status updates, and answers questions about what's changing in code.
👁 21K/mo
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GitLoop
✓ verifiedFree trial
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
👁 11K/mo♥ 2.7K
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Rerun
✓ verifiedFreemium
Open-source SDK and viewer for logging, querying, and visualizing multimodal robotics data, with a paid managed Hub for scale.
👁 88K/mo
Pricing
No public pricing
No public pricing
No public pricing
Free trial available
Open Source SDK: Free (Apache-2.0/MIT)
Core features
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦AI code review
- ✦Automatic engineering status updates
- ✦Agent that answers questions and takes action
- ✦Metrics on coding time and project focus
- ✦Pushed vs landed tracking
- ✦Commit and contributor insights
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Open-source Python, Rust, and C++ logging SDK
- ✦Interactive desktop and web viewer for reviewing recordings
- ✦SQL and dataframe queries across logged data
- ✦Column-chunk .rrd storage format for multimodal data
- ✦PyTorch dataloader for training directly on recordings
- ✦Commercial Hub with managed catalog, SSO, and byte-range indexing
- ✦Used in robotics projects like LeRobot, Brush, and PyCuVSLAM
Use cases
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Automating code reviews
- →Keeping stakeholders updated on engineering progress
- →Understanding what's changing in a codebase
- →Tracking team productivity metrics
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Robotics teams debugging calibration and training runs
- →Visualizing and querying large multimodal sensor datasets
- →Streaming training data mixes directly to GPUs at scale
- →Sharing annotated recordings across a robotics engineering team
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