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Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.
Open-source framework for automated end-to-end UI testing of mobile and web apps, with a paid cloud for parallel device runs.
Converts screenshots, PDFs, and slides into editable Figma, PowerPoint, or Canva designs and turns Figma layouts into code.
CI reliability platform that auto-quarantines flaky tests and runs an intelligent GitHub merge queue for engineering teams.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦AI code completion and suggestions
- ✦Natural-language code generation
- ✦In-IDE chat assistance
- ✦AI code review
- ✦IDE integrations (VS Code, JetBrains, etc.)
- ✦GitHub integration
- ✦Human-readable YAML test flows
- ✦Local CLI and Studio testing for free
- ✦Open-source, CI-friendly design
- ✦Cloud device farm for parallel runs
- ✦AI-agent integration through MCP
- ✦Self-healing tests with local agents
- ✦Screenshot-to-editable-design conversion
- ✦NoteSlide: PDF and image slides to editable PowerPoint or Keynote
- ✦Figma-to-code generation
- ✦Image-to-vector/SVG and PSD/web-to-Figma import
- ✦Visual Struct API for developers
- ✦Codia AI Vision layout and typography reconstruction
- ✦Automatic flaky test detection and quarantining
- ✦AI-powered failure analysis and duplicate detection
- ✦Anti-flake protection in the merge queue
- ✦Batching up to 100 PRs with auto-bisection on failure
- ✦Parallel merge queues for non-overlapping changes
- ✦Integrated ticketing with Linear/Jira and Slack alerts
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Speeding up coding with AI completions
- →Generating code from plain-language prompts
- →Getting in-editor help and explanations
- →Reviewing pull requests with AI
- →Understanding unfamiliar codebases
- →Automate mobile app UI regression tests
- →Run tests in parallel across many devices
- →Integrate UI testing into CI pipelines
- →Let AI agents generate and run app tests
- →Rebuild UI screenshots into editable Figma layers
- →Turn NotebookLM PDFs into editable decks
- →Convert images and posters into reusable design assets
- →Move designs between Figma and Canva
- →Extract layout structure via API
- →Eliminating flaky test re-runs that slow down CI
- →Managing high-volume PR merges in a monorepo
- →Getting visibility into which tests impact the most pull requests