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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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Maestro Studio Desktop Beta
✓ verifiedFreemium
Open-source framework for automated end-to-end UI testing of mobile and web apps, with a paid cloud for parallel device runs.
183K visits/mo
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Apify
✓ verifiedFreemium
Full-stack platform for web scraping, data extraction, and automation; category leader.
4.4M visits/mo2.0K saves
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PTE APEUni
✓ verifiedFreemium
AI-scored practice platform for PTE Academic and PTE Core exam prep, with question banks, predictions and study tools.
2.1M visits/mo
Pricing
No public pricing
No public pricing
Local: $0 (open source)
Cloud: $250/device/mo (parallel runs)
Free trial available
Free: $0/mo ($5 included usage)
Starter: $29/mo ($26/mo billed annually)
Scale: $199/mo ($179/mo billed annually)
Business: $999/mo ($899/mo billed annually)
Free trial available
No public pricing
Core features
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦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)
- ✦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
- ✦Web scraping
- ✦Data extraction
- ✦Browser automation
- ✦AI agents
- ✦Anti-blocking
- ✦Proxy rotation
- ✦Open-source tools (Crawlee)
- ✦Ready-made tools and code templates
- ✦AI scoring for speaking and writing
- ✦Full PTE question-type practice
- ✦Weekly exam prediction files
- ✦Vocabulary books and shadowing tools
- ✦AI study plan and score analysis
- ✦Web and mobile app sync
Use cases
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →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
- →Data for generative AI
- →Lead generation
- →Market research
- →Sentiment analysis
- →Preparing for PTE Academic/Core exams
- →Practicing speaking and writing with AI feedback
- →Studying likely exam questions
- →Tracking prep progress
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