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Data Analytics__data Labeling Training Data__managed Annotation ServicesSoftware Development__coding Assistants Copilots__code Chat Q ASoftware Development__code Generation__frontend GenerationData Analytics__data Labeling Training DataSoftware Development__coding Assistants Copilots__ide CopilotsSoftware Development__code GenerationSoftware Development__coding Assistants CopilotsData Analytics
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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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Sherpa Coder
✓ verifiedFree
VS Code extension letting developers chat with their own custom OpenAI assistants without leaving the editor.
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Appen
✓ verifiedPaid
Long-standing provider of human-labeled, expert-validated training data and model evaluation services for building frontier AI.
👁 1.2M/mo
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Magic Patterns
✓ verifiedFreemium
AI prototyping tool that generates UI matching your design system, letting product teams test features fast.
👁 242K/mo♥ 3.8K
Pricing
No public pricing
No public pricing
No public pricing
No public pricing
Core features
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦in-editor chat with OpenAI assistants
- ✦workspace source-code context sharing
- ✦support for custom, user-defined assistants
- ✦secure management of the user's OpenAI account
- ✦Frontier alignment data (RLHF, SFT, red teaming)
- ✦Speech and audio data
- ✦Multimodal / VLM annotation
- ✦Physical AI data (LiDAR, robotics, sensor fusion)
- ✦Model integrity, bias and hallucination audits
- ✦1M+ vetted contributors, 500+ locales
- ✦SOC2 and ISO 27001 certified
- ✦AI UI generation from prompts
- ✦Match existing styling and design systems
- ✦Rapid, high-fidelity prototyping
- ✦Live team editing and sharing
- ✦Enterprise security and compliance
Use cases
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →getting coding help without switching out of VS Code
- →using a personalized OpenAI assistant tuned to a project
- →quick in-editor Q&A while writing code
- →Source training data for AI models
- →Evaluate and benchmark models
- →Annotate multimodal and sensor data
- →Run safety and bias audits
- →Prototype new product features
- →Test designs with customers
- →Build design-system-consistent mockups
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