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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Sherpa Coder logo
Sherpa Coder
✓ verifiedFree

VS Code extension letting developers chat with their own custom OpenAI assistants without leaving the editor.

GitLoop logo
GitLoop
✓ verifiedFree trial

AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.

11K visits/mo2.7K saves
Workik logo
Workik
✓ verifiedFreemium

AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.

210K visits/mo
Magic Patterns logo
Magic Patterns
✓ verifiedFreemium

AI prototyping tool that generates UI matching your design system, letting product teams test features fast.

242K visits/mo3.8K saves
Banani logo
Banani
✓ verifiedFreemium

AI copilot that turns text or references into editable, multi-screen UI prototypes exportable to Figma or code.

419K visits/mo13K saves
Pricing

No public pricing

No public pricing

Free trial available

Trial: $0/month (20 AI requests on signup, 7 requests/day, 50 free flow runs, up to 3 users)
Starter: $15/month billed annually or $25/month (20M standard AI tokens, 1,000 flow runs)
Premium: $30/month billed annually or $50/month (40M standard + 4M advanced AI tokens, 3,000 flow runs)
Elite: $80/month billed annually or $150/month (100M standard + 10M advanced AI tokens, 10,000 flow runs)
Tailored: $62/month (custom AI token allocation)

Free trial available

No public pricing

No public pricing

Free trial available

Core features
  • 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
  • Chat with your repositories
  • Natural-language codebase search
  • Fast code indexing
  • AI pull-request and commit review
  • Automated documentation generation
  • AI unit-test generation
  • Automatic context-gathering from connected engineering sources
  • AI-generated code, tests and pull requests from tickets
  • Task planning that breaks complex work into subtasks
  • Auto-updating engineering documentation
  • Vector search over embedded project data
  • Multiple selectable AI models (GPT, Gemini, Claude, Llama, etc.)
  • Engineering productivity analytics dashboard
  • AI UI generation from prompts
  • Match existing styling and design systems
  • Rapid, high-fidelity prototyping
  • Live team editing and sharing
  • Enterprise security and compliance
  • Text-to-UI prototype generation
  • Design from image or Figma references
  • Interactive multi-screen prototypes
  • Conversational AI editing
  • Export to Figma, HTML/CSS, images
  • MCP access for coding agents
Use cases
  • 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
  • Onboard new developers to a codebase
  • Resolve bugs faster
  • Generate docs and tests automatically
  • Review pull requests with AI
  • Engineering teams automating ticket-to-PR workflows
  • Developers wanting AI-assisted debugging and test generation
  • Engineering managers tracking AI-driven productivity gains
  • Teams centralizing documentation from scattered sources
  • Prototype new product features
  • Test designs with customers
  • Build design-system-consistent mockups
  • Rapid UI wireframing
  • Prototyping product screens
  • Recreating a reference UI
  • Handing designs to developers
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