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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.

2.6K visits/mo
Continue logo
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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
Runcell - Jupyter AI Agent logo
Runcell - Jupyter AI Agent
✓ verifiedFreemium

Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.

170K visits/mo5.5K 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

No public pricing

Starter Plan: $1.99/mo
Expert Plan: $5.99/mo
Pro Plan: $2.99/mo

No public pricing

Free trial available

Core features
  • Natural language to SQL conversion
  • Open-source AI code assistant
  • Customizable autocomplete
  • In-editor AI chat
  • Community-built coding agent
  • Cross-session project memory recalling prior decisions and state
  • Autonomous execution of long, multi-step notebook tasks
  • Reads cell outputs (plots, tables, metrics), not just code
  • In-notebook cell-level assistance and error fixing
  • Installs directly into existing JupyterLab via pip, no new editor
  • Concept explanations with runnable example cells
  • AI-Powered SQL Query Generation
  • No-Code SQL Builder
  • SQL Syntax Explainer
  • SQL Optimizer
  • SQL Formatter
  • SQL Syntax Validator
  • NoSQL Query Builder
  • 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
  • Generating SQL queries from text descriptions.
  • Get AI code completions while coding
  • Ask questions about code in the editor
  • Build on an open-source coding-agent foundation
  • Data scientists running multi-week model iteration projects
  • Domain experts (e.g. risk/fintech) who know the problem but not deep Python
  • Researchers wanting an agent that remembers project context across days
  • Analysts needing help understanding unfamiliar algorithms or libraries
  • Generating complex SQL queries without SQL knowledge
  • Understanding and decoding intricate SQL queries
  • Optimizing SQL queries for faster results
  • Formatting messy SQL code for readability
  • Validating SQL syntax to prevent errors
  • Generating NoSQL queries without manual coding
  • Rapid UI wireframing
  • Prototyping product screens
  • Recreating a reference UI
  • Handing designs to developers
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