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Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Converts screenshots, PDFs, and slides into editable Figma, PowerPoint, or Canva designs and turns Figma layouts into code.
AI app builder that turns plain-English prompts into deployable full-stack web apps with a managed database and full code ownership.
No public pricing
No public pricing
No public pricing
No public pricing
Free trial available
- ✦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
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
- ✦Natural language to SQL conversion
- ✦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
- ✦Builds full-stack apps from plain-English descriptions
- ✦Choice of 12+ underlying AI models
- ✦Managed Supabase database included
- ✦GitHub code export on all plans
- ✦One-click Vercel deployment
- ✦Credits that don't expire while subscribed
- →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
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Generating SQL queries from text descriptions.
- →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
- →Non-technical founders shipping an MVP quickly
- →Agencies delivering client projects faster
- →Developers prototyping SaaS ideas without boilerplate setup
- →Solo builders launching small businesses without hiring engineers