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Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Agentic terminal and cloud agent platform (Warp Terminal, Warp Agent, Oz) for developers orchestrating Claude Code, Codex, and other agents.
Converts screenshots, PDFs, and slides into editable Figma, PowerPoint, or Canva designs and turns Figma layouts into code.
No public pricing
No public pricing
No public pricing
No public pricing
- ✦CSV to API conversion
- ✦Data parsing (CSV to JSON)
- ✦Filtering capabilities
- ✦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
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦Modern terminal rebuilt for agentic coding workflows
- ✦Warp Agent with multi-agent orchestration and model routing
- ✦Oz platform for launching agents into the cloud via SDK, CLI, or terminal
- ✦Codebase indexing and granular permission controls
- ✦Team-wide usage visibility and spend/credit caps
- ✦Open-source terminal core
- ✦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
- →Sharing CSV data with a team via an API
- →Creating a public API from CSV data
- →Filtering and accessing specific data within a CSV file programmatically
- →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
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Developers who want an AI-assisted terminal for daily coding
- →Teams orchestrating multiple coding agents (Claude Code, Codex) together
- →Engineering orgs needing governance over agent-driven development
- →Companies moving agent workflows from local machines to the cloud
- →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