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Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
AI app builder that turns chat prompts into working web apps and sites, with credit-based build and deploy.
Marketplace and no-code builder for AI mini-apps and chatbots, with one-place access to many models and embeds.
No public pricing
No public pricing
Free trial available
No public pricing
- ✦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
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦Chat-to-app and website generation
- ✦Real-time prototype building
- ✦One-click deploy and hosting
- ✦Templates to start projects
- ✦Credit-based building with shared workspaces
- ✦You own your code and data
- ✦Access to many AI models in one place
- ✦Create no-code AI mini-apps and chatbots
- ✦Community app/game marketplace
- ✦Embed apps on websites
- ✦Image, audio and video generation apps
- →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
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Build web apps without coding
- →Prototype product ideas quickly
- →Create landing pages and sites
- →Ship internal tools
- →Building custom AI chatbots
- →Discovering community AI apps
- →Embedding AI apps on a site
- →Generating images, music and text