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Jupyter-native AI agent that remembers a data project across sessions and reads chart/plot outputs, not just code.
Self-hosted cloud development environments and AI-agent governance, letting enterprises run coding agents on their own infrastructure.
No-code AI platform that builds full-stack apps, websites and agents from plain-language prompts with hosting built in.
AI prototyping tool that generates UI matching your design system, letting product teams test features fast.
AI design engineer that designs UIs on a canvas and ships production frontend code in your own stack.
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- ✦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
- ✦Self-hosted workspaces with desktop and web IDEs
- ✦Coder Agents run coding agents on isolated infrastructure
- ✦AI Governance gateway for LLM usage control
- ✦SSO (OpenID Connect) and role/group sync
- ✦Audit logging and resource quotas
- ✦Multi-organization access controls
- ✦High availability and workspace proxies
- ✦Prompt-to-app full-stack generation
- ✦Built-in backend, database and auth
- ✦One-click integrations (Slack, Notion, HubSpot, etc.)
- ✦Instant hosting and custom domains
- ✦Superagents for automated workflows
- ✦GitHub sync and code export
- ✦AI UI generation from prompts
- ✦Match existing styling and design systems
- ✦Rapid, high-fidelity prototyping
- ✦Live team editing and sharing
- ✦Enterprise security and compliance
- ✦Design UIs on an infinite canvas
- ✦Production frontend code in your stack (400+ libraries)
- ✦Reuses your components, tokens, and hooks
- ✦In-browser editing with DevTools context
- ✦Design and code stay synced in your repo
- ✦Asset and animation generation
- →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
- →Standardize developer environments
- →Run AI coding agents securely on-prem
- →Enforce governance and compliance
- →Cut VDI costs
- →Speed up developer onboarding
- →Building internal tools and dashboards
- →Launching websites and landing pages
- →Creating customer portals and CRMs
- →Deploying AI agents that automate tasks
- →Prototype new product features
- →Test designs with customers
- →Build design-system-consistent mockups
- →Turning designs into production frontend code
- →Building landing pages and product UIs
- →Refining UI directly in the browser
- →Keeping design and code in sync