Build with Notebooks
More than Jupyter. MINEO Notebooks combine Python, interactive widgets, AI blocks on any model, and one-click Data Apps — collaborative and governed.
Quarterly breakdown by region with growth projections.
df = mineo.query("SELECT region, SUM(revenue) FROM sales GROUP BY region")
px.bar(df, x="region", y="revenue", title="Q4 Revenue")
Key insight: North America drives 43% of total revenue. APAC showed the strongest growth at +23% QoQ, driven by expansion in Japan and Australia.
df.sort_values("revenue", ascending=False).head()
| Region | Revenue | Growth |
|---|---|---|
| North America | $1.8M | +12% |
| Europe | $1.1M | +8% |
| APAC | $820K | +23% |
| LATAM | $480K | -3% |
From notebook to Data App
Author in Python, enrich with visual controls, and ship the same notebook as a polished Data App.
Compose with blocks
Mix code, markdown, assistant, widgets, and snippets inside one notebook.
Run in an isolated worker
Each session gets its own encrypted execution context, kernel state, logs, and packages.
Share, collaborate, deploy
Work with your team in real time, keep version history, and publish as a live Data App.
Everything lives in one notebook
MINEO notebooks are not just code cells. They are a structured workspace for analysis, controls, documentation, and AI-assisted work.
Code, markdown, and snippets
Write Python, document your logic, and reuse common building blocks without leaving the notebook.
Widgets and layouts
Add SQL queries, charts, KPIs, forms, uploads, and layouts to turn notebooks into interactive user-facing experiences.
Assistant blocks
Use MINEO Assistant directly inside the notebook to explain, generate, and refine code or analysis block by block.
A runtime designed for real work
The notebook experience is backed by isolated workers, managed kernels, project context, and APIs that let notebooks orchestrate more than just cells.
Isolated worker per session
Notebook sessions run in their own workers with encrypted communication and session-specific context.
Kernel state, variables, and queries
Keep shared context across blocks, inspect memory and logs, access project variables, and query data sources or workbenches from code.
Install packages when needed
Bring extra Python packages into the running worker and keep moving without rebuilding infrastructure.
Resources
Link notebooks to project files and resources so outputs connect cleanly to the rest of your workspace.
Variables
Use project and environment variables directly inside notebooks and snippets.
Version control
Track notebook evolution with built-in version history and Git-oriented workflows.
Collaboration
Work with teammates in the same notebook using comments and real-time editing.
Turn notebooks into live Data Apps
A notebook can stay technical for builders and still become a polished Data App for stakeholders. Layouts, widgets, and app mode close that gap.
Data App-ready layouts
Structure blocks into cleaner interfaces that feel like Data Apps, not raw notebooks.
Interactive controls
Let Data App users filter, upload, select, and explore without touching code.
Deploy as live Data Apps
Publish the same notebook as a production-ready Data App without rebuilding it somewhere else.
Go deeper with the documentation
Technical references, implementation details and examples for teams building on MINEO.
Part of MINEO, the governed AI Workspace
Every MINEO product runs on one multi-model platform: use any AI model, keep your data protected and stay EU-compliant — with no vendor lock-in.
Build your first notebook and Data App on MINEO
Start with Python, add widgets and assistant blocks, then ship it as a live Data App.