A better Python Notebook to scale and grow

Collaborate, develop and share your Python supercharged notebooks in a production-ready environment powered by Code, No-Code & AI.

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Data science notebook

A better Python Notebook

MINEO takes Jupyter notebooks to the next level by adding production-grade features such as: layouts, no-code widgets, integrated SQL/data sources, versioning, collaboration tools, integrated filesystems, detailed permissions and AI.

People with data

Connect people and insights

Transform traditional Python notebooks into interactive data applications. Easily share insights, foster collaboration, and drive action with a modern, data science-focused platform.

Data Pipeline

Data Pipelines

Automate and streamline your workflows with Python-based data pipelines that leverage the power of notebooks. Combine one or more notebooks to create ETL Pipelines based on your existing Python libraries.


Start coding right now

Skip the configuration of large installation environments on your computer like Anaconda and get straight to the content in reproducible environments based on Docker images accessible with just a browser and GPU-ready.

Meet your new Super Powers.

MINEO expands traditional Jupyter Notebooks apps
into a powerful cloud platform to build and share data apps.

Supercharged Notebooks
Build and deploy supercharged Python Notebooks powered by Code, No-code & AI.
Dashboards icon
Convert Python notebooks into beautiful dashboards powered by Code, No-code & AI.
Data pipelines
Data Pipelines
Run python notebooks with your desired frequency or combine multiple notebooks to create pipelines.
MINEO Assistant
Streamline data apps with AI-powered code guidance, insightful data interpretation, and advanced text editing.
Design first
Adjust and perfect every design detail of the notebooks, from colors and sizes to paddings and backgrounds.
Data sources
Connect MINEO to databases and files using just the credentials.
Data Observability
Measure and track the quality of your data using machine learning 🤖 and custom business rules.
MINEO Workbench provides an easy way to build SQL queries and analyse your data without any development time.
Manage your organization
Manage your entire organisation with fine-grained permissions (ACL) in one platform.
Reproducible environments
Run your data apps in dockerized environments with support for the installation of any package you like.
Integrated Filesystem
Organise your data and files with a full-featured file system accessible from notebooks.
Scalable platform
Dynamic scaling of your resources, providing environments for any size including GPUs.

MINEO in action for Data Scientists.

Real examples of how MINEO can improve Data Science projects.

Charge Monitoring

A data app that manages an electric charger grid network

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A tiny vision language model that kicks ass and runs anywhere

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Face Recognition Demo

Dashboard that uses pre-trained facial recognition models to demonstrate the capabilities of local models integrated into dashboards.

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Clustering exploration

An overview of different clustering algorithms

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Image Generation

Image Generation web app powered by Stable Diffusion models.

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Audio Generation with Bark

Audio Generation Data App with Bark.

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Introduction to Scikit-Learn: Machine Learning with Python

An introduction to Machine Learning using the package scikit-learn with python.

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Retail sales forecast

Forecasting of retail sales including treating holidays and anomalies.

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Linguistic analysis of Moby Dick with NLTK

Linguistic analysis of Moby Dick with NLTK, Python and Mineo Widgets.

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Webscraping with Python

Tutorial of how to autoscrape a website with autoscraper package.

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Access datasources from notebooks

Notebook that explains how to access datasources from notebooks.

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Python Data Visualizations

A nice tutorial that explains how to use matplotlib, seaborn and pandas.

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COVID-19 Visualization & Prediction

Prediction and visualization of COVID-19 global pandemy.

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Unleashing the Power of Large Language Models (LLMs) on Consumer Hardware

This notebooks shows how to use a local instance of GPT2 model inside MINEO without any external service.

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