Python analytics
in the cloud 
made easy

Collaborate, Deploy, Deliver.


How it Works

Shared notebooks.

Larger than memory datasets.

Instant deployment.

Build your data pipelines and models with the Python tools you already know and love. omega|ml makes working with the cloud fully Pythonic:


Publish models & datasets from code or using our cli
om.models.put(model, ‘sales-prediction’)
om.datasets.put(dataframe, ‘sales-data’)


Use the cloud for data processing & model training 

om.runtime.model('sales-prediction').fit(X, Y)


Leverage the instant REST API from any application:
HTTP GET /api/v1/model/sales-prediction/predict
HTTP PUT /api/v1/dataset/sales-data/

Any Framework

These frameworks are supported out of the box. Any framework can be supported using plugins.


What is Included

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Fully installed, customizable Python data science distribution

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Scalable compute cluster for model training & prediction

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Scalable NoSQL database for any-size data sets

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Instant REST API for data, models, reports

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Secure Jupyter Notebooks ready for collaboration

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Notebook scheduling for controlled batch execution


Cloud & Enterprise Add-on Features

  • Jupyter Notebook publishing as reports and presentations

  • Instant Plotly Dashboard deployment

  • Mini batch framework for streaming and IoT data

  • Run on Apache Spark or Anaconda Distributed cluster

  • Deployment integration for any cloud backend

  • Enterprise-grade security

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Why omega | ml



Leverage Python machine learning models & pipelines in any application, straight from our easy-to-use REST API



Collaborate instantly on any data science project, using the tools you love (e.g. Python, scikit-learn, Jupyter Notebook)



Scale model training and prediction from any client, applying the power of the built-in compute cluster



Large-scale datasets at a fraction of the cost of other solutions (no need to run Apache Hadoop or Spark)​


No Vendor Lock-in

Our fully open source core and support for any Kubernetes cloud means you can deploy anywhere.


Secure & Independent

Our compute center in Switzerland meets all your data privacy and security requirements.


From Your Lab to Production

omega|ml is your one-stop hub to build, productize and launch your AI/ML project

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More and much faster:

Data Scientists continue working with  the Python tools they trust & love.


Working right out of Jupyter Notebook or any other IDE, omega|ml does not stand in your way. Yet it is always ready to deploy and collaborate on datasets and models.


All it takes is a single line of code.

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Collaborate easily:


Ever wondered where to store all those .csv files? How to share your  notebooks? How to persist and deploy your models?


Sure there are ways. But they are all complicated.


omega|ml provides collaboration out of the box, for datasets, models, pipelines and applications

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Launch your app today:

Want to integrate your datasets and models into an application? Don’t waste weeks or months to build your own. omega|ml is ready in minutes.


omega|ml publishes datasets, models and dash apps with a single line of code.  Once published you get a nice, ready-to use REST API and app URLs. Scheduled data pipelines included.

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Leverage Swiss cloud power:


The built-in compute cluster provides instant, no-hassle, scalable model training and prediction. Support for Dask Distributed, Hadoop and Apache Spark is available free of charge.


As a private or public IaaS/PaaS provider, deploy omega|ml Enterprise Edition to offer your clients a scalable Data Science and ML Platform As a Service

Extensible Architecture

Storage & Compute Backends, DataFrame Operations

omega|ml comes with batteries included, however new requirements are not a problem: alternate data sources or sinks and data pipelines can easily be added.

The following extension points are available:

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Extend what  objects can be stored and retrieved

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Add any compute backend to run any omega|ml-stored models through the same API

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Add processing options such as AutoML or Model Visualization