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UbiOps

Run your data science code live in the cloud

Page last modified
Saturday, June 12, 2021 - 13:00

UbiOps is an easy-to-use deployment and serving layer for your data science code. Run your Python & R models and scripts live and use them from anywhere at any time. UbiOps is currently used as a backend to optimize heat networks by Gradyent. Furthermore BAM energy systems uses UbiOps to predict energy usage of buildings and builds their services on top of that.

Pro/con

Up to 80% reduced time to market
No in-depth IT knowledge required
Support for complex pipelines
Automatic API endpoint creation
Your code is automatically containerised and deployed on Kubernetes
Available as SaaS or on-prem version
As you don't have to install and maintain kubernetes clusters, you give away some control of how this is done. You do have the option to set minimum and maximum amount of active instances
We support Python and R, but not any other languages

Specification

Compatibility UbiOps serves and hosts any code (Python and R) as a micro-service with an API endpoint.
Automation Every piece of code that you upload is automatically deployed to a kubernetes pod, making it scalable depending on your specifications.
Modular Design Every piece of code is containerised and any dependencies are installed in a container too.
Monitoring Using the integrations with various monitoring tools, you can measure accuracy, F1 scores, data drift and explain local predictions.
Training Using the integrations with ML services, Sagemaker and other training tools, you can easily push your model from the training environment to production with Ubiops.
Business Efficiency UbiOps speeds up the time to market of your data science projects.

Relative Business Impact

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Technology Readiness Level

[9/9]

Development Technology demonstration Mature / Proven
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About UbiOps

UbiOps is an easy-to-use deployment and serving layer for your data science code. Run your Python & R models and scripts live and use them from anywhere at any time.

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