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Learn more about Domino’s enterprise MLOps platform

Connect with Domino product experts and see a live, personalized demo

I want to learn more

Dive into the product and see why over 20% of the Fortune 100 has chosen Domino to unleash data science. During this live demonstration you’ll see how the Domino Enterprise MLOps platform is used for key data science tasks:

Data science development

Data science development

Get an introduction to the powerful workbench capabilities that give data scientists self-serve access to the tools and infrastructure they need to accomplish the most challenging data science projects – without DevOps complexity.

Collaboration and project management

Collaboration and project management

See how Domino enables teams of data scientists using different tools to seamlessly collaborate on a project, with the ability to leverage valuable insights, reproduce prior work, and harvest collective wisdom.

Model publishing

Model publishing

Learn the four different ways to turn models into end-user assets that can be used by anyone in an organization to make better decisions and transform the way their business operates.

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Hear from our customers

“If we hadn't invested in Domino first, I wouldn't have been able to set up a team at all, because you can't hire a high-skilled data scientist without providing them with the state of the art working environment.”

Chief Analytics Officer

Insurance

“For our COVID-19 research, we needed to work with external academics and hospitals. We brought them into Domino as collaborators and they were able to get up and running very quickly without any issues. We were feeding them our data and they were able to start developing deep learning models to help us predict hotspots and other things. That work went very efficiently because of Domino’s collaboration tools.”

Director of Data Platforms

Pharmaceuticals

“The biggest piece is collaboration. Having multiple people working in the same project and having all your data and code in the same box has been huge. It's a big way that people share code and insights across their teams, especially data science teams, and that's been a really nice thing.”

Cloud Analytics Lead

Agriculture

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