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    Loved by data scientists, trusted by IT

    Domino is a unified platform that orchestrates the end-to-end data science lifecycle, using your preferred tools and existing data, across hybrid multicloud infrastructure. Domino accelerates time to value from AI, increases collaboration, and makes it easier to manage compliance, security and cost.


    The Domino difference

    Freedom for Data Scientists and Analysts

    Self-serve access to any tool, data or languages with powerful auto-scaling CPU & GPU infrastructure

    Integrated workflows streamline exploring, experimenting and deploying to production

    Delight, retain, and upskill everyone to achieve more, together

    and Collaboration

    Multi-persona collaboration and knowledge sharing accelerates business value as you scale

    Integrated project management provides leaders visibility towards business goals

    Exact reproducibility of work improves accuracy, efficiency and lowers regulatory risk

    Control for IT

    Unified platform streamlines security, access control and policy management to improve efficiency

    On-premises, hybrid or multi-cloud deployment enables balancing costs, performance and scale

    Granular governance and access controls for IT reduces cost and risk

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    Return on

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    cost savings

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    Reduction in model deployment time

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    Faster deep learning
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    Trusted by Fortune 100 companies worldwide

    Lockheed Martin
    Lockheed achieved a 10x increase in productivity and a $20M per year cost reduction through Domino's self-service capabilities.
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    Greater collaboration and choice of tools for Bayers' 500+ data scientists across the globe accelerates the pace of research to help farmers grow crops more efficiently.
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    Johnson & Johnson/Janssen
    10X faster development of deep learning models puts Janssen researchers one step closer to delivering precision medicine.
    Learn more

    Data science resources worth exploring

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    2022 Gartner Market Guide for DSML Engineering Platforms
    The Complete Guide to Enterprise MLOps Principles