A framework for real-life ML, AI, and data science

Open-source Metaflow makes it quick and easy to build and manage real-life ML, AI, and data science projects.

  • Modeling

    Use any Python libraries for models and business logic. Metaflow helps manage library dependencies, locally and in the cloud.
  • Deployment

    Deploy workflows to production with a single command and integrate with other systems through events.
  • Versioning

    Metaflow tracks and stores variables inside the flow automatically for easy experiment tracking and debugging.
  • Orchestration

    Create robust workflows in plain Python. Develop and debug them locally, deploy to production without changes.
  • Compute

    Leverage the cloud to execute functions at scale. Use GPUs, multiple cores, and large amounts of memory as needed.
  • Data

    Access data from data warehouses. Metaflow flows data across steps, versioning everything on the way.

Metaflow is used by these companies and hundreds of others

Metaflow is built for ML/AI engineers and data scientists, not just for machines

Bring your own Cloud

Get started easily on a laptop. When you are ready to scale, deploy the Metaflow stack on your cloud account or on-premise Kubernetes cluster. Metaflow integrates seamlessly with your existing infrastructure, security, and data governance policies.

To get a taste of Metaflow in the cloud, try Metaflow Sandbox in the browser.

Battle-hardened at Netflix

Metaflow was originally developed at Netflix to address the needs of developers and data scientists who work on demanding real-life ML, AI, and data projects. Netflix open-sourced Metaflow in 2019.

Today, Metaflow is used by hundreds of companies across industries, powering diverse projects from state-of-the-art GenAI and compute vision to business-oriented data science, statistics, and operations research.

How leading ML, AI, and data science teams use Metaflow

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A framework for real-life ML, AI, and data science