Get an overview of your entire ML lifecycle through a unified user interface to increase transparency and reduce handover points across your organization.
Improve cross-team collaboration as you develop to production
Bridge knowledge gaps via a unified user interface that contains detailed information about all areas of the ML lifecycle.
Enable your developers to focus deeply on what they do best by decoupling code development from infrastructure and tooling.
Sensible and intuitive abstractions make it easier to comprehend and use the work of your colleagues.
Visually browse and explore all parts of your company’s ML lifecycle
View your ML code, infrastructure, and tooling in an intuitive user interface.
Drill down into detailed visualizations of your pipeline runs to gain insights and identify areas for improvement.
Detailed lineage information allows you to see exactly by which code and infrastructure a given model was produced.
Organize and manage all your MLOps tooling and infrastructure in one place
Supercharge your ML workflows with the latest best-in-class tools from all areas of MLOps.
ZenML’s standard interfaces ensure that your tools work together seamlessly.
Adjust your tooling to your needs and add or switch out components as your setup matures.
Many, many teams still struggle with managing models, datasets, code, and monitoring as they deploy ML models into production. ZenML provides a solid toolkit for making that easy in the Python ML world
Chris Manning
Professor of Linguistics and CS at Stanford
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