Dashboard-driven pipeline lifecycle

Trigger and manage pipelines directly from the web interface.

ZenML dashboard displaying machine learning pipeline runs and experiment tracking with statuses and components.

One-click pipeline deployment

Build, push, and launch pipelines with different configurations effortlessly. No need to set up your local environment. No-code, one-click launch of ML pipelines.

"ZenML pipeline diagram showcasing process flow for model training and deployment, ideal for MLOps and automated machine learning."

Pipeline Run Templates

Create reusable templates of pipelines and share across technical and non-technical members to trigger from dashboard. Create repeatable, reprodubile pipeline runs without breaking a sweat!

Advanced pipeline scheduling (coming soon)

Set up complex scheduling rules for automated pipeline runs, without relying on the underlying orchestrator.

ZenML allows you to keep your ML pipeline code cloud-agnostic, enabling faster future migrations to another technology stack. The management of the metadata and artifacts generated at each step is seamless, and allows the user to extend the framework if needed without much effort.

Gabriel Martin

Machine Learning Engineer at Frontiers

Unify Your ML and LLM Workflows

Free, powerful MLOps open source foundation

Works with any infrastructure

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Dashboard displaying machine learning models, including versions, authors, and tags. Relevant to model monitoring and ML pipelines.