Observability

Unified model lifecycle management

Deploy, monitor, and update all ML models from a single dashboard
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Dashboard displaying machine learning models, including versions, authors, and tags. Relevant to model monitoring and ML pipelines.

Unified model lifecycle management

Deploy, monitor, and update all your ML models from a single dashboard. Track performance, accuracy, and health in real-time.
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Dashboard mockup

Track metrics and metadata

Track and visualize model metrics and metadata such as LLM prompts, centrally in one place.

Automated model governance

Implement version control, approval workflows, and audit trails for your ML models effortlessly.
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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
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Dashboard displaying machine learning models, including versions, authors, and tags. Relevant to model monitoring and ML pipelines.
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