ZenML Features: Your MLOps Framework Solution

Tired of setting up new MLOps tools, doing manual deployments, or having non-reproducible experiments? Use ZenML MLOps Framework to transform your ML workflows into production-ready solutions.

Increased collaboration

Modular code for immediate production-ready ML projects.
Dependency management and automated dockerization
Simple templates for common ML paradigms.
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Reproducible machine learning

Automated data versioning of common ML artifacts (pandas, polars, pytorch datasets, etc)
50+ Integrations with the most popular cloud and open-source tools
Automated lineage and provenance

Optimized infrastructure bill

Develop locally and deploy on the cloud only when you need - massively reducing cloud dependencies and spend!
Deploys on any machine learning infrastructure like AWS Sagemaker, Google Vertex AI orAzureML Platform.
Model lifecycle management with integration into popular experiment tracking and model registry tools like MLflow, Weights & Biases, and Neptune.
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Increased security & compliance

Separate config from code with modular settings
Centralized credentials management
Secret management integrated with Vault, GCP Secret Store, AWS Secrets Manager, and more

Observability over the entire ML lifecycle

Comes with a beautiful UI for full observability and collaboration between teams.
Set up data quality gates and embed visualizations with your reports
Create alerts and monitoring for your machine learning pipelines.
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Write local, run anywhere

Write your core machine learning workflow code locally, and run it anywhere.

Simple, straightforward syntax

Easy to use, beginner-friendly syntax

Unified end-to-end

Our MLOps Framework provides a unified approach, covering the entire ML lifecycle from training to deployment.

No vendor lock-In

Use the tooling and infrastructure best suited to your use-case.

Standardized & reproducible ML

Best practices baked into your ML development from the start.

Open, extensible, integrated

ZenML integrates with your favorite ML tooling out-of-box.