Deployment and Monitoring for Any Model

Deploy models from anywhere

Serve models built in any language, framework, or training tool with Modzy.

Monitor ML for peak performance

Keep track of usage, drift, and latency so your models perform at their best.

From laptop to live model in minutes

Modzy for Data Scientists

The MLOps platform that saves you time

We don't think you should have to learn Kubernetes (unless you want to!)


Deploy your models in minutes

Quickly deploy the models you've trained into scalable services.


Choose your own MLOps tooling

Modzy works with whichever labeling, training, and pipeline tools you like to use.


Keep track of your models in prod

Monitor, manage, and update your models whenever you need.

Join the over 1000+ strong Modzy Developer Community.

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Features for data scientists

No/low-code deployment

Turn your models into scalable services with no extra work.

Model serving

Serve models on AWS, Azure, on-prem, or on edge devices.

Drift detection

Keep an eye out for errant models with data drift and model drift monitoring.


See how your models are making their prediction in prod to spot overtraining and other issues.

ML tool integrations

Integrate your favorite ML tools like Snowflake, LabelStudio, and SageMaker.

Model library

Curate all your models with documentation, performance stats, API details, and "test drive" functions.

Learn more

See how else Modzy can help you get the most out of your ML models.

Learn how ModelOps helps organizations deploy, run, and scale ML models

Automating the model deployment pipeline can help organizations improve efficiency, increase reliability, and monitor performance.

An overview of current approaches to AI explainability, and an easier way to incorporate it into your AI pipelines.

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Build AI Powered Solutions Faster

Deploy, connect, and run machine learning models in the enterprise and at the edge

Build AI Powered Solutions Faster