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