Deploy Machine Learning in Minutes

Modzy MLOps platform for businesses to deploy, manage, and get value from AI

MLOps platform to deploy, integrate, run, and monitor AI—anywhere. Unmatched platform features to manage the full lifecycle of trained AI models—Modzy is powering AI for the enterprise.

Easy to get started

Watch Video Demo

See how to quickly deploy and run models, connect to pipelines, autoscale resources, and integrate into workflows with Modzy

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See Modzy in action with real use cases, and get all your questions answered with Modzy engineers in your private demo

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Experience all the features of the Modzy MLOps platform for production-ready AI for enterprise and edge
Modzy MLOPs platform easily integrates into your tech stack

Powerful integrations

Modzy MLOps platform integrates with your favorite tools, machine learning training frameworks, data pipelines, CI/CD systems, and front-end applications. Fits within your existing tech stack, with flexibility for the future.

ML Training frameworks

Data Pipelines & CI/CD Systems

Business applications


Modzy deploys anywhere

The only MLOps platform with the power to deploy anywhere. See the many deployment options in action with a Modzy demo.

On-Premises

Scale MLOps in your own infrastructure, data center, or multiple locations

Cloud

Use your own private cloud and existing security policies on AWS, GCP, or Azure

Hybrid

Use multiple cloud providers at the same time, or mix your infrastructure with cloud

Air gap

Scale Modzy in disconnected and physically separated environments

Edge

Use any x86 or ARM device to bring MLOps across your edge infrastructure

No code model deployment

Make your model production-ready with one of our no-code integrations, or if you already have a container, import it directly.


Autoscale and pipeline MLOps

Autoscale infrastructure of choice — on-premise, cloud, edge, or hybrid with deployment pipelines to common CI/CD systems.


Train, experiment and test-drive

Train using your favorite training frameworks and auto-pipeline into Modzy projects for full ModelOps capability. Test-drive models for accuracy, precision, and infrastructure performance.


Manage and govern all your AI assets

Single pane of glass

See all the models your organization created or licensed from leading AI companies. Workflows, approvals, auditing, performance tuning, and full governance to control costs and create value from AI.

Transparency, not guesswork

Curate different versions of models, complete with training data linage, model architectures, CI/CD integration to existing workflows, and detailed performance metrics. Transparency of model performance, characteristics, and usage over time.


Edge AI on any x86 or ARM device

Deploy and manage thousands of device types with standard API to serve models on any x86 or ARM chipset device.


Enterprise-grade security

Proven security for the enterprise.
Modzy addresses 354 accredited security controls from NIST 800-53, Rev. 5 that directly support FISMA Moderate and FedRAMP accreditation, and is DOD IL 6 Authorization ready.


Model drift & re-training

Drift detection
Specify your performance threshold limits to monitor and trigger automatic alerts when model performance deteriorates.

Re-training
Using transfer learning, certain types of models can re-train on updated data for better performance, for extensive time and cost savings.

Modzy AI Explainability for ModelOps and MLOps

AI explainability for text and images

5x Faster than LIME or SHAP. Generate explanations of outputs at the same time the model runs, generating faster, more precise results. Results you can trust while saving time and compute costs.


Build trust with human in the loop

You can choose to have users, data scientists and business analyst submit feedback on model predictions. Add new labels, offer corrections to past predictions, and enhance the explainable results.

Modzy can detect and alert on adversarial attacks against models

Adversarial defense

Modzy adversarial defense ensures your models are robust against attacks, model probing, and poisoned data. Optional model watermarking validates provenance information for models running in production.