Give us a star ⭐️ on GitHub to support the project!
⚡️ Join us June 6 to see how you can use Evidently open-source to evaluate LLMs. Register now →

Evaluate, test, and monitor ML model performance

How are your models doing in production? Make sure that your ML systems work reliably in real-world scenarios. 

Evidently ML Model Performance
What is ML model health?

The ultimate goal of an ML system is to improve or automate business processes. To keep the models on track, you need to measure their production performance and understand the errors they make.

How Evidently helps

Evidently helps track ML model quality with built-in standard metrics, checks, and visualizations. You can run pre-deployment model testing, monitor them in production and troubleshoot when things go wrong.

Build models you can trust

Visualize model quality

Evaluate the performance and compare ML models side-by-side. Understand key metrics, such as accuracy, precision, and recall. Go beyond aggregates to explore where models fail. 

Evidently for ML model quality
Evidently for ML model tests

Run model tests

Validate the quality and behavior of ML models with structured checks. Ensure the models comply with your expectations when you deploy, retrain and update them. 

Monitor the performance

Keep a close eye on the health of production ML systems. Maintain confidence in your models and know when to intervene.  

Evidently for ML model performance
Evidently for detecting ML model decay

Detect model degradation

Track metrics over time and detect deviations. Take proactive steps by monitoring prediction and data drift even before you get the labels. 

Pick your metrics

Choose from standard model quality metrics for different model types or easily define your own. Align the evaluation with your business goals. 

Evidently in-built ML model quality metrics

Yes, it's open-source!

With a lot of examples in the docs.


Get started

Easily add Evidently to existing workflows, no matter where you deploy. 

Evidently Cloud

Evidently Cloud is the easiest way to get ML monitoring up and running.



Deploy and run Evidently on your own.
Apache 2.0 license.

By clicking “Accept”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.