Model monitoring at scale for your ML Platform
Nobody knows your models as well as you. So when it comes to configuring monitors for ML production, you’re the natural choice.
Aporia provides a rich variety of model monitoring options and modules to help you to build the most suitable models and optimize them for your use cases and data.
How to monitor model performance in production
Install Aporia
Integrate ML Models
Set Up Monitors
Get Insightful Notifications
Install Aporia
Integrate ML Models
Set Up Monitors
Get Insightful Notifications
Visibility into actual performance
Our dashboard provides a single pane of glass for checking ML production status, continuously comparing actual performance with expected results. Customize views to track the measures that matter most for each model – average prediction, version comparison, or sub-segment performance.
Rich model monitoring options
Aporia proactively monitors your models to ensure early detection of the full range of issues. From type mismatch to prediction drift, and from model staleness to custom metric degradation and more, Aporia makes it easy to cover all monitoring needs.
Complementary investigation toolbox
Once an issue has been detected, its extent and causes must be assessed to determine the right action to take. From the alert, dive right into Aporia’s quick triage zone, where you’ll find essential diagnostic information.
Get quick answers about which elements of your data have been affected; whether the issue impacts the full model or just a segment if the issue revolves around specific features or timeframes, and much more.
Aporia helps you identify the source of the problem at hand – data integrity, data science, or engineering – so you can expedite root cause analysis and remediation.
We’re Integrated with Your ML Stack
