The world’s most powerful ML monitoring system

The world’s most powerful ML monitoring system

During our experience as Data Scientists, we’ve learned that there’s something wrong with how we’ve been checking our machine learning systems. We’re typically left with too many blind spots, after spending too much time running tests that we don’t enjoy working on. After countless hours of manual testing and monitoring, of searching for edge cases in other people’s models and anomalies in the ever-changing data, we’ve realized that something has to change. We fell in love with the problem and vowed that we’ll find a way to do this systematically.

During our experience as Data Scientists, we’ve learned that there’s something wrong with how we’ve been checking our machine learning systems. We’re typically left with too many blind spots, after spending too much time running tests that we don’t enjoy working on. After countless hours of manual testing and monitoring, of searching for edge cases in other people’s models and anomalies in the ever-changing data, we’ve realized that something has to change. We fell in love with the problem and vowed that we’ll find a way to do this systematically.

Supervising and controlling the health,
performance and stability of your AI systems

Supervising and controlling the health, performance and stability of your AI systems

Nearly seamless integration.

Raw Data

Data from all of your sources,
in their raw format, is tracked
and checked for drifts and
integrity issues.

Data Processing

Code from the different
phases of your ML system is
analyzed, to enable visibility
of the data’s transformations.

ML Model

Your ML model is analyzed for
limitations and weak subspaces,
to enable you to know when it’s
being misused.

An end-to-end approach towards monitoring your machine learning pipeline.

Nearly seamless integration

Raw Data

Data from all of your sources,
in their raw format, is tracked
and checked for drifts and
integrity issues.

Data Processing

Code from the different
phases of your ML system is
analyzed, to enable visibility
of the data’s transformations.

ML Model

Your ML model is analyzed for
limitations and weak subspaces,
to enable you to know when it’s
being misused.

An end-to-end approach towards monitoring your machine learning pipeline.

Any questions? Reach out to us and we’ll get back to you shortly.