WhyLabs is the essential AI Observability Platform for model and data health. It is the only machine learning monitoring and observability platform that doesn't operate on raw data, which enables a no-configuration solution, privacy preservation, and massive scale.

Machine learning engineers and data scientists rely on the platform to monitor ML applications and data pipelines by surfacing and resolving data quality issues, data bias, and concept drift. These capabilities help AI builders reduce model failures, avoid downtime, and ensure customers are getting the best user experience. With out-of-the-box anomaly detection and purpose-built visualizations, WhyLabs eliminates the need for manual troubleshooting and reduces operational costs.

The platform can monitor tabular, image, and text data. It integrates with many popular ML and data tools including Pandas, Apache Spark, AWS Sagemaker, MLflow, Flask, Ray, RAPIDS, Apache Kafka, and more. To learn more about what data types WhyLabs can work with and which tools we integrate with, check out the whylogs GitHub page: https://github.com/whylabs/whylogs 

WhyLabs was created at the Allen Institute for Artificial Intelligence (AI2) by Amazon Machine Learning alums and is backed by Andrew Ng's AI Fund.

For custom pricing, EULA, or a private contract, please contact AWSMarketplace@whylabs.ai  for a private offer.