The company Arize has released a beta version of its embedding drift monitoring and analysis product, which is designed to help machine learning teams troubleshoot models and data that contain unstructured data. The product addresses key challenges such as lack of visibility into what's happening to the data when it's put into production, expensive model training, and difficulty in identifying new patterns emerging from unstructured data. With this release, teams can log models with both structured and unstructured data to Arize for monitoring, enabling them to proactively identify drift and troubleshoot issues using interactive visualizations. The product aims to provide actionable insights to help ML teams improve their models and data, and is designed to work with a wide range of deep learning models and architectures.