A new integration just hit the shelf! Sagify users can now integrate with the Superwise model observability platform to automatically monitor models deployed with Sagify data drift, performance degradation, data integrity, model activity, or any other customized monitoring use case.
Sagemaker is like a swiss army knife. You get anything that you could possibly need to train and deploy ML models, but sometimes you just need a knife, and this is where Sagify comes in. Sagify is an open-source CLI tool for Sagmaker that simplifies training and deploying ML models down to two functions, train and predict. This abstracts away a lot of the low-level engineering tasks that come along with Sagemaker.
What you get with Sagify + Superwise
Now that Sagify has simplified Sagemaker training and deployment, the Sagify & Superwise integration streamlines the process of registering your new model and training baseline to Superwise’s model observability platform. This lets you hit the ground running because once you’ve initialized, you get train-deploy-monitor all in one run. Superwise will infer all relevant metrics out-of-the-box (In addition, you can also add customized metrics unique to your use case and business). This way, you don’t need to invest time in configuring model metrics. You can focus on detecting issues like drift, performance degradation, data integrity, etc., to resolve issues and improve your models faster.