Sagify

Sagify is a command‑line and Python-based tool that streamlines the process of building, containerizing, and deploying machine learning models to AWS SageMaker. It provides a structured project scaffolding that separates training, prediction, and infrastructure code, helping data scientists and ML engineers move from experimentation to production with less DevOps overhead. Using Sagify, users can quickly create Docker-based environments, package their models, and push images to Amazon ECR, then configure and launch SageMaker training jobs and endpoints directly from the CLI.

The tool manages configuration files for different environments (e.g., dev, staging, production), supports local testing of training and inference code, and integrates with standard Python workflows and requirements management. Sagify is particularly useful for teams that want a repeatable, version-controlled way to operationalize models without manually writing complex SageMaker SDK scripts or CloudFormation templates.