Case Study: Cash App achieves flexible, secure machine learning workflows with Prefect

Cash App secures ML workflows across 4 environments with Prefect

Cash App, a mobile payment service, needed a more flexible and scalable orchestration tool for its machine learning workflows to combat fraud. Their previous tool, Airflow, was sufficient for ETL but could not meet the demands of rapidly deploying new ML models, provide heterogeneous compute options, or easily exchange data between workflows. This led them to seek a new solution from the vendor Prefect.

By implementing Prefect, Cash App gained the flexibility to run deployments across varied compute infrastructure with configurable work pools and flow-specific environments. The Prefect solution provided a secure assembly line for ML workflows, improving data security through access control lists and enabling efficient compute resource use. The switch generated higher interest among internal customers due to the platform's increased flexibility, positioning the team to scale into more complex models with Prefect's integrations.

Cash App