Clicklease is a financial services company that offers equipment leasing to small businesses and they make use of ML to make predictions about policies, pricing, and risk, but they need to compute features on-demand when users interact with the platform. In this talk, we present our journey from computing real-time features using stored procedures to using Python to define and compute features at request time. We will look in detail at some of the requirements for on-demand transformation functions and how we leverage Hopsworks to support our ML platform.
