Case Study: JLL accelerates ML model delivery and improves prediction accuracy with Qwak

JLL speeds batch inference 10x with Qwak

JLL, a global leader in real estate services, faced challenges scaling its machine learning operations. Their process involved manual model training and tracking, inefficient batch inference that slowed development, and a lack of infrastructure for deploying real-time models online. They partnered with Qwak and its MLOps platform to overcome these hurdles and enhance model accuracy without increasing engineering effort.

Using Qwak's platform, JLL centralized experiment tracking, accelerated batch inference by 10 times, and gained the ability to deploy scalable real-time models. This solution from Qwak resulted in significant yearly savings of hundreds of thousands of dollars and enabled JLL to deliver complex models faster and more efficiently.

JLL