Case Study: JLL achieves faster ML model delivery and batch inference with Qwak

JLL's real estate ML services designed to scale with Qwak

JLL, a global leader in real estate services, wanted to scale its machine learning operations to production faster and more efficiently without adding engineering overhead. The team faced manual model training and experiment tracking, slow batch inference, and limited infrastructure for deploying new online models, so it turned to Qwak and its JFrog ML platform.

With Qwak, JLL centralized experiment tracking, sped up batch inference by 10x, and gained the ability to deploy real-time models at scale. The implementation also enabled A/B testing and delivered annual savings of hundreds of thousands of dollars, helping JLL focus more on value creation and less on infrastructure setup.

JLL

Or Hiltch

Vice President Engineering