JLL: Real estate leader introduces ML services to uncover investment opportunities and deliver rent prediction and valuation
JLL, a global leader in real estate services, pioneers technology-driven innovation to transform the industry. The company invests in diverse real estate assets and serves clients across various sectors, aligning with a long-term commitment to benefit its people, clients, and communities.
Industry
Real Estate, PropTech
Use Case
Model Frameworks
Faster Batch Inference
Model Scenario Testing
100Ks savings yearly
Challenges
Manual Model Training and Tracking: Model training and the process of tracking experiments demanded extensive manual intervention. JLL urgently required an integrated platform for streamlined tracking of model experiments.
Inefficient Batch Inference: Inference batch requests had to be executed hundreds of times daily. Each request's long processing time hampered the pace of development projects.
Lack of Infrastructure for Online Models: As the team ventured into creating new models necessitating online serving, JLL found itself without the requisite infrastructure to support these models on a large scale.
Implementation
Solutions
Centralized Experiment Tracking: Qwak provided JLL's team with a unified platform, facilitating centralized model experiment tracking. It also allowed for the creation of a version repository for swift comparison across different versions.
Enhanced Batch Execution: With Qwak's Inference, batch execution became 10 times faster than our previous solution. This rapid execution capability not only saved significant engineering time but also proved cost-effective.
Scalable Real-Time Model Deployment: Qwak equipped JLL with the tools to design novel models and seamlessly deploy them as real-time models, even on a large scale.