JLL: Real estate leader introduces ML services to uncover investment opportunities and deliver rent prediction and valuation

Qwak was brought aboard to enhance JLL's already impressive machine learning operation and enable delivery of complex models faster and more efficiently. The main requirement was to scale model delivery to production and enhance model accuracy without increasing engineering efforts.

About JLL

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

Real estate investment opportunities
Rent prediction via deep learning and text classification
Portfolio predictions via Automated valuation models (AVM) ‍

Model Frameworks

XGBoost
Pytorch
scikit-learn

Using Qwak allowed us to focus on creating value for customers and rather than spending valuable time on our infrastructure setup.

JLL
10X

Faster Batch Inference

A/B

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.