Jacob Baron

Software Engineer III

Machine Learning Scientist with a PhD in Physics and experience across the Machine Learning lifecycle.

Real-Time Package Damage Detection at Scale: Integrating YOLO in Warehouse Operations

Introduction: The High Cost of the "Last Mile"At Wayfair, we prioritize the safe arrival of every customer order. Currently, quality control relies on manual visual inspections, a system that is difficult to scale and prone to human error. Damaged package shipments impact the customer experience through delayed replacements and frustration, which also drives up our costs with increased logistical strain. To address this, we developed Tarragon, a YOLO-based Computer Vision (CV) model that automatically detects damaged packages in real-time. By integrating Tarragon into our warehouse sorting flow, we are moving toward a scalable, automated solution that protects the customer experience before the "last mile" begins. In this post, we will dive into how we build and integrate Tarragon into our operations.

6 Min Read

Wayfair Tech Blog

Vision-Language Models in the Wild: Damage Diagnostics from Customer Photos

Providing a fast and fair resolution when an item arrives damaged is critical for maintaining customer trust at Wayfair. When customers report a problem, whether online or with an agent, we often ask for photos because they’re the quickest way to understand what happened and choose the right resolution.

6 Min Read