Case Study: TimberEye achieves faster, safer log scaling with Scale AI

Enhancing Log Scaling and Inventory Management with Scale Rapid

TimberEye, a company that provides a mobile application for measuring and categorizing logs, faced significant challenges in developing a more advanced instance segmentation model. Manually annotating the required image dataset was overwhelmingly time-consuming and complex, stalling their development and nearly causing them to abandon the project. They turned to Scale AI's Rapid service for a solution.

Using Scale Rapid, TimberEye received a large volume of high-quality, production-ready image annotations tailored to their specific use case in just three days. This enabled them to successfully train their new model, leading to greater consistency and accuracy, especially with difficult corner cases. The overall solution allows TimberEye to scale logs 70-80% faster, improves measurement accuracy by 1.2cm per log, and reduces related labor requirements by 50% for their customers.

TimberEye

Scott Gregg

CEO and Founder