Case Study: Teton.ai prevents falls in care homes and hospitals with Encord

Teton.ai - Customer Case Study

Teton.ai, a computer vision company focused on preventing falls in hospitals and care homes, faced challenges in obtaining and annotating the large volumes of data required to train its deep learning models effectively. They needed a highly flexible platform to manage their training data and adapt their annotation strategy, moving beyond simple bounding boxes to directly predicting patient states. They turned to Encord and its training data tooling to solve this problem.

By implementing the Encord platform, Teton.ai gained the flexibility to quickly create new projects and utilize unique labeling tools. The Encord SDK was particularly valuable, allowing Teton to build internal pre-labeling tools, upload data directly, and create an efficient loop for reviewing and correcting labels to continuously train their models. This solution provided the adaptive framework Teton needed to develop its fall-prevention technology, which successfully alerts staff to pre-fall behaviors and automates documentation, saving healthcare workers significant time.

Teton.ai