Case Study: OTIV advances autonomous rail operations with Segments.ai

How OTIV is leading the autonomous revolution in rail

OTIV, a company specializing in autonomous railway systems, faced the challenge of developing safe and efficient operations, which required highly accurate labeling of railways, signs, and potential obstacles for its machine learning models. To achieve pixel-perfect annotations for object detection, they partnered with the vendor Segments.ai.

By integrating Segments.ai into their machine learning lifecycle, OTIV utilized its platform for multi-sensor labeling and ML-powered image segmentation tools. This solution enabled their internal and external teams to collaborate effectively, resulting in the development of world-class algorithms for their autonomous systems. The vendor Segments.ai provided the necessary tools for faster, higher-quality data labeling, ultimately freeing up engineering resources for other critical tasks.

OTIV

Sean Nachtrab

Software/ML Engineer