ADAS data forms the foundation of modern driver-assistance systems, enabling vehicles to perceive, interpret, and respond to complex road environments. Captured through sensors like LiDAR, radar, and multi-view cameras, this data powers algorithms that detect lanes, objects, and traffic signals with high precision. However, raw data alone isn't enough—structured, accurately annotated datasets are critical for effective model training and validation. By leveraging expert annotation workflows and scalable data pipelines, companies can accelerate the development of reliable, real-time ADAS applications. High-quality ADAS data ensures safer roads, smarter vehicles, and seamless integration of autonomous capabilities into everyday driving.