Accurate measurements of daily feed consumption for dairy cattle is an important metric for determining animal health and feed efficiency. Traditionally, manual measurements or average feed consumption for groups of animals have been employed which leads to human error and overall inconsistent measurements for the individual. Therefore, we developed a scalable non-invasive analytics system that leverages depth information derived from stereo cameras to consistently measure feed offered and report findings throughout the day. A top-down array of cameras faces the available feed, measures feed depth, projects depth to a 3-dimensional (3D) mesh, and finally estimates feed volume from the 3D projection. Our successful experiments at the Purdue University Dairy, that houses 230 cows, demonstrates its robustness and scalability for larger operations holding significant potential for optimizing feed management in dairy farms, thereby improving animal health and sustainability in the dairy industry.