CAPE Analytics creates AI applications, primarily for insurance organizations, that extracts information from aerial or satellite geospatial images. Their applications deliver accurate, up-to-date property information to insurance providers. To train and improve the quality of these deep learning models, CAPE ML engineers needed to collect as much data as possible. To keep this process efficient and cost effective, the team set out to build a reliable, repeatable ML Ops pipeline.

CAPE Analytics now depends on Labelbox as a critical, integrated component of this pipeline, regularly using both the APIs and fixed solution to optimize everything in the labeling process, from communication to annotation to iteration. Watch the video to learn more about how CAPE Analytics is enabling breakthroughs in AI.