Point cloud data are an important component of geospatial data workflows, but software and formats to manage it often have compromises that work against efficient storage and processing of data. While commonly seen characterizing topographic information in LiDAR applications, point cloud data are an important driver of change detection applications in SAR workflows and provide important raw data to bring the physical world to the augmented one through handset capture on devices like the iPhone 12+. COPC.io is an open specification by Hobu, Inc. for organizing point cloud data in LAZ that allows it to be streamable over HTTP, selectable for resolution or spatial window, and adaptable to existing point cloud workflows in a backward compatible way. We will discuss the design choices and evolution of COPC, demonstrate its use in PDAL and QGIS scenarios, and show how COPC can be used in the cloud for management of massive point cloud collections.