The 3DGL group is utilizing artificial intelligence/machine learning (AI/ML) for automated feature extraction of 3D point cloud data. Here, models have been trained on labeled point cloud data to accurately label 3D points as terrain, buildings, vegetation, power lines, roadways, water, or unidentified. The classification of 3D points is further improved by utilizing localized spatial information. The classifiers will incorporate RGB information if those data are available, however, the models are also successful in labeling point cloud data with only XYZ geospatial information. With a 3D point cloud correctly labeled, higher level products such as Digital Terrain Models (DTMs), Building Footprints, or Vegetation/Forest characterization can be produced serving a variety of applications. This automated feature extraction software (VIPER) was developed to work on 3D point cloud data from multiple platforms (i.e. UAV, airborne, or spaceborne). Separate AI/ML models were created to compensate for the difference in spatial resolution and geometry of these systems.