In almost every planetary surface investigation, the characterization from a camera is a common initial step [1]. Mission Control is developing a science autonomy system called Autonomous Soil Assessment System: Contextualizing Rocks, Anomalies and Terrains in Exploratory Robotic Science (ASAS-CRATERS). It can enable automated surface characterization on planetary missions, which can benefit a wide range of science investigations and rover navigation alike. It can perform terrain classification and novelty detection using convolutional neural networks, and data aggregation to produce relevant data products for supporting science operations. Built on cutting-edge algorithms and off-the-shelf computing components, it offers low-cost ways to speed up tactical decision-making in next-generation commercial lunar missions.