Analysis of ceramic standardization and variation provides a powerful tool for evaluating the scale, organization, and technological practices behind pre-modern production and for gauging the coordination and complexity of past economic systems. The selection of formal attributes to allow effective measurement and comparison of complex shapes, though, presents a crucial challenge to systematic study. Alongside fabric composition and surface treatment, consistent linear dimensions offer helpful metrics for assessing standardized production. More difficult to measure, though, are the many finely graduated variations in shape that can reflect how these processes were implemented and the limits to large-scale serial productions like those of the ancient Mediterranean world. We offer here a new method and computational pipeline, developed using open-source libraries, to quantify morphological similarities and differences among ceramics. Grounded in point cloud comparison, our method enables comprehensive 3D characterization of geometries down to the pixel level and leverages state-of-the-art machine learning algorithms and high-speed data structures for efficiency and scalability across large assemblages. Case studies of transport amphoras from two late antique shipwrecks off the coast of southwest Turkey demonstrate the robustness of the methodology and pipeline. Together, they provide an analytically rigorous and flexible approach to quantifying formal variation within a dataset. The first results suggest strategies for controlling the capacities of these transport jars within late ancient systems of production, but the method should also prove useful in formal analysis of artifacts of other forms and contexts
