The evolution of biometric decision stacks represents a significant shift in how we architect computer vision systems. For developers building facial comparison or access control tools, the news is clear: a simple 1:1 match is no longer a sufficient unit of verification. The industry is moving toward a "decision stack" where the comparison algorithm is just the foundation, layered beneath liveness detection and policy engines. For those of us working with Euclidean distance analysis—the mathematical backbone of modern facial comparison—this architectural shift changes our implementation priorities. It’s no longer just about optimizing the embedding extraction or minimizing the distance between two vectors. It’s about how we handle the "presentation attack" surface. Beyond the Vector Match In a standard facial comparison workflow, we extract feature vectors (embeddings) from two images and calculate the distance between them.…