Today's optical design tools use AI mostly for discrete tasks: accelerating simulations, suggesting configurations, or exploring vast parameter spaces. These are enhancements to classical computation—not full replacements. Artificial Intelligence is transforming industries, and optical design is no exception. From machine learning and deep learning to reinforcement learning and agent-based systems, AI brings a diverse toolkit to the engineering table. When you have historical data, supervised learning models can. In this transformation, optical transceivers —key components that convert electrical signals to optical signals and vice versa—are moving from behind the scenes to center stage, becoming the vital arteries supporting data centers, cloud computing, and AI training and inference. For example, predictive analytics can help determine which patients would benefit the most from complex surgeries like LASIK. However, integrating AI requires prerequisites, such as. We are adopting a physics data driven approach, we combine our expertise in optics with simultaneous measurement-oriented processing (physics-driven), which gives us a cleaner data. Our platform allows the operator and our multidisciplinary team to quickly validate/analyze data (2D, 3D), retrain.