A model is different from a real product. We'll share Infervision's journey from designing algorithms for medical image analysis to actually implementing models inside hospital's PACS systems. A product is different from a model on three aspects: (1) Products make a real difference. Robustness, reliability, and accuracy are no longer simple numbers reported in articles, but criteria that judge the efficacy of algorithms from time to time; (2) Products solve real problems. Models service deep learning science, whereas products service medical decisions. When designing a medical image diagnosis product, we need to identify radiologists' real need and solve problems that matter to clinical decisions. (3) Products take into account all complexities in a real application context. We'll give a brief introduction of China's medical system with an emphasis on radiology imaging diagnosis. We'll also share some challenges and achievements Infervision experienced when attempting to insert A.I. products into radiologists' daily work flow.