As sleep surgeons, we strive to offer precise, individualized sleep care, however, there are several challenges: defining the best treatment path hinges on the accurate definition of “successful result”, as some of the commonly used sleep study metrics have little to no correlation with clinically meaningful outcomes and offer limited perspective on the ideal surgical procedure for each individual. In addition, decisions around procedure selection and perioperative routines are based on less-than-ideal evidence to support or refute its usefulness. To target this issue, we have gathered multidisciplinary talent and assembled a team with clinical, computer science and statistics expertise aiming to collect, refine and analyze large volumes of data to generate Real World Evidence to define clinically relevant deliverables and efficient routines. In the future, our aim is to build AI algorithms that will augment the capacity of specialists to deliver the best possible care to our patients.