Systems and methods for automatic tagging of images and video in surgical streams are described. A plurality of machine learning models, trained on annotated surgical data, are used to extract salient images and video clips from surgical video streams. In addition, speech transcription models process audio streams to generate transcriptions that are then associated with the tagged media. Subsequently, the system synchronizes the multimodal data and generates structured operative records. After synchronization, billing rules are applied to produce accurate billing reports. Applications of the system include improving surgical documentation, reducing administrative burden, enhancing billing accuracy, and accelerating revenue cycles in healthcare environments.