Vetiver and mlflow speak similar languages so it likely possible to view mlflow as a board to pull model versions into a VetiverModel and then deploy as an API. From the user's perspective, things would be more or less the same, but model itself and its metadata, deps, etc. would be coming from an mlflow registry.