Oh sorry I was meaning the way datarobot's prediction api accepts data and returns data for time aware modeling. It needs rows of data as the input, and spits out different rows of data (so maybe 60 rows full of features over time, and it predicts 14 days). Every single tool in mlflow seems geared around "one row => one prediction based upon values solely in that row"

I feel like I'm working against the grain trying to reconcile the two.