How does the "hyper-local" computation work if all the sources are very generalized? Does that mean when your service says there's an 89% chance of rain at my location that's an actual, local probability?
The machine learning model combines more weather models as mentioned and this feeds proprietary local models that compute the weather exactly for your location. If you request a specific GPS, the chance of rain will be computed for the exact point based on the orography and nearby grid points.
Well wouldn't this only be better if you've come up with something superier to all the folks at NOAA. They combine weather models into the grid product every day with local human expert judgement rather than AI.
Have you published a backtest against NOAA's data? Have you looked into why they don't provide more hyperlocal data themselves? There's some interesting papers on the work they've done to get wildland firefighters appropriately local data.