“Retroactive detection” manifests itself as data backfill. You can imagine this if the historical data is of sufficient resolution to go back and search for models … mileage will vary depending upon the nature of the model.
The local Sense box, from what I understand is actually doing what you call inferencing – let’s call it detection. The model, built on cloud data, is stored locally in the Sense memory I’m guessing and so the high frequency sample data can be compared and matched. Without that, the dependency on the cloud would likely have latency beyond workable.