Please contact us for a complete list of current and future engines.
The engines deploy fully automatically for each time series data stream (channel), without input from the user. No need to indicate training data, thresholds, limits, ranges, operating states, etc. Based on the last three weeks of data, the engines will build the first model for each signal, and then continuously reiterate these models as new data arrives (that is, the first models will rely on Archive data exclusively, and the iterations will rely more heavily on snapshot data, but not necessarily exclusively). In terms of time from DataWise deployment, until the engines have built models, this can be parallelized as much as you would like, meaning that it becomes a matter of dollars, rather than time. As an example, 100K channels would cost $100 per year on AWS, and each channel takes around 3 minutes to process upon first connection, and becomes continuously processed hereafter.