I'm having trouble understanding what the goal is of this as well. It seems like the quick summary would be "ML-based forecasting/prediction in a box" but the readme is making all of these broad claims...
We're looking to make timeseries AI easier for developers to integrate into their applications by providing tooling and patterns that are familiar to them. We're a group of devs that were looking to add intelligence to one of our projects, but struggling with existing tooling. We wanted to use patterns that were more familiar to us as devs, like a quick debugging loop, easily consumed packages, etc.
Surely the context for the time series matters? Not sure good outcomes will follow from people blindly applying black boxes.