So can this be used to predict patterns for traffic, restaurant table availability, and your customers’ demand for things based on other customers?

Hey! I'm one of the engineers who worked on this project.

These are all problems that KumoRFM is able to solve given that you have the right relational data of course! So e.g. for predicting restaurant table availability you would need at least an occupancy table which records how many seats were available historically and you can predict its future entries.

But you can also add more relevant data without joining into a single table, so you can add a restaurants table, a holiday-calendar table, weather patterns, etc. and KumoRFM should take it all into account when predicting.