This time recommendation engine takes an arbitrary number of calendar schedules as input and understands the context of the event based on features such as NLP embeddings of event name and description, as well as history of users past events. It output times that worked well for everyone and also made the most sense for the event in question.
Our location recommender utilized natural language embeddings of massive databases of location details to match locations to groups of users and their respective social events. This engine allowed for curated social events to be built automatically with everyone’s preferences in mind.