Most of our development time is spent on the algorithms.

We are continuously reducing drag and friction to increase the speed and accuracy of your Master Scheduler.

The faster the algorithms are, the more powerful the schedule can become and the more solutions it can find, instead of wasting time.

We have done a lot of experimental writing meaning finding new ways to add intelligence to the algorithms.

If you look at the example of when you walk into the room, very quickly you are able to know who is the leader the room, we set happy, friendly person jumping off the walls and two other people with whom you can relate to.

It is normal for you to gravitate towards the people that you like and have a lot in common with. In the same way the scheduler algorithms would walk into a room(figuratively speaking) and know exactly the same information and then act on it.

The scheduler will not sit on the bench all shy but would be the fun guy in the room with whom everybody wants to gravitate towards and feel the need to share information with.

The scheduler will then analyze and compare information received from the different people and from that, make the best decision as a leader, which direction the group needs to go. By no means is the scheduler a shy chap, but rather a highly intelligent and dynamic person(so to speak).

Patterns

Unlike something like a chess program that comes preloaded with certain patterns or opening moves, what makes most scheduling so challenging is that these patterns cannot be preloaded and need to be calculated ‘on the go’.

Especially in the American schools, with the amount of different courses available which differ from school to school; spotting these patterns in the data field becomes very, very tricky.

Having worked with high institutions that are very large in numbers, we were able to spot patterns that