Hi Joanna. Thanks for the encouragement and we're glad you liked our work! Most of what we discussed in the post is within our means at our current skill level.
For instance, one of the challenging aspects of building this app was accurately grouping emails (e.g. phone bill emails and library reminder emails should be separated into different groups so that accurate reminders can be given to the user). Using machine learning clustering algorithms, we recently got that working. For certain other aspects, including getting information based on user location and family members, we have looked into it enough to know that we can achieve it.
The Companion app is definitely challenging to build, and there are certain areas where we may get face difficulties. For now, we don't intend to look elsewhere for the skills required. However, being students at Georgia Tech, we are well positioned to seek guidance from friends and faculty around us should the need arise.
Hi Susan, thank you, we truly hope our app can achieve that goal. To effectively achieve it, we've made our app, Companion, differ from others in various manners.
The most basic difference between our app and the others is the integration of various sources of data, instead of relying on just one or two sources. This is why Companion reads through emails, analyzes user's location data, and even allows family members to set reminders. Using these sources, it then decides what to remind the user about. Beyond that, Companion is more active in its decision making. Current apps rely on passive decision making, i.e. The user enters what to be reminded about, whereas Companion predicts what the user may find useful to be reminded about.
There are further extensions we would like to make to Companion to set it apart more, but for now we have focused on the most critical areas as the first stage of our project.