What inspired this project was we wanted to create a health-conscious environment when meeting up with people.
We wanted create a method of event hosting / publishing that felt natural but accommodating. When you have a gathering, similar to other apps, this app offers the ability to send invites in various different ways, but with a unique twist on the functionality of the usage of the app. It is not just for event hosting, but for a common issue of reiterating one's own dietary restrictions. No longer should one have to explain that they are vegan when accepting an invite to a cookout, it will just be on their profile and shared with the host automatically, saving time and possibly even shame if that concern happens to be something they may not want to say.
What it does
This application allows people to create events. When they create a event they will have the option to invite their friends via a hyperlink or through direct discovery via a username on the application. There are two users at a given point in time; a host and an attendee. The host is a user who has created an event and likely wants to share it with others. Upon sharing it, more users will populate the feed, as well as their tags they shared on their profile. All users can see this information. The attendee will have an option to accept an invite to an event, given a Yes, No, or Maybe option on the event page. The event shows the location, host, time, and date of the event. For the host, they can see a special built AI tool that will take into account the preferences, dietary restrictions, allergens, etc. of the attendees, and it will "audit" the event such that the host can see what they may want to consider changing, or at the very least, might just importantly know that X attendee should absolutely not be near peanuts.
How we built it
We built this using Google AI Studio, React, Featherless API, Google Gemini, MongoDB Atlas, and Base44. Unfortunately due to time constraints, we cannot really fully explain further but we would love to.
Challenges we ran into
Some challenges we faced was figuring out the how to implement are project. We had a good idea what to do based on sketches of the user interface and how data will come from the from the front end to the backend. Turning sketches into reality was a big challenge.
Accomplishments that we're proud of
Generally just learning everything that we did, we had a multitude of unique opportunities working on this project, all of which led us out of our respective comfort zones.
What we learned
None of us had used AI tools beyond google gemini, so learning featherless was a unique experience. Beyond that, MongoDB Atlas was an interesting tool with very easy to implement functionality.
What's next for Feast Meet
Refinement. This isn't meant to be a catch all, just a dedicated tool that's very good at its task.
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