Bored by the redundant recommendations by algorithms on music platforms I tried to find a new way of discovering new artists and tracks: Instead of having an algorithm analyse the overall plays and try to predict the next video a person might play, I wanted to use an algorithm sorely to connect two persons with a similar music taste.

In my perception, human based selection had some advantages when it comes to finding new music: I noticed, that algorithms tend to run in circles, since they didn't take into account already known tracks. Further, algorithms are not able to understand cultural context, so their recommendations are quite narrow and rarely result in unrelated, yet interesting results.

The aspect that made pursuit this project was the idea that the user could follow his own interest by saving tracks for himself, yet creating a value for other users.

To test this, I built a fully functional prototype with a working database for user management and comparing different playlists, Soundcloud and Youtube API requests to gather the content, and a working user interface based on the Meteor framework.

Since I did this project in a course focused on business, I also analysed the potential and weaknesses of marketing the platform. You can find the results in the attachments.