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This startup is using Big Data to find the next music superstar

We rely a lot on Spotify’s (or any other streaming service’s) algorithms to find us the next earworm.

To find the next big artist, record labels and executives need to listen to demos or go to gigs in search of gems. Andrson is trying to change all this by breaking down songs and providing more data about tracks.

What problem is it solving?

When we listen to a new artist, we mentally compare them to songs and bands we know. Andrson is making this phenomenon possible by using AI to assign a similarity score to a band and their songs.

For example, a music executive can search for artists that are similar to Bruno Mars or Ariana Grande. The platform shows the percentage similarity of a musician to these artists or their songs. There’s also a location filter that could narrow down the search for artists in their vicinity.

For artists, it gives a platform to showcase their songs and get discovered for gigs, and sign deals with music labels.

The company believes that Spotify and other music services are designed to make already popular music more popular and that hinders artist discovery. So by putting an onus on what they call “pure audio analysis,” Andrson wants to highlight any artists even if they have one recorded song.

Where’s the AI?

Andrson’s AI prowess lies in its ability to match songs and artists on multiple levels. The company says that often songs are associated with mood labels that are assigned by humans.

For example, when an executive for Sony would be looking for a background track for a romantic scene, they might be typing in keywords such as “romantic” or “love” in a software.