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Musiio Launches NFT Song Slicer 1.0 to Maximise Song Revenue for Artists

Musiio Launches AI Powered NFT Song Slicer Ver1. Music Press Asia

Today, industry-leading music AI experts Musiio announce a new tool for song monetisation called NFT Song Slicer 1.0. The new tool for artists and rights holders uses AI to identify the most valuable sections of a song.

This information, according to Musiio, can be used to mint song slices as separate NFTs to maximise a song’s value and make the NFT financially accessible – and more tangible – to fans.

While the music streaming model makes it difficult for fans to put a dollar in the pocket of their favourite artists, NFTs present a solution. And although music NFTs can seem abstract to fans because the value proposition isn’t always clear, in the perspective as an asset class, it is already helping fans understand the value of an artist’s work and help them get paid.

Nas’ recent NFT drop on Royal saw the rapper mint and sell 1,110 tokens, each giving the buyer a small fraction of streaming royalties on a track. But what if, instead of owning a small fraction of a song’s royalties, you got to own a larger share of a song section you loved? Like the chorus from Livin’ On A Prayer, the guitar solo from Hotel California, or the intro from Money, Money, Money.

Musiio-logo.-Music-Press-Asia

The NFT Song Slicer 1.0’s automatic AI-driven process can find up to three slices per track and is highly successful at finding desirable hooks. By splitting up a song into multiple audio files, there are more opportunities to generate revenue. An artist can then price these slices differently when minting them as NFTs; for example, a vocal chorus hook might be priced higher than a verse.

Song slices are equivalent to pieces of limited-edition merch. Buyers don’t necessarily own the rights to the section they’ve bought as an NFT, and they may be one of many buyers, but
because there are a fixed number of these digital collectibles, they have inherent value. Moreover, that value may increase over time, making them tradable, of course, an NFTs value can also decrease, so buyers need to be aware and savvy, and Musiio is not a financial advisor!


“We’re committed to helping our users get more value from their music catalogues. NFT Song Slicer 1.0 is a great example of how AI can do this. Automation makes it possible for us to split up songs in large catalogues for minting as NFTs incredibly quickly. The result is that artists and catalogue owners can quickly generate new, valuable assets from existing work that fans can engage with.”

– Hazel Savage, Musiio CEO and Co-Founder.


For fans, buying music NFTs can be expensive. By carving a song up into sections, the cost can be reduced for the buyer, while artist revenue increases. The artist can also stipulate that they receive a cut of any future resale to continue earning if an NFT’s value increases.

As for catalogue owners or artists with an extensive back catalogue, the benefit of AI is that it can select the most valuable sections of millions of songs a day. Thanks to the automation that AI allows, Musiio can now add more value for rights holders and artists with larger back catalogues.

[Hazel Savage (front, left) and Team Musiio]

But why is using AI better than manually selecting sections, you may ask? Well, according to Musiio, its NFT Song Slicer 1.0’s AI has been trained to understand which sections have the greatest value. It has been trained to recognise those sections of songs that are most popular and makes highly accurate predictions.

Also, letting the AI slice up songs is far more streamlined and scalable than doing it manually. For those with large catalogues, AI makes cutting up tracks for NFTs a quick process.

So, what are the future applications of Musiio’s technology? Musiio says that there is scope with version 2.0 to work with catalogues and NFT minting platforms to train the AI to give a dollar value to each section based on popularity data.


Musiio is already a market leader in music AI. Its services provide AI-powered analysis, tagging and search tools to some of the world’s biggest music catalogues, counting Sony Music, Hipgnosis, Amanotes, Epidemic Sound and Blanco Y Negro among our customers.

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