Etere AI can now identify songs automatically and enrich media assets with detailed music metadata, including artist, album, genre, record label, release date and cover artwork. Stop wasting time entering music metadata manually.
With Etere AI, songs can be identified automatically and their metadata added directly to your media assets. The result is a richer, cleaner and more searchable media library without adding another manual task to the workflow.
As soon as Etere AI detects a song, it retrieves key information including the artist, album title, genre, record label, release date and cover artwork. This gives broadcasters and media companies more complete and accurate metadata while significantly reducing repetitive manual work.
For large media archives, the difference can be substantial. Content that was previously difficult to identify or search can become instantly more useful, allowing users to find songs, artists, albums and related media much faster.
Because the feature is fully integrated into the Etere Ecosystem, song identification can be included directly in existing workflows. Music metadata can be enriched automatically as content is ingested, processed, archived, prepared for playout or distributed.
Better metadata means better content discovery. Users can search and organise media by artist, album, genre, release information and other music-related fields, making archived content easier to find, reuse, programme, distribute and monetise.
Etere AI does the listening. Your archive gets the information.
With automated song identification and metadata enrichment, Etere AI helps turn your media library into a smarter, more valuable content resource.
Contact Etere to discover how AI-driven automation can improve the way you manage, search and reuse your media.
Visit https://www.etere.com
