Music Rights Intelligence for Social and Digital Content
Trakr combines music identification, rights intelligence and structured evidence to help teams discover, understand and act on music use, including legal support for those that need it.
SOCIAL PLATFORMS
ABOUT
Trakr brings transparency to how music is used across social and digital content identifying artists, recordings, rights ownership and where licensing status appears unclear.
ABOUT
Trakr brings transparency to how music is used across social and digital content identifying artists, recordings, rights ownership and where licensing status appears unclear.
HOW IT WORKS
HOW IT WORKS
Built for discovery, evidence and action
Built for discovery, evidence and action
Trakr is designed to recognise music as it appears in real-world social and digital content, then connect each use to rights data, attribution and monitoring workflows over time. Every identification is tied to rights data and preserved as a structured record.
Trakr is designed to recognise music as it appears in real-world social and digital content, then connect each use to rights data, attribution and monitoring workflows over time. Every identification is tied to rights data and preserved as a structured record.
Schedule a Demo
Schedule a Demo
Recordings
Remixes
Mashups
Samples
Covers
Background
HOW IT WORKS
Built for discovery, evidence and action
Trakr is designed to recognise music as it appears in real-world social and digital content, then connect each use to rights data, attribution and monitoring workflows over time. Every identification is tied to rights data and preserved as a structured record.
Schedule a Demo
Schedule a Demo
Recordings
Remixes
Mashups
Samples
Covers
Background
VISIBILITY
See where and how music is being used
Build a structured view of music use across past content.
Reconstruct twelve, twenty-four, thirty-six months of posts — and surface patterns of use that were never visible in real time.
Track emerging patterns of use as new content is published.
Continuous detection across accounts and portfolios, flagging new uses the moment they appear on the open social graph.
Detailed attribution for recordings, artists, writers, labels & publishers.
A global attribution layer that maps each identified recording to the rights parties behind it.
Upload or link content to identify music & review rights status.
Drop a URL or file and get a structured rights record back; audio ID, attribution, license signal, and an exportable evidence trail.
VISIBILITY
See where and how music is being used
Build a structured view of music use across past content.
Reconstruct twelve, twenty-four, thirty-six months of posts — and surface patterns of use that were never visible in real time.
Track emerging patterns of use as new content is published.
Continuous detection across accounts and portfolios, flagging new uses the moment they appear on the open social graph.
Detailed attribution for recordings, artists, writers, labels & publishers.
A global attribution layer that maps each identified recording to the rights parties behind it.
Upload or link content to identify music & review rights status.
Drop a URL or file and get a structured rights record back; audio ID, attribution, license signal, and an exportable evidence trail.
TECHNOLOGY
Identification built for the modern world
Trakr was built to handle what actually happens to music online across social media and digital platforms. The entire process, from input to identification, takes seconds.
Trakr is engineered for the messy reality of social media.
Most identification systems work fine with pristine, unmodified audio. But that's not how music lives on the internet.
Speed and Pitch Changes
Sped-up audio is one of the most common modifications on TikTok and Reels. Trakr identifies tracks across a wide range of speed and pitch variations.
Covers and Compositions
Beyond recording-level matching, Trakr identifies the underlying composition through melody analysis. This catches covers, live performances, and interpolations.
Remixes & Mashups
When multiple tracks are layered together, Trakr can separate and identify individual components within the mix.
Background Noise and Voiceover
Music playing behind speech, environmental noise, or other audio? Trakr isolates and identifies the music layer.
RESEARCH
Trakr analysed 200,000 TikTok posts from 800 brands published over a 12 month period.
16,000+
16,000+
Posts in the sample dataset featured music with no clear evidence of licensing
Posts in the sample dataset featured music with no clear evidence of licensing
4,100+
4,100+
Unique titles were discovered from major and significant independents in the dataset
Unique titles were discovered from major and significant independents in the dataset
1.14B
1.14B
Views generated by posts with no clear evidence of licensed music in the dataset
Views generated by posts with no clear evidence of licensed music in the dataset
60M+
60M+
Likes generated by posts with no clear evidence of licensed music in the dataset
Likes generated by posts with no clear evidence of licensed music in the dataset
4M
4M
Shares generated by posts with no clear evidence of licensed music in the dataset
Shares generated by posts with no clear evidence of licensed music in the dataset
1.3M
1.3M
Comments generated by posts with no clear evidence of licensed music in the dataset
Comments generated by posts with no clear evidence of licensed music in the dataset
