AI Music Intelligence for Independent Artists
SongScore gives you the same depth of insight that major label A&R teams have had for years — in a format that is actually usable.
SongScore is a music intelligence platform founded by Robbie Rundle in Limassol, Cyprus in May 2026. The platform uses artificial intelligence to analyze tracks across 120+ audio dimensions, providing independent artists with platform-specific fit scores, Sonic DNA analysis, and written AI reports before release.
Key Facts About SongScore
Our Story
SongScore is an AI-powered music intelligence platform headquartered in Limassol, Cyprus, founded by Robbie Rundle and launched publicly in May 2026. The company was built on a simple observation: independent artists are running serious businesses with almost no business intelligence.
For years, major labels have had dedicated A&R teams, data analysts, and proprietary tools to evaluate tracks before release. Independent artists have had gut feel, a few friends' opinions, and hope. That gap is not just unfair — it is expensive. Every track released blind is a bet placed without odds.
SongScore was built to close that gap. The platform's mission is simple: give every independent artist the same depth of insight that major label teams have had for years, in a format that is actually usable. Not a dashboard designed for data scientists. Not a report written for executives. A score, an analysis, and a clear set of actions — in under two minutes.
“Independent artists are running serious businesses with almost no business intelligence. They’re making creative and commercial decisions blind. SongScore changes that — giving them the same depth of insight that major label A&R teams have had for years, in a format that’s actually usable.”
What SongScore Does
Upload any track and SongScore returns platform-specific fit scores for Spotify, TikTok, YouTube Music, and Apple Music — each weighted by that platform's unique algorithmic preferences. These are not opinions. They are data-driven scores mapped against what platforms algorithmically reward: completion rate signals on Spotify, hook strength for TikTok's For You Page, mood consistency on YouTube Music, and editorial quality standards on Apple Music.
Beyond platform scores, every track receives a detailed analysis that covers mood, energy envelope, genre fit, vocal profile, and sonic character. The Full Analysis Report turns these dimensions into an actionable career-guidance document with release strategy recommendations, playlist pitching targets, and production improvement suggestions.
For labels, distributors, and publishers, SongScore also offers AI Music Detection technology — identifying AI-generated or AI-assisted tracks with high confidence, enabling rights holders to make informed decisions about catalogue intake, royalty tracking, and content verification.
Key Capabilities
- ▸AI-driven audio analysis across 120+ dimensions
- ▸Cross-platform streaming performance tracking for Spotify, TikTok, YouTube Music, and Apple Music
- ▸Artist benchmarking against comparable releases in your genre
- ▸AI-generated music detection for labels, distributors, and publishers
- ▸Playlist matching with real, active Spotify playlists in your genre tier
- ▸Production analysis: loudness, dynamic range, stereo width, and frequency balance
- ▸Vocal clarity scoring — a key predictor of algorithmic playlist acceptance
- ▸Hook segment analysis identifying your track's strongest 15–30 second window
Why SongScore
Data-Driven, Not Opinion-Driven
Every score is calculated against platform-specific audio signals — the same signals that determine algorithmic reach. No guesswork, no subjective feedback.
Built for Artists, Not Executives
A clear score, a clear analysis, and a clear next step. No dashboard designed for data scientists. No report written for label executives. Just actionable intelligence.
All Platforms, One Analysis
One upload, four platform-specific scores. Spotify wants different audio signals than TikTok. YouTube Music weights different factors than Apple Music. SongScore evaluates your track against all of them simultaneously.
Private by Design
Your unreleased music stays yours. Tracks are analysed and scored without being shared, stored, or used for training. No one listens to your unreleased work except our AI.
The Market Opportunity
The global music analytics software market is growing rapidly, powered by two converging trends. First, the volume of independent releases has reached an all-time high — over 120,000 tracks are uploaded to streaming platforms every single day. Second, artists are more data-literate than ever. They understand that streaming platforms are algorithmic products, and they want to know how their music fits before they release it.
The tools, however, have not kept pace. Enterprise analytics platforms designed for major labels are too expensive for independent artists. Free tools offer surface-level metrics that do not translate into actionable release strategy. There has been no tool purpose-built for the artist who releases independently, budgets carefully, and needs professional-grade intelligence without enterprise pricing.
SongScore fills that gap. It is the first music intelligence platform designed from the ground up for independent artists — combining the analytical depth of a label analytics department with the speed and accessibility that independent releasing demands.
The Founder
Robbie Rundle
Robbie founded SongScore after spending years inside the independent music ecosystem — watching talented artists release exceptional music without any meaningful data to guide their strategy. SongScore is the tool he wished had existed. Based in Limassol, Cyprus, he built the platform to close the intelligence gap between independent artists and the major label system.
The Problem We Solve
Independent artists are running serious businesses with almost no business intelligence. They are making creative and commercial decisions blind — choosing which single to lead with, which platform to prioritise, when to release, and how to position their music — all without the data that would tell them whether they are making the right call.
A producer spends weeks on a mix but has no way to know if their vocal clarity is strong enough for Spotify playlists. An artist chooses between two singles but has no data on which one has stronger hook retention. A manager allocates a marketing budget across platforms without knowing which platform their track is algorithmically best-suited for.
SongScore changes that. One upload, two minutes, and every question above has a data-driven answer. Not a guarantee — no platform guarantees anything — but a signal. For the first time, independent artists can make release decisions with the same quality of intelligence that major labels have relied on for decades.
It's all about the song's score.
Score Your First Track FreeContact
Questions, press or partnership enquiries? Email us at support@songscore.co.
Prefer a form? Reach out here.