AI Song Analyzer for Producers & Independent Artists
Drop a track and get its tempo, key, loudness and dynamics right now, free, no account. Want to know what to do about them? The scored report covers sync appeal, production, mix, mastering and songwriting, and tells you what to fix and in what order.
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- Decoding
- Loudness and true peak
- Tempo and key
- Dynamic range
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What the numbers say
That's what the track measures. Not whether it works.
The scored report listens to the whole song and scores it on five things: sync appeal, production, mix, mastering and songwriting. Then it ranks what to fix first.
What is an AI song analyzer?
An AI song analyzer is software that listens to a recording and evaluates its musical, technical and commercial characteristics — arrangement, songwriting, production, mix, mastering and genre fit — then reports what is working and what is holding the track back. The useful ones return reasoning, not just a number.
TuneLens is an AI song analyzer built as a feedback coach: every score arrives with the assessment behind it and a ranked list of what to fix first, so the output is a plan rather than a grade.
What the AI analyzes
TuneLens evaluates your track across five scored dimensions, examining both the technical characteristics and creative factors that determine how a song performs in the real world. Each dimension gets a numerical score, a written assessment, and specific time-coded observations — not a vague summary, but a structured report you can act on. The goal isn't a grade; it's a clear picture of where your track is strong and where it's losing ground.
Sync Appeal
Commercial fit, emotional arc, and placement potential. The AI assesses how well the track would serve TV, film, advertising, and trailer contexts — including whether the structure, energy, and mood match the kinds of cues that actually get placed.
Production & Sound Design
Arrangement quality, texture, instrumentation choices, and how well the production supports the song's emotional intent. Covers density, contrast between sections, and whether the sonic palette feels cohesive or scattered.
Mix
Frequency balance, stereo width, dynamic range, low-end control, and separation between elements. The AI flags frequency clashes, overly crowded arrangements, and moments where the mix is working against the song rather than for it.
Mastering
Loudness levels, limiting, transient handling, and final output quality relative to commercial standards and streaming platform targets. The report identifies whether the master is hitting appropriate LUFS targets and how it compares to released material in the same genre.
Songwriting
Structure, hook strength, lyrical clarity, and the relationship between the music and the words. The AI assesses whether the arrangement supports the lyrical narrative, whether the hooks land at the right moments, and how the song's internal logic holds together from intro to outro.
How it works
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Upload your track
Drop an MP3, WAV, or audio file. TuneLens runs the AI analysis immediately — no configuration, no setup, no template to fill out. The analysis starts as soon as your file is processed.
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Read the scored report
Five scored sections, each with a written assessment, specific strengths and weaknesses, and time-coded observations flagging exactly where issues occur. Every score is explained — you'll understand why the AI landed where it did, not just what the number is.
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Work through action items
A consolidated, prioritized list tells you what to fix first — ranked by impact so you're not guessing where to spend your time. Re-upload revised versions and track your score progress over each iteration.
More than a score
A score on its own tells you very little. An 71 in Mix means nothing unless you know which frequencies are causing the problem, which elements are stepping on each other, and what a fix would actually look like. That's the difference between TuneLens and a meter plugin: the score is just the headline. The action items are the report. Every issue the AI surfaces comes with enough context that you can take it back to your session and do something about it without guessing.
TuneLens also supports reference comparison. Upload a commercially placed track alongside yours and the AI runs a side-by-side assessment — showing you exactly where the gap exists between your version and a track that's already been placed. This is particularly useful for producers working toward sync, where the brief often names a reference track and you need to understand in concrete terms how far your production sits from it across mix, mastering, energy, and mood.
Every revision you upload is saved and scored, so you can see whether your changes actually moved the needle. It's common to make what feels like a significant improvement in a session and find the score hasn't shifted — or to make what feels like a small tweak and watch a problem dimension jump several points. Version tracking makes that feedback loop visible and removes the guesswork from the revision process.
AI song analysis vs. the other AI music tools
“AI music tool” covers at least five different jobs, and they are easy to confuse because they all take an audio file as input. What separates them is what comes back out.
| Category | What it returns | What it will not tell you |
|---|---|---|
| AI music tagging | Metadata labels — genre, mood, tempo, instrumentation — so a track can be filed, searched and licensed at catalogue scale. | Whether the track is any good, or what to change. |
| AI song analysis | A judged assessment of the recording across songwriting, arrangement, production, mix and mastering, with the reasoning attached. | It names what to change; it will not make the change for you. |
| AI mastering | A processed audio file, with EQ, compression and limiting applied automatically. | Why the mix underneath needed that processing in the first place. |
| AI music similarity | Other tracks that sound like yours, ranked by acoustic distance. | Where yours falls short of the ones it matched you to. |
| AI sync analysis | An assessment of fit for film, television, advertising, trailers and games — structure, emotional arc, edit points, and match to a supervisor’s brief. | Whether a supervisor will actually place it. |
TuneLens does AI song analysis, and treats AI sync analysis as one dimension of it — Sync Appeal is one of the five scored sections, and the Cue Score summarises it. TuneLens does not master your track and does not return processed audio, and it is not a tagging service, though every run does emit mood, genre and tempo-feel descriptors as a by-product of the analysis. For the sync-specific read on its own, see sync licensing readiness.
How to choose an AI song analyzer
Inside the category, most tools specialize. Some read the mix and report frequency balance, stereo width and loudness. Some read the arrangement and report structure and section changes. Some return a general impression of the song. Each one is useful for the part it covers, and none of them covers the rest.
TuneLens scores five dimensions in a single pass on the same upload — Sync Appeal, Production & Sound Design, Mix, Mastering and Songwriting — each with the reasoning behind the score and a ranked list of what to fix first. On a track you are trying to finish, the songwriting, the production and the technical read arrive in one report instead of from three tools you have to reconcile yourself.
Frequently asked questions
What is an AI song analyzer?
An AI song analyzer is a tool that listens to your track and returns a detailed assessment of its strengths and weaknesses across production, mix, mastering, and commercial appeal. TuneLens analyzes uploaded MP3s and scores each dimension, then generates prioritized action items so you know exactly what to fix first.
What does TuneLens analyze in a song?
TuneLens scores five dimensions: Sync Appeal (commercial fit and placement potential), Production & Sound Design (arrangement, texture, instrumentation), Mix (frequency balance, stereo width, dynamic range), Mastering (loudness, limiting, final output), and Songwriting (structure, hooks, lyrical fit). Each section includes a detailed written assessment and time-coded observations.
Is there an AI that can listen to my song and give feedback?
Yes. TuneLens listens to the recording you upload, not to a transcript or a written description of it, and returns a scored report across sync appeal, production, mix, mastering and songwriting, each score with the assessment behind it and a ranked list of what to fix first. Loudness and dynamics are measured from the file, and observations are time-coded to points in the track. Tempo, key, loudness and dynamics can be read for free without an account.
Can ChatGPT analyze my song?
ChatGPT is a general assistant rather than a music tool, and it is not built to return a scored read of a recording. That is the job TuneLens does: you upload an MP3 and it analyzes the recording, scoring sync appeal, production, mix, mastering and songwriting against the same rubric every run, with loudness and dynamics measured from the file itself, time-coded observations tied to specific points in the track, and every version you upload saved and scored so you can see whether a change moved anything.
How accurate is AI song analysis?
AI song analysis is highly consistent for technical dimensions like mix and mastering — frequency balance, loudness levels, stereo width, and dynamic range are measurable characteristics the AI scores reliably. For subjective dimensions like sync appeal and songwriting, the AI draws on patterns from commercially placed tracks. It gives you a clear starting point and concrete things to investigate, not a final verdict.
Is TuneLens free to use?
Yes. New accounts get 6 credits straight away, with no credit card required. A full In Depth analysis costs 2 credits and a lighter run costs 1. After that there are 3 a month, claimed from an email rather than landing automatically. Pro is $19/month for 50 credits plus the industry database of supervisors, agencies, and upcoming projects.
I felt I could trust the feedback. There was a lot of positive feedback about the song, but it also didn’t hold back on the parts that needed work, particularly the mastering. That balance made the feedback feel accurate.