Made to Spark artwork — Jack Righteous's real-world Cyanite music analysis case study

Cyanite AI Review (2026): Free Plan + Made to Spark Genre Test

Jack Righteous tool review · Real-song test · October 24, 2026

Cyanite AI Review: I Tried Its Free Music Analyzer on “Made to Spark”

I was choosing a DistroKid genre for Made to Spark, but our first suggestion—reggae—didn't match the actual recording. So I uploaded the finished song to Cyanite. Here's what its free analyzer reported, what the scores really mean, and where I still had to make the call myself.

By Jack Righteous · Independent hands-on case study · Updated October 24, 2026

Made to Spark single artwork by Jack Righteous, gold light over a dark horizon

The test track

Made To Spark (Suno V6)

The song throws big brass arrangements, electronic breaks, prominent lead vocals and layered gospel-flavoured responses into the same room. That's exciting to make. It's less straightforward when a distributor asks you to pick a genre.

My question: could a free audio-analysis tool offer something more useful than guessing from the lyrics or the original style instructions?

See the single and lyric video →

First: what Cyanite actually is

Cyanite is an AI-powered music analysis, tagging and search platform. It's not a song generator, mastering service or distributor. You give it recorded music, and it produces descriptions and classifications for how that recording sounds: genres, moods, instruments, rhythmic feel, vocals, energy, key and more.

Its broader products also include natural-language music search, similarity matching, auto-descriptions and business-oriented catalog workflows. For this review I concentrated on the artist-facing web app and the information available from my own upload—not on enterprise features I didn't personally test. Cyanite's feature FAQ provides the official distinction.

The short version: Cyanite helped me get beyond a bad first genre guess, but it did not—and should not—make the final artistic or distribution decision for me.

What does the free Cyanite plan include?

As of October 24, 2026, Cyanite states that new users can analyze five songs per month at no cost in its web app. Standard web-app uploads accept MP3 audio of any bitrate up to 15 minutes per track. The company says analysis typically takes seconds to under 30 seconds, depending on the file. You can inspect music tags and use the web-app views without writing code. Source: Cyanite FAQ.

Capability Free web-app position What it means for a creator
Monthly allowance 5 song analyses Enough to try a handful of singles or release candidates.
File upload MP3, up to 15 minutes per track Use a finished mix or export—not lyrics or a Suno prompt.
Genre and subgenre tags Part of the web-app tagging interface Compare broad genres with narrower labels; some styles don't map neatly to a distributor menu.
Mood, musical character, movement, energy Included in tagging views Useful for describing your song without calling everything “epic.”
BPM, key, voice and instruments Available musical attributes Build a more grounded release brief and playlist pitch.
Segments and representative section Supported within the web-app analysis Compare the whole song with what the chorus or a break is doing.
CSV/Excel export Not self-service for private users Save screenshots or take notes; business CSV and API JSON are separate arrangements.
Edit auto-generated tags Not supported Keep your own corrected notes when a label feels wrong.

Paid options exist for additional credits, including a 20-track-per-month web-app subscription and individual analysis credits. I could not verify a public, fixed price without signing into the billing area, so I'm not quoting one here. Cyanite's newer Auto-Tagging 2.0 introduces additional models such as Vocal Style and Music For, but its announcement invites users to request access. Do not assume every new model or enterprise/API function is available without restriction on the free plan.

Real Cyanite web app screenshot captured during the Made to Spark free-plan analysis
Real screen from my Made to Spark test. Tap or click to inspect the larger image. The web app provides multiple tagging views rather than only a single genre label.

My test: what Cyanite found in “Made to Spark”

I was preparing the single for DistroKid. The initial genre suggestion we were working with leaned on lyrics and style descriptions—especially the Jamaican lead-vocal direction and gospel-style backing. But those descriptions didn't capture the recording's underlying rhythm and arrangement. The actual track has driving electronic production and bright, forceful brass.

So I uploaded the audio to Cyanite's free analysis and reviewed the genre, mood, key, tempo, vocal and time-segmented screens. These are the findings we documented from that session:

130 BPMCyanite tempo result
B♭ majorPredicted musical key
ElectronicProminent genre family in the review
Result What we observed How I used it
Genre direction Electronic dance characteristics emerged more strongly than the reggae label originally proposed. Reconsider the broad primary genre for distribution.
Segmented subgenre Breakbeat/Drum & Bass reached roughly 0.86 in a segment around 1:45. Investigate breakbeat-oriented categories; do not mistake one segment score for a full-song verdict.
Tempo Approximately 130 BPM. More useful music metadata for pitches, production notes and comparing mixes.
Key B♭ major was reported. Helpful starting point for harmonic references and collaborator notes; musical parameters can still merit double-checking.
Mood Energetic 0.72; Happy 0.70; Uplifting 0.66. These descriptors fit the release's celebratory direction, without making the mood a genre.
Voice and arrangement Strong vocal presence, male lead-vocal signal and prominent bass. Build a more accurate promotional description. The bright brass remains an important human listening observation.

How to read the scores: 0.72 or 0.86 is a model's classification strength for a feature, not a claim that 72% or 86% of the song belongs to that category. A segment score belongs to a particular time interval, not automatically to the recording as a whole. Cyanite's model-output documentation explains the difference.

Additional Cyanite music tagging screenshots from the Made to Spark song analysis
Part of the deeper tag inspection from the actual test. Different classifiers describe different parts of the music; a strong tag is evidence, not a replacement for listening.

Why the segment view made a difference

One of the most useful parts of Cyanite is its separation between whole-track analysis and analysis over time. This matters for a hybrid track. A drum break, chorus or instrumental passage can sound quite different from the opening verse. Genre and energy can shift while the identity of the song remains recognizably the same.

In my case, the Breakbeat/Drum & Bass signal was especially strong around 1:45. That's valuable evidence about that passage. It does not mean Cyanite declared the entire track Drum & Bass. The better approach is to compare the result with the full-track classification and then with what your own ears hear across the song.

Further Cyanite analysis view recorded while reviewing Made to Spark
Additional view from the Made to Spark analysis session. A creator can inspect the model's different musical classifications instead of trusting one top-line label.

What Cyanite helped me decide—and what it didn't

For DistroKid, the evidence pushed us toward a working classification of Electronic, with Breaks as the subgenre worth checking and Dance as a secondary genre possibility. Those are distribution menu choices we considered, not exact Cyanite output fields and not proof that DistroKid accepted a particular combination.

The same data helped describe the song more clearly: brass-led electronic dance with breakbeat rhythms, a powerful lead vocal and layered group responses. I trust that description more than calling a song reggae simply because its singer has a Jamaican-influenced delivery. But neither Cyanite nor its scores can tell me whether the lyric works, whether a mix is release-ready, or what kind of emotional connection an audience will make.

A model can identify patterns in the sound. The creator still has to decide what the song is.

What else does Cyanite analyze?

Beyond the results I focused on in this test, Cyanite documents a broader set of music-intelligence categories. These are capabilities of the platform's tagging system, not a claim that I manually verified every category for this one track:

Category What it can help you understand
Genre, subgenre and free genres Broad classifications, finer style families and flexible genre descriptors.
Mood, character, valence and arousal Emotional character, positivity/intensity, and changes across the recording.
Energy, dynamics, movement Whether the track is forceful or subdued, how it moves and how intensity changes.
Instruments and vocal presence What appears in the arrangement, and whether vocals dominate or recede.
BPM, perceived tempo, key and meter Core musical parameters for music notes, cataloging and comparisons.
Segments and representative passage How the song changes by section and which part best reflects the overall sound.
Auto-Descriptions A text summary of defining sonic characteristics.
Search and similarity tools Finding tracks by sound or descriptive prompts; suitability depends on catalog size and plan.
Music-for-use-case and AI music detection Separate or newer offerings that require checking current product availability and access.

Cyanite has continued developing its models. Its August 2026 Auto-Tagging 2.0 announcement adds new use-case matching, vocal-style classifications, revised tempo and instrument models, and more frequent time-segment measurements. Those are important developments, but don't confuse the product roadmap with guaranteed free-plan entitlements. Read the official update.

Where the free tool falls short

  1. No downloadable dataset from the private-user library. If you want to maintain a catalog spreadsheet or reuse numeric outputs, you need to document them yourself or explore business/API options.
  2. No direct tag corrections. When an AI classifier gets a track wrong, you can disagree and keep your own notes, but you can't simply fix the tag inside the web app.
  3. Genres aren't perfectly hierarchical in real music. A hybrid record can trigger tags that are locally accurate but poor labels for the entire single.
  4. Not a mastering or rights audit. A BPM or instrument result doesn't tell you if your mix meets a streaming platform's loudness guidance, or whether a copyright claim is valid.
  5. Other Cyanite products aren't automatically part of this free test. AI Music Detection, exports, large-scale catalog tagging and new API model access need separate scrutiny.

My practical free-plan workflow for other creators

  1. Finish a version of the song. Use the actual exported MP3, not a lyric sheet, prompt, genre wish list or unfinished project file.
  2. Run one analysis. Begin with the primary genre, subgenre, key and BPM, then open the full tag view. A free monthly allowance is valuable—don't waste it analyzing every minor revision.
  3. Read beyond the first label. Check voice, instruments, mood, movement and energy. If your track combines styles, inspect segmented results and the representative passage.
  4. Write down only defensible claims. Record the top genre families, exact numbers shown, and the places where your listening disagrees. Take screenshots because private-user exports aren't available.
  5. Map to your distributor separately. DistroKid's available genre list isn't Cyanite's taxonomy. Pick the nearest useful categories and avoid overstating what the model decided.
  6. Keep the results with the release. Save the report notes beside cover art, masters, lyric files and distribution metadata so the next upload doesn't restart the same conversation.

Who should try it? Independent artists with genre-crossing recordings, producers preparing release metadata, curators organizing a small catalog, or creators learning to describe the actual sound of their music. If you're releasing only a few tracks, five no-cost analyses per month is a useful testing allowance.

Hear the case-study song

You can hear exactly why the genre decision wasn't obvious by playing the Made to Spark lyric video. The release's electronic groove, sharp brass and vocal arrangement are much easier to understand in sound than in a paragraph of labels.

My verdict

Would I recommend Cyanite's free web app? Yes—as a second opinion for understanding a finished recording, especially when genre is not straightforward. In one session I got genre evidence, segment-level detail, tempo, key and mood descriptors useful enough to reconsider our release metadata. That's more informative than guessing from Suno style notes.

I wouldn't treat the output as an absolute answer. I would use it to ask better questions, check my own ears, and make a more defensible decision. For me, that's exactly where an AI tool earns its place in the workflow.

Frequently asked questions

Is Cyanite really free?

The web app currently advertises five music analyses each month at no cost. Paid credits and subscriptions cover additional usage, while some advanced product capabilities have separate conditions. Check Cyanite's FAQ for current limits.

Can Cyanite identify the genre of an AI-generated song?

It analyzes the recording's audio rather than reading the lyrics or prompting instructions. It can suggest useful genre labels, but hybrid songs can be ambiguous. Consider the whole track as well as individual segments.

Does Cyanite upload my music to streaming platforms?

No. It's a tagging and music-intelligence service, not a distributor. You choose and enter your actual genre metadata separately in a distributor such as DistroKid.

Can I download all of my free results?

Not directly from the private-user library, according to Cyanite's current FAQ. I recommend capturing the information you need in notes and screenshots.

Does a Cyanite score mean 86% of a song is Drum & Bass?

No. The number is a model's classification strength for a label in a particular analysis context. A score for one time segment does not define the entire song.


Editorial note: This independent Jack Righteous hands-on review uses an actual October 2026 Cyanite web-app analysis of Made To Spark (Suno V6) and publicly available Cyanite documentation. The selected result values above come from the analysis screenshots retained during our release preparation. We did not run a controlled benchmark of accuracy or test every enterprise feature. There is no suggestion that Cyanite endorsed the track or this review.

Sources and further reading: Cyanite FAQ and current free-plan terms · Web-app genre tagging and library views · August 2026 model update · Model scores and segment interpretation.

Regresar al blog

Deja un comentario

Ten en cuenta que los comentarios deben aprobarse antes de que se publiquen.

articleall levelsHow to Use Jack Righteous
On this page

    Keep Jack Righteous in your Google results

    Make Jack Righteous a preferred source.

    Google can highlight preferred publications more prominently for you in Top Stories, AI Mode and AI Overviews when those features are available.

    The Righteous Beat

    Get the week’s most useful creator guidance, platform changes and free resources.

    Join the free newsletter →