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HOW IT WORKS

A Cleanup Flow, Not A Black Box.

A technical but easy-to-understand path from raw AI output to a cleaner, release-ready file. Five stages, one signal pass.

THE FLOW

Five stages of the cleanup signal

SOLUTIONrelease_ready(t) =
  1. 1
    STEP 01

    Generate your track

    Create your track in Suno, Udio, or any AI music tool, then export the final audio file.

  2. 2
    STEP 02

    Upload or process through Undetectr

    Run the file through the Undetectr cleanup engine — the underlying technology EraseAI points creators toward.

  3. 3
    STEP 03

    Reduce synthetic artifacts

    Lower transient roughness, metallic edges, harsh high-end, and repeating watermark-like patterns.

  4. 4
    STEP 04

    Review the cleaner output

    Compare the result against the original and confirm the creative core is intact.

  5. 5
    STEP 05

    Prepare for mastering, publishing, or distribution

    Hand off a sharper file to your mastering engineer or upload workflow.

▸ result:cleaner, release-ready track
WHAT GETS CLEANED

The artifacts a cleanup pass targets

TRANSIENTS

Tame rough transients

Soften the brittle, clicky edges that reveal synthetic generation.

HIGH-END

Calm harsh highs

Reduce metallic, piercing frequencies that fatigue the ear.

REPETITION

Break robotic repetition

Address watermark-like patterns that loop too perfectly.

THE DETAIL

What happens inside each stage

The five steps above, unpacked — so nothing feels like a black box.

Generate. Everything starts with your raw export from Suno, Udio, or another AI tool. The most important habit here is to export the highest quality file available — a WAV or lossless file gives the later stages more signal to work with than a compressed MP3, which has already thrown detail away.

Process. The file goes through the cleanup engine EraseAI recommends, Undetectr. Rather than a generic denoiser, this is a pass tuned for the specific artifacts AI generation leaves behind, so it can be more targeted than a stack of general-purpose plugins.

Reduce. This is the core of the work: lowering transient roughness, calming metallic and harsh high-end, and breaking up the watermark-like repetition that makes a track read as machine-made. The aim is subtraction of the synthetic edge, not addition of new color.

Review. Always compare the cleaned output against the original. A good result removes the synthetic tells while leaving the melody, lyrics, and feel untouched. If the track suddenly sounds like a different song, you have gone too far — dial it back.

Prepare. Hand the cleaner file to your mastering step or upload workflow. Cleanup gives mastering a better starting point; it does not replace it, and it does not guarantee approval from any distributor or platform.

DON'T CONFUSE THESE

Cleanup is not the same as mastering

Artifact cleanup

First

Reduces the synthetic signatures AI generation leaves behind — metallic vocals, harsh highs, robotic repetition. Fixes the source texture.

Mastering

After

Sets final loudness, tonal balance, and stereo width for release across platforms. Polishes an already-clean file — it does not remove AI artifacts.

Run them in order — cleanup, then mastering. Mastering an artifact-heavy file tends to amplify the very edges you want gone.

FINAL SIGNAL

Ready to run the cleanup equation?

Move your AI track through a cleaner signal path. We recommend Undetectr.

Independent · We recommend Undetectr