Work from the arrangement toward the master
Mixing determines how the parts work together. Mastering prepares a selected mix for its listening and delivery context. Neither step benefits from treating every generated track as if it has the same fault. Begin with a clear description of what needs changing and preserve the source before you experiment.
If a vocal competes with a guitar, address their balance where you have separate control. If one syllable chirps, investigate that event before applying a whole-song chain. If the recording already has the right balance and impact, a restrained master may be enough.
Pick the guide for your stage
Use stem cleanup to check alignment and decide which leakage matters in context. Use metallic vocal repair for persistent ringing or harshness. Once the mix is stable, follow the AI music mastering checklist.
At every stage, compare the original and candidate at similar loudness. Keep an exposed passage, a dense chorus, and a quiet ending in the listening set. Check that an improvement in one section does not damage another.
Meter readings support those decisions. Spotify’s normalization guidance describes playback behavior; it does not turn one loudness number into a universal admission requirement. Read the intended recipient’s delivery specifications and preserve the dynamics that suit your music.
Evaluate automation with the same standard
An automated service can offer another candidate to compare. Our Undetectr review explains why we recommend it and how it fits a Suno release workflow.
Approve the actual exported file after a full listen, and retain the premaster and project. Continue to the release-ready hub for records and destination checks. A better-sounding track is a production result; claims about provenance or acceptance need their own evidence.