AI-generated songs can shift in level, tonal character and high-frequency texture as they unfold. Built by a producer facing those problems in real mastering work, RESTORE prepares the premaster for the final mastering stage.
When AI-generated songs arrive for mastering, the same issues can keep appearing: related sections that jump in level, gradual volume drift, shifting hats and crashes, and high-frequency harshness or fizz.
RESTORE grew out of those real production jobs. Select the part of your song that sounds right, then use four connected, editable stages to correct inconsistencies and export a repaired 24-bit WAV premaster.
Explore the entire four-stage workflowRESTORE addresses level variation, reference-driven tonal drift, high-frequency excess and spectral balance—before final mastering.
Four-stage AI music premaster restoration.
A connected workflow for level matching, reference-based high-frequency correction, dynamic HF cleanup and spectral clarity. Refine manually and export a mastering-ready premaster.
Explore RESTORERESTORE and professional mastering are separate offerings. Use the restoration software yourself, or explore a hands-on mastering service for the finished release.
Correct unwanted level and high-end inconsistencies across AI-generated songs. Export a repaired premaster; no final mastering is applied.
Final release preparation by a working producer. A dedicated mastering service, with review, sonic decisions and delivery separate from RESTORE's repair processing.
We're planning to offer the processing stages as focused, individual plug-ins alongside the complete RESTORE suite.
Song level + trend
Work with changes in overall level and longer-term dynamics.
Reference tonal character
Use a section you trust as the target for high-frequency tonal consistency.
High-frequency cleanup
A dedicated tool for focused high-frequency repair.
Spectral clarity
Control spectral presentation with independently adjustable processing.
The best tonal reference is the section you choose. RESTORE follows your musical judgment, and its output remains a premaster—not a finished master.
Find the part of the AI-generated recording with the high-frequency character you want to keep.
Analyze the full song for level consistency and tonal deviations, with safeguards for intentional musical changes.
Edit level and tone automation, use the cleanup and clarity stages, then export a 24-bit WAV premaster for mastering.
As AI-generated songs increasingly arrived for mastering, XCENTRiC kept encountering the same time-consuming manual repairs. The high end would shift from section to section. Levels would wander. Hats, crashes and brightness would stop sounding coherent.
Instead of repeating that work one track at a time, he built RESTORE as a focused four-stage processing chain. Producer judgement stays at the center: you choose the reference, review the corrections and control the result.
Read the origin storyIndependent listening comparisons and full-song demonstrations will be published here before commercial sales begin.
See launch statusProducer-built premaster restoration, a growing plug-in collection, and professional mastering—under one independent audio brand.