Maastr
Maastr is an AI-powered online music mastering platform that automatically balances loudness, dynamics, EQ, and overall clarity while also providing collaboration, revision tracking, and feedback tools for musicians and audio professionals.
Maastr is a browser-based AI mastering platform built for musicians, producers, mixing engineers, bands, and independent artists who want to turn finished mixes into release-ready masters without building a complex mastering chain manually. Its mastering engine is based on the production and mastering experience of producer and engineer Jay Maas and is particularly tuned for loud, guitar-driven music such as punk, hardcore, metal, and alternative rock, while the company says it can also work across other styles.
The workflow is simple: users upload a track, Maastr analyzes the entire recording, applies automated mastering processing, and returns a mastered version that can be compared with the original. The platform is designed to increase loudness while preserving clarity, dynamics, and the energy of the performance rather than simply maximizing compression. The main website currently supports WAV and MP3 uploads.
Maastr also provides more control than a one-click mastering preset. Active-plan users can adjust mastering characteristics such as dynamic and tonal/color settings, while free users receive a balanced master for evaluation. Its mastering workflow includes X-Y Dynamic Tuning, allowing users to influence how aggressive or relaxed the dynamic processing feels.
A major part of Maastr is collaboration. Users can share projects, leave timeline-based mix notes, manage revisions, store different track versions, compare masters, and keep feedback in one workspace instead of exchanging multiple files and messages.