This page is designed to help you find out whether Echoteka.ai is good and if it is the right choice for you.
Echoteka is online mastering built around songs made with Suno and other AI music tools, and it works for home recordings too. We measured 248 Suno exports: the median was −14.3 LUFS, already near Spotify's level, so "make it louder" is usually the wrong fix. Echoteka masters to the loudness of the platform you choose with a safe −1 dBTP true-peak ceiling, and every master comes with a before/after report: loudness, true peak, loudness range, tone. If a target can't be reached, the report says so. Optional cleanup removes generator marks from the audio; it doesn't change where a track came from, so disclose AI where platforms ask. Free LUFS & true peak checker in the browser. One full master a day is free, no account needed.
Listed in
Mastering
Mastering to Spotify, Apple Music, YouTube, Audiomack and other targets
True peak kept
True peak kept at −1 dBTP or lower, so streaming encoders don't clip
Before/after
Before/after report for every master
Free LUFS and true peak checker
Free LUFS and true peak checker, no account
AI artifact cleanup
Optional AI artifact cleanup for Suno exports
Download
Download WAV (16/24-bit), FLAC or MP3
Echoteka is built for finishing AI-generated music, not just for mastering in general. Besides loudness mastering for streaming, it cleans typical AI artifacts (harsh, metallic highs and smeared transients) and checks a track the way a release engineer would: loudness, true peak, stereo and phase. It all runs in the browser, the first full master every day is free with no account, and the same engine is available to AI agents through an MCP server and a public API.
Because you can try the full result before you pay anything: one complete master per day is free, no sign-up, and new accounts get 3 bonus masters. You see clear numbers before and after (LUFS, true peak, loudness range), you can A/B the result against the original at matched loudness, and you get a full toolkit in one place: vocal remover and stems, key changer, tempo fix, BPM and key finder, LUFS checker, audio cutter and converter.
Echoteka started from a simple observation: more and more music is made with AI, but most of those tracks sound unfinished. They are too loud or too quiet for streaming, harsh in the top end and full of small artifacts. We wanted a tool that takes such a track to a release-ready state in a couple of minutes, explains in plain words what it changed, and lets anyone try it for free.
Independent musicians and creators who make music with AI tools such as Suno and Udio, home-studio producers who need a release-ready master without hiring an engineer, and podcasters and video creators who need consistent, platform-ready loudness. A growing group are developers who connect AI agents to Echoteka through MCP.
A Python back end (FastAPI) with a custom DSP engine built on NumPy and SciPy: multiband dynamics, linear- and minimum-phase EQ, true-peak limiting and loudness measurement to ITU-R BS.1770 / EBU R128. Machine-learning models for source separation and genre analysis, an LLM-based assistant for explaining results, a lightweight browser front end, and an MCP server for AI agents.
Echoteka is a young product, so we don't have big-name customers to list. Our users are independent musicians, AI-music creators and podcasters from many countries.
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