What loudness does it normalize to?

Every file is normalized to -16 LUFS integrated with a -1.5 dBTP true-peak ceiling and a loudness range target of 11 LU, per EBU R128. That is the level most podcast and streaming platforms target, so normalized files play at a consistent, comfortable volume.

Will it squash the dynamics of my audio?

It changes the overall level far more than the feel. The loudnorm filter adjusts gain toward the target and gently controls very wide loudness swings, but it is not a hard compressor, so speech and music keep their character. Extremely dynamic material will sound somewhat more even by design.

What format do the files come back in?

The same format you uploaded where possible: mp3 in → mp3 out, and likewise for m4a, wav, flac, and ogg. AAC uploads come back as m4a, and opus or wma uploads come back as mp3. Every output is re-encoded, so keep your originals if you may need them again.

How does batch normalization work?

Each file is measured and normalized on its own, independent of the rest of the batch, so a quiet memo and a loud track both end up at -16 LUFS. One output per upload, named after the original; a batch downloads as a single zip.

How is pricing calculated?

Normalization is 2 credits per file, with a 2-credit minimum, so one file is 2 credits and ten files are 20 credits.

Yes. No AI model touches your audio. Normalization runs on our own servers, your files are never used to train a model, and everything is auto-deleted 7 days after the job finishes.

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Audio → -16 LUFS2 credits / file

Normalize Loudness

Quiet voice memos and loud music bounces → every file at -16 LUFS, the loudness podcast and streaming platforms target.

50 credits free every month

No card needed

Private files

Add your files

Upload after your free sign-upMP3, M4A, WAV, AAC, FLAC, OGG, OPUS, or WMA · up to 500 MB each

Secure upload

EXAMPLE

UPLOADED · MIXED LEVELS

arrow_forward

NORMALIZED · -16 LUFS

voice-memo.m4a → voice-memo-normalized.m4a -27 → -16 LUFS

interview.mp3 → interview-normalized.mp3 -21 → -16 LUFS

intro-music.wav → intro-music-normalized.wav -9 → -16 LUFS

lecture.flac → lecture-normalized.flac -24 → -16 LUFS

What you get

check_circleEvery file normalized to -16 LUFS integrated (EBU R128)

check_circleTrue peaks capped at -1.5 dBTP so nothing clips

check_circleEach file measured and normalized independently, whatever the batch

check_circleFormat preserved: mp3 in → mp3 out (aac → m4a; opus and wma → mp3)

check_circleA single file downloads on its own; a batch comes back as one zip

How it works

1Upload your audioDrop in any mix of MP3, M4A, WAV, AAC, FLAC, OGG, OPUS, and WMA files, a single clip or a whole batch, recorded at whatever levels they happen to be.

2Every file is normalizedEach upload is measured and brought to -16 LUFS integrated with true peaks capped at -1.5 dBTP, per EBU R128, independently of the rest of the batch. No AI model touches your audio; the normalization is fully deterministic.

3Download at one levelOne output per upload, named after the original: voice-memo.m4a → voice-memo-normalized.m4a, format preserved. A single file downloads on its own; a batch comes back as one zip.

Who uses this tool

PODCASTING

Guests at the same volume

Segments recorded on different mics and calls land at the -16 LUFS level podcast platforms expect, so listeners stop reaching for the volume control between speakers.

VOICE NOTES

Memos you can actually hear

Phone recordings made at arm's length come back at a normal listening level instead of a whisper buried in room tone.

TEAMS & MEETINGS

Recordings from different rooms, one level

Normalize a batch of meeting and call recordings so playback volume is consistent across the whole archive.

EDUCATION

Lecture audio students can play anywhere

Recordings captured from the back of the room or a quiet laptop mic come back loud enough for earbuds on a bus.

MUSIC & AUDIO

Demos at streaming loudness

Bring rough bounces and reference tracks to the same integrated loudness so A/B comparisons are about the mix, not the level.

CUSTOMER SUPPORT

Call recordings ready for review

Exports from different phone systems arrive at wildly different volumes; normalize the batch so QA can listen straight through.

SECURITY

Built for sensitive documents

Bank statements, medical files, case records. Security isn't a feature we added - it's the foundation.

lock

Encrypted in transit

Encrypted in transit over TLS 1.2+, and stored in access-controlled, encrypted object storage. Files are protected the moment they leave your browser.

admin_panel_settings

Your files stay yours

Workspaces are isolated per account. Role-based access shows teammates only what they need.

auto_delete

Deleted, not stored

Files are deleted after processing. Everything runs on our own hardware and is never sent to an outside AI service, so your data is never used to train models.

dnsProcessed on our own hardwareauto_deleteDeleted after processinglockEncrypted in transit