The 60-second test

Tick each box as a service passes. Each card also shows how LuvLang answers, so you can verify us too.

Do this: Upload your own mix and listen to the result before any payment or subscription.

Red flag: Only demo tracks, or you must subscribe first.

How LuvLang answers: Free before/after preview of your own track.

Do this: Louder almost always sounds better at first. Compare with the loudness matched, or the louder version wins every time.

Red flag: No fair way to compare.

How LuvLang answers: Before/after comparison with a level-matched bypass.

Do this: Look for measured integrated loudness (LUFS) and true peak. You can check any master yourself with a free LUFS checker.

Red flag: "Loud" or "pro" with no measurements.

How LuvLang answers: BS.1770-4 loudness and 4× oversampled true peak, shown for your track.

Do this: A good service can name the processing stages it used.

Red flag: "Proprietary AI" and nothing else.

How LuvLang answers: Up to 16 named stages in your master (12 Standard, 14 Professional, 16 Studio).

Do this: For streaming, a true peak at or below about -1 dBTP leaves room for lossy encoding.

Red flag: Peaks above 0 dBTP.

How LuvLang answers: True-peak limiting at -1.0 dBTP with 4× oversampling.

Do this: Know whether you are buying one master or a subscription, and what "unlimited" covers.

Red flag: Price hidden until after sign-up.

How LuvLang answers: One price per master from $9.99, no subscription.

LuvLang details come from our own site; confirm current prices on the pricing page before you buy.

How to read your score

Measure it yourself in 30 seconds

Don't take anyone's word for loudness, ours included. Drop any master into the free LUFS and true-peak checker and see the integrated loudness, true peak and how Spotify, Apple Music, YouTube and other platforms will treat it. For what the numbers mean, read LUFS Explained.

What about the "AI" label?

It tells you how a service picks its settings, not how good the result is. The test above works the same whether a service calls itself AI, automated or engineered. For the full picture, see AI audio mastering vs human mastering.