I've been loving the app. The audio restoration works amazing on my suno songs
These generations were shared by Neural Analog users
Have you ever wondered why compared to commercial releases your music sounds... different? It's simple. Producers use a secret sauce and you don't (at least, not yet).
The music you made is amazing. Your track deserve that extra sparkle.
Turn your music streaming-ready with optimal loudness and tone, up to platform and genres standards.
I've been loving the app. The audio restoration works amazing on my suno songs
Neural Analog makes me feel like a monkey with an AK-47, in the best way possible
It worked! Well done :) Many thanks :))))
Wow thank you so much i upscale videos and take out live recordings from music because of my autism i hate the crowd
Amazing tool for audio. Clean, simple, and effective. I would spend hours in RX to get the same results. Give it a try. I can save you hours of production time.
IMDK
I love the interface. I love the bulk upload/download features. They're a life saver! Also I just realized that Apollo is magic and I don't even need to use denoise. Apollo somehow removes noise much more naturally. So I'm actually spending way less credits than I expected.
The Grim Tower
Love it! Makes everything crisp!
Shrunken Head
IT'S GREAT
Francisco
Sensacional
Tommi, Studionet
Highend services!
Bjark
Easy to use and high quality results.
Eve
amazing!!!! love this! THANK YOU! I just discovered batch dl, this feature SAVED ME
AI audio enhanced with Neural Analog
LUFS (Loudness Units relative to Full Scale) is the standard measurement for perceived audio loudness. Spotify, Apple Music, and YouTube automatically adjust every song to around -14 LUFS. If your track is louder, they turn it down. If it's quieter, they leave it as is—making it sound weak. Matching this target gives you consistent playback and competitive loudness.
Use the Loudness Penalty Analyzer or LUFS analyzer to measure a file before release, then use Automatic Mastering if you need to hit a target safely.
A basic volume boost turns everything up together. If the peaks hit 0 dBFS, the file clips, dynamic range collapses, and harsh frequencies can become more obvious. That is different from mastering.
Neural Analog mastering uses limiting, loudness targeting, and tonal balance controls so the track can get louder without simply clipping. If the source is a compressed AI-generated MP3, restore it first with Audio Restoration, then master the restored file.
The mastering process preserves your original creative intent. Your track will sound clearer, more present, and competitively loud without sounding squashed or distorted.
Yes. However, for AI-generated MP3s, you can achieve even better results by first using Neural Analog's Audio Restoration service to rebuild missing frequencies, then mastering the restored file. This two-step process gives you the highest possible quality.
No. They solve different problems.
If your file sounds compressed, old, muffled, or artifacted, restore it first with Audio Restoration. Then master the restored file with Automatic Mastering.
For a deeper explanation, see the restoration versus mastering FAQ.
A single restoration model may not fix every problem. If the track sounds flat or weak in the low end, try a stem-based pipeline:
UniverSR is better for missing high frequencies. Neural Remix and EQ are often better starting points for bass, muddiness, or low-end problems.
Use stem splitting when one part of the song is the problem, and use mastering only after the mix balance is already close.
Your songs deserve to be heard at their best. Stop settling for quiet uploads and boring tone.