Every Distributor Kept Flagging My AI Music — Until I Found This
If you’ve been making music with AI tools like Suno or Udio, you already know the frustration. You spend hours crafting the perfect prompt, tweaking generations, picking the best output, and then DistroKid or TuneCore rejects it. No detailed explanation, just flagged. It’s the most deflating feeling in the world.
I went through this cycle probably a dozen times before I stumbled onto something that actually fixed the problem.
The Problem Nobody Talks About
AI music generators have gotten incredibly good at making tracks that sound professional to human ears. But distributors aren’t just listening anymore. They’re scanning for specific technical signatures like spectral anomalies, perfectly quantized timing, unnaturally consistent pitch, stripped dynamic range, and metadata fingerprints baked in by the AI tools themselves.
Your track might sound like a legit synthwave banger, but under the hood it’s screaming “AI made this” to every automated screening tool on the planet. And as distributors get more aggressive about filtering AI content, this problem is only getting worse.
How I Found Undetectr
After my third rejection on the same track from DistroKid, I started digging into what exactly was getting flagged. I went down a rabbit hole of spectral analysis, LUFS metering, and metadata forensics. Turns out the artifacts AI tools leave behind are subtle but consistent, and nearly impossible to fix manually unless you really know what you’re looking for in a DAW.
That’s when I came across Undetectr. The premise is straightforward: upload your AI-generated track, their engine identifies and removes the detectable artifacts, and you download a clean version ready for distribution.
What It Actually Does
The thing I appreciated most is that it’s not a one-trick pony. It addresses pretty much every vector that distributors use to flag AI content:
- Spectral Smoothing removes those unnatural frequency spikes and harmonic patterns that AI generation leaves behind. These are often invisible to your ears but obvious to detection algorithms.
- Timing Humanization is a big one. AI-generated beats are too perfect. Every hit lands exactly on the grid. Undetectr introduces micro-timing variations that mimic how real musicians actually play. Subtle but crucial.
- Pitch Micro-Variation adds organic wobble back into vocals and instruments. Real vocalists and instrumentalists naturally drift in pitch by tiny amounts. AI vocals are unnervingly consistent.
- Dynamic Range Restoration fixes the flattened dynamics that AI tools tend to produce. This restores the natural ebb and flow that human-produced recordings have.
- Noise Floor Normalization is one people overlook. Real recordings have a characteristic noise floor. AI tracks are often too clean. This matches the noise profile to what organic recordings look like.
- Metadata Cleanup is easy to forget about. AI tools embed generation data into file metadata. Undetectr strips all of that and rewrites clean tags.
The workflow itself is as simple as it gets. Drag and drop your file, wait for processing, download the result. Supports MP3, WAV, and FLAC.
The Free Mastering Is a Nice Bonus
Something I wasn’t expecting: every track you process also gets mastered to platform-specific loudness standards. Spotify wants -14 LUFS, Apple Music wants -16 LUFS, and so on. Undetectr handles this automatically.
If you’ve ever paid for mastering separately, you know this alone can run you $20-50 per track. Having it bundled in is a genuine value add, especially if you’re pushing out a lot of tracks.
The Pricing Makes Sense
One-time payment. No subscription. No monthly drain on your PayPal.
In the AI music space where every tool wants recurring revenue from you, this stood out immediately. You pay once and use it for as long as you need. For anyone building a catalog of AI-generated tracks, this pricing model is way more sustainable than yet another $15/month subscription.
Anything I’d Want to See Improved?
It’s not perfect, nothing is. Right now there’s no batch processing, which means if you’ve got a backlog of 30 tracks you’re uploading them one by one. I’ve heard batch processing is on the roadmap though, so that should be sorted soon. For most people processing a few tracks at a time, it’s not a dealbreaker.
I’d also like to see a before/after spectral comparison so you can visually see what changed. It would just add confidence in the process, especially for producers who are protective of their sound. But honestly, the proof is in the results. My tracks are getting accepted now, and that’s what matters.
Who Should Use This?
If any of these sound like you, it’s worth a look:
- You’re generating tracks with Suno, Udio, or similar AI tools and want to distribute them
- You’ve had tracks rejected or taken down by DistroKid, TuneCore, Bandcamp, CD Baby, or Ditto
- You’re building a music catalog for streaming platforms and need a reliable pipeline
- You want platform-specific mastering without paying per track
If you’re producing fully human-made music, you obviously don’t need this. And it’s worth saying, this isn’t going to transform a bad AI generation into a hit. You still need to put effort into getting a quality output from whatever AI tool you’re using. Undetectr handles the distribution side, not the creative side.
Final Thoughts
I’m not going to pretend this is some revolutionary life-changing tool. It solves a specific problem, and it solves it well. Before Undetectr, I had a growing folder of tracks that sounded great but couldn’t get past distribution gates. Now that folder is empty and those tracks are on Spotify.
The combination of comprehensive artifact removal, free platform mastering, and one-time pricing makes it a practical tool for anyone serious about distributing AI-generated music. It does what it says on the tin, and sometimes that’s all you need.
