DistroShield
DistroShield
We catch AI music from unlicensed studios, duplicate uploads, metadata fraud, and recording-fingerprint identity fraud — before your tracks reach Spotify, Apple, or Deezer. Avoid the litigation time bomb that's hitting distributors who don't filter AI content.
Metered pricing from $0.40/analysis. Batch, webhooks, per-client thresholds.
Try the APIPaste a Spotify URL or upload a track. Get the ISRC and AI verdict in seconds — no signup, no code.
🛡 With paid plans: weekly automatic Shield monitoring — we email you if someone uploads your track to another distributor without authorization.
Analyze a trackThe problem
AI-generated tracks removed by Spotify in the past 12 months (~205,000/day). Voice-cloning ban and DDEX AIGC labeling now live. Read the brief →
Growth in AI music uploads in 16 months. Accelerating.
Spotify, Apple, and Deezer are pulling catalog and withholding payments from distributors who deliver AI content.
Your ingest has no pre-upload filter. By the time a DSP catches an AI track, your catalog is flagged, your payouts are held, and your relationship with the platform is damaged.
What's at stake
AI music doesn't trigger blanket DSP penalties on distributors — but it changes the economics. DSPs are demonetizing and taking down AI streams. Distributors have split three ways: some (Qobuz, FUGA, Deezer) block unlicensed AI at ingest; others (Believe, TuneCore) now route licensed-model AI through a partner lane while still blocking unlicensed; the rest evaluate case-by-case. Same track, different outcomes depending on the ingest layer.
DistroShield gives you the information to decide per-track: which generator produced it, whether it falls under a rightsholder-licensed lane (Warner and BMG have signed with Suno; UMG signed with ElevenLabs; Udio also has major-label agreements), whether it's outside every licensed lane (unlicensed Suno uploads and unknown generators like MusicGen or Riffusion), and whether to distribute, withhold Content ID, or block. The policy stays yours.
The solution
Integrate in 15 minutes. Works alongside any standard distribution pipeline or custom ingest.
POST audio URL + metadata to our API from your ingest pipeline.
Analysis confidence (0–100), classification, and DDEX-ready tags for Apple's Transparency requirements.
Pass, flag for review, or block — at the threshold you set. Webhooks notify your queue.
POST /v1/analyze
Authorization: Bearer ds_...
{
"audio_url": "https://your-cdn/track.wav",
"metadata": { "title": "...", "artist": "...", "isrc": "..." }
}
→ {
"ai_score": 0.87,
"classification": "ai",
"confidence": 0.92,
"recommendation": "block"
}
What's in the response
Every call runs five independent checks in parallel. Your integration decides what to do with each — pass, review, or block — from a single combined recommendation.
Our fine-tuned acoustic classifier analyzes the audio directly — real vocal, synthetic vocal, or AI instrumental. Trained on real distributor catalogs + modern Suno / Udio / MusicGen. Returns generator attribution: Suno (Warner-licensed since Nov 2025, BMG-licensed since Aug 2026; UMG/Sony pending), Udio / ElevenLabs (major-label deals), or unknown (MusicGen/Stable/Riffusion). Distribution and Content ID decisions stay with your policy.
Cross-references ISRC and title+artist against Spotify, Deezer, YouTube in parallel. Catches covers, re-uploads, and tracks already live on DSPs before you distribute a collision.
ISRC format + DDEX completeness + identity fraud (client claims an ISRC that belongs to another artist on Spotify) + artist impersonation + YouTube Content ID fraud (short-track abuse pattern).
Audio-fingerprint match against 100M+ commercial recordings. Detects copyright infringement at ingest: unauthorized re-uploads, covers of released tracks, sample use of commercial recordings, and cross-distributor identity fraud — the same recording registered under multiple artist names on different distributors. The highest-confidence form of copyright check available.
Our own audio-fingerprint index that grows with every analysis. Catches copyright infringement on indie material that public catalogs don't cover — a master previously submitted by another client, cover-of-a-cover chains, and repeat abuse patterns on unreleased tracks invisible to Spotify / Deezer / YouTube. The gap-filler between commercial-catalog checks and true cross-distributor coverage.
See the API docs for the full response shape and per-module detail. Or read two real fraud catches from production, and our take on the RIAA's proposed AI labels.
See the actual output
A single API call, rendered the way your compliance panel would show it. Every module surfaced, every signal explained, one recommendation at the top. Wire the same JSON into your own dashboard, or use ours.
A single POST returns AI verdict, generator attribution, cross-DSP presence, metadata issues, fingerprint matches, and a combined recommendation.
Every analysis produces a cryptographically-signed PDF suitable for takedown appeals, pre-acquisition due diligence, and DSP dispute resolution.
The API returns structured JSON. Wire it into your existing panel or dashboard. This mockup shows one possible rendering — the shape is yours to design.
Real DistroShield output. Sample track data — not a live customer analysis.
Signed certificate
Cryptographically signed by DistroShield. Timestamped UTC. Hash-verifiable at /verify without contacting our servers. This is the artifact your artist attaches to a takedown appeal, that your compliance team files with DSPs, and that a marketplace investor sees before tokenizing a royalty stream.
PDF, 15 KB — inspect it in a reader, share it with your legal team, forward it to a DSP.
Generators detected
Our model is trained and validated on real audio from the AI generators flooding ingest pipelines today. Coverage extends beyond the trained set through the underlying acoustic representation — new architectures get caught by family.
Versions through v4. Vocal + instrumental.
Meta's open-source model. Small / Medium / Large.
Same architecture family as Suno.
Stability AI. Caught via backbone.
Spectrogram-based generation.
Loop-based and template generators.
New generators are added to training as they emerge in client pipelines — production review verdicts feed the next model version directly. Per-generator performance is shared in private benchmarks during evaluation. See methodology in docs.
Apple Transparency Tags
Apple Music announced AI Transparency Tags in early 2026 — disclosure metadata for artwork, audio, composition, and music video. Today they're elective. Soon they're mandatory, and the distributor is the party responsible for setting them in DDEX.
Most detection tools stop at a score. DistroShield is built so the detector's verdict and the disclosure metadata can be emitted in a single payload — when Apple finalizes the spec, your pipeline is already wired for it.
One API call returns the AI verdict in a structure designed to ship the DDEX disclosure fields alongside it — no second integration when the policy hardens.
Disclosure field names and value sets land in the response as Apple Music's transparency taxonomy is finalized — mapped to DDEX 4.3, no guesswork on your side.
Spotify and Deezer disclosure schemas plug into the same response shape as their specs publish — one integration, multi-DSP coverage.
Why not a DSP's detector?
Deezer now licenses its internal AI detector to third parties — but that solves a DSP-side problem, catching AI that already entered their catalog. Your penalties are already triggered.
Distributors shouldn't buy infrastructure from the same platforms that penalize them. DistroShield is neutral — no conflict of interest.
Standard pipeline integration, DDEX-native output, distributor-scale pricing — not enterprise DSP licensing.
Apple Music AI Transparency Tags, Spotify disclosure, NO FAKES Act, EU AI Act — handled in one API call.
Blocks YouTube Content ID rejection, Spotify anti-spam flagging, and Deezer demonetization — all pre-upload.
Why us
Our first pilot customer is Mh Musik, LLC — a working distributor processing 400+ releases per month across a 25,000+ track catalog. Every feature is validated against real catalog pressure before it ships to you.
Our detector learns from a blended dataset: verified human tracks from working distributor catalogs, AI samples from Suno, Udio and MusicGen, plus real production uploads labeled by QA teams. Not academic benchmarks.
We know Merlin, FUGA, Revelator, SonoSuite, AudioSalad, CI, DDEX formats, and DSP penalty mechanics from the inside.
Spanish-language support, serving markets other tools ignore.
Pricing
Start with a 7-day free trial — 50 analyses, no card. Pay-as-you-go from there, or pick a plan when volume justifies it. Every tier includes the full detection engine: AI scoring, duplicate check, metadata validation, and recording fingerprint match.
Under ~620 tracks/mo? PAYG is usually cheaper than Starter.
Best-value break-even vs Starter: ~2,500 tracks/mo.
Above 3,750 tracks/mo? Let's talk contract.
All prices in USD. Pricing may change with 30 days' notice for new billing periods. Plans don't auto-upgrade — you're always the one to switch.
Sign up
One-click signup with Google, or fill out the form below. Either way you'll get an API key in seconds. No credit card. Cancel anytime.
Are you an individual artist checking a single track? Use our free Lookup tool instead — no signup, no API integration required.
Your trial is active. We've also emailed your API key to you for safekeeping.
⚠ This key won't be shown again. We don't store it in plaintext — if you lose it, you'll need to regenerate.
curl -X POST https://api.distroshield.com/v1/analyze \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"audio_url":"https://your-cdn.com/track.mp3"}'