Creators lose monetisation, sponsors and platform reach over a few bad words. Cleaning them by hand means scrubbing through hours of audio, word by word, and missing one gets the episode flagged.
The story
01
Forty words. Due tomorrow.
Creators lose sponsors and reach over a few bad words, and cleaning them by hand means scrubbing hours of audio.
02
Upload, or go live
Drop in a podcast, video or song, or stream from the browser. Pick beep, mute or rephrase.
03
Listen
Veil isolates the voice first, so it hears every word clearly under music, noise and fast rap.
04
Detect
Multi-layer AI detection flags candidate words, including slang, variations and sound-alikes.
05
Verify
Every flag gets an independent check. Clean look-alikes are protected, so false alarms stay low.
06
Pinpoint and clean
Each word is locked to millisecond timing, and only that word is beeped, muted or rephrased.
07
Clean file, full audit
A clean file in the same format, side-by-side transcripts and a log of every change. Or live to YouTube, a few seconds behind.
What we built
The work that made it.
An engine that hears through the noise
Veil isolates the voice before it listens, so it catches words under music, crosstalk and fast rap over loud beats.
A verification layer we built in-house
Every flag gets an independent check before anything is cut. Clean words that only sound like profanity are protected, so Veil won't bleep your “championship ring”.
Millisecond-level cuts
Each word is locked to its exact timing and the edit is trimmed to just that word. The sentence around it stays untouched.
Live mode, straight to YouTube
Stream from the browser. Veil cleans short rolling segments and relays them to YouTube Live with a few seconds of delay.
A complete product, not a script
Web app, dashboard, side-by-side transcripts, an audit log for client sign-off, reprocessing and bulk download.
How it works
Step by step.
01
Listen
Isolates the voice so lyrics and speech are clear, even under music, noise or effects.
02
Detect
Multi-layer AI detection flags candidate words, including slang spellings, variations and sound-alikes.
03
Verify
Clear cases pass straight through; uncertain ones get a second, closer look. This keeps false positives low.
04
Pinpoint and clean
Locks each word to millisecond timing, applies beep, mute or rephrase, rebuilds the file and writes a context-aware clean transcript.
Web app→Secure API→Job queue→GPU workers→Private storage
Cloud-native, queue-based and GPU-accelerated. Every file runs as its own background job; live audio goes through a real-time gateway in short segments before it reaches the streaming platform.
Features
Everything in the product.
Upload and clean
Audio or video (.mp3, .wav, .mp4) in, a clean file out, in the same format.
Three filter styles
Beep, mute, or rephrase: the word is replaced with a clean spoken alternative.
Side-by-side transcript
Original and clean transcripts next to each other.
Audit log
Every flagged word with its timestamp and what was done to it, ready for compliance.
Go live
Stream from the browser to YouTube Live, filtered in near real time.
Reprocess
Switch the filter style on a finished file without uploading again.
Dashboard
Usage over time, words caught, processing time and bulk download.
Who it's for
— Podcasters and YouTubers who want ad-friendly versions without manual editing
— Music and radio teams that need clean edits of explicit tracks
— Live streamers who want a safety net before audio reaches the audience
— Studios and agencies processing content in bulk for clients
Built with
Cloud-native · Queue-based · GPU-accelerated · English at launch
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