Bleep out swear words in your videos automatically, and blur speakers' mouths so nothing slips through. Built for creators, podcasters, and media teams shipping to TikTok, YouTube, Twitch and Spotify.
I know censoring content is a pain for editors, not only because it takes up valuable time, but because the typical way of doing it is extremely error-prone. It's a perfect example of 'busy work'. Stuff that needs to be done, but doesn't improve the art, or leave a lasting impact on the consumer. This is the exact type of work that can be handled via automation.
Many existing solutions have handled this to some degree, delivering automated profanity censoring for audio. But none of them go as far as to blur the mouth of the speaker during a profanity. And I thought to myself, "what's the use of censoring the audio, if we're not going to blur the mouth too. That's the most difficult part of the process".
Hence why I created Redactify. An all-in-one video & audio censoring tool to give content creators the confidence to post without feat of crippling their income, and to give media teams a tool that handles the 'busy work', so they can focus on quality whilst still meeting deadlines.
This looks genuinely useful for creators and editors who spend way too much time on repetitive cleanup work. One thing I'd be curious about is how accurate the detection is across different accents and speaking styles.
@henry_habib Hey Henry! Glad to hear you also see the value 😎
It's a great question, under the hood Redactify uses ElevenLabs, which (from what I've seen & experienced) seems to be best-in-class for transcription.
I've tested with a range of accents, but I'd be interested to hear your feedback if you get a chance to try it out yourself!
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For audio/video tools, the edge cases are usually timeline alignment and review speed, not just detection accuracy. A profanity censor that stays frame-accurate and easy to audit is much more valuable than one that is merely clever.
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Redactify
Voquill
This looks genuinely useful for creators and editors who spend way too much time on repetitive cleanup work. One thing I'd be curious about is how accurate the detection is across different accents and speaking styles.
Redactify
@henry_habib Hey Henry! Glad to hear you also see the value 😎
It's a great question, under the hood Redactify uses ElevenLabs, which (from what I've seen & experienced) seems to be best-in-class for transcription.
I've tested with a range of accents, but I'd be interested to hear your feedback if you get a chance to try it out yourself!
For audio/video tools, the edge cases are usually timeline alignment and review speed, not just detection accuracy. A profanity censor that stays frame-accurate and easy to audit is much more valuable than one that is merely clever.