About Us
We're building trust infrastructure for the AI era
When AI can clone any voice from a 30-second sample, the question "is this real?" becomes a business-critical question. We're building the answer.
Our Mission
Make voice trustworthy again
Voice has always been one of the most trusted signals in human communication. "I recognise your voice" meant something. Today, that assumption is dangerous.
AI voice cloning has gone from a research curiosity to a commercial product in under three years. The same technology that powers voice assistants and audiobooks can now replicate your CEO's voice from a YouTube video — and authorise a wire transfer.
Verified Voice exists so that businesses can verify what they hear, not just hear it. We give teams the tools to detect synthetic and cloned voices before they act on them.
"One fake call can undo months of KYC work. We built Verified Voice because no business should have to take that risk blind."
Verified Voice Team
Founders
Context
Why now
Voice cloning democratised
Commercial voice cloning tools reach mainstream. First documented AI voice frauds in UK businesses.
The problem scales
AI voice fraud attacks increase 400%. UK Finance reports £12M lost in voice-authorised payment fraud.
Verified Voice launches
We ship the first accessible, no-account-needed voice authenticity checker for businesses of any size.
Values
How we operate
Privacy first
We built the product we'd want to use: audio deleted the moment analysis is done, no surveillance, no data brokering.
Speed matters
Fraud decisions are time-critical. We optimise for results in seconds, not minutes.
Accuracy over false confidence
We'd rather report a 'Medium' risk with caveats than give false certainty. Our reports are honest.
Built for real teams
Not just tech giants. We build for recruiters, call handlers, and paralegals — people who need this and have no other option.
Technology
How the detection works
Our detection model analyses audio across 40+ vectors — including spectral fingerprints, prosody consistency, breathing patterns, and artefacts introduced by voice synthesis models. We update our detection continuously as new cloning techniques emerge.
Spectral Analysis
Identifies frequency artefacts from neural vocoders
Prosody Modelling
Detects unnatural pitch and rhythm patterns
Breath & Pause Detection
Natural speech has irregular micro-pauses; synthetic speech often doesn't
Clone Signature Matching
Matches against known TTS model output signatures
Noise Floor Analysis
Synthetic audio often has unnatural silence
Try it for yourself
Upload a recording and get a free authenticity report in seconds.