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One detector, many decisions.

Updated July 2026

Whoever has to decide whether a recording is real, a fraud analyst, an editor, an investigator, a developer, reaches the same model. These are the ways teams put an AI voice verdict to work.

One verdictMany uses
Output
Probability + model
Speed
Under 0.48s
Fraud and security

Stop cloned-voice fraud before the money moves

Cloned voices now authorize wire transfers and pass phone checks. Fraud and security teams at banks and call centers use the detector to screen flagged recordings for executive-impersonation (CEO) fraud, vishing, and family-emergency scams, then keep a citable verdict for the case file. It fits a review workflow, not a live switchboard: we analyze recordings after the fact and integrate through the API, never by intercepting live calls. See the fraud detection use case.

Newsrooms and journalism

Verify audio before you publish

Fabricated "leaked" clips and manipulated candidate audio move faster than a correction. Newsrooms verify suspicious recordings before publication and cite the verdict, with a published methodology that holds up in editorial review. The detector reports confidence honestly and says when it cannot tell, which is exactly the caution an editor needs on deadline. See the newsrooms use case and our note on deepfakes in elections.

Legal and investigations

Authenticate audio for a case

Recordings enter disputes, custody matters, and investigations already suspect. A saved verdict provides a probability, a confidence level, a methodology version stamp, and a one-way fingerprint under a permanent citation URL that an opposing expert can reproduce. It is a documented analysis, not a ruling on admissibility. See the legal and investigations use case.

Developers

Build the verdict into your stack

The deepfake voice detection API returns the same JSON verdict as the public detector, with webhooks for bulk and async jobs, so screening runs inside your own tooling. For the product framing, see deepfake voice detection; to identify a suspected generator, start from the detect pages.

How it works

The same model behind every use case

Whatever the surface, the detector reads the acoustic fingerprint of a clip, the spectral, prosodic, and timing traces synthesis leaves behind, and returns a probability, a confidence level, and the source model where recognized, usually in under half a second. It works on cloned and stock voices alike, and returns an honest "unknown synthesis" when it cannot attribute the source.

01 . Submit

Drop or POST a clip

Use the public detector, the browser extension, or the API. MP3, WAV, M4A, WebM, or a video's audio track.

02 . Score

Read the verdict

Probability, confidence, and the named model in about half a second, with honest confidence on compressed audio.

03 . Cite

Save and act

Keep a permanent citation URL and fingerprint for a case file, a story, or an audit trail.

0.48s
Median verdict
99%
Accuracy on clean audio
24+
Generators named
24h
Audio deleted after
FAQ · Solutions

Common questions

Who uses AI voice detection?
Fraud and security teams at banks and call centers, newsrooms and fact-checkers, investigators and legal teams, and developers integrating detection through the API. The common need is a citable answer to whether a recording is a real human voice or a machine-generated one.
Is it real-time call monitoring?
No. We analyze recordings after the fact, a saved voicemail, call recording, or voice note, and integrate through the API into review workflows. We do not intercept or monitor live calls.
Can I try it before integrating?
Yes. A single verdict is free with no account through the public detector. The API and higher volumes begin on the paid plans.

Put a verdict to work.

Free for a single verdict. API and volume on Starter and above.

Open detectorSee pricing