Deepfake Detection
Catch the deepfake before it becomes a customer
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Deepfake Detection - Catch the deepfake before it becomes a customer

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Shufti catches AI-generated faces, face swaps, synthetic identities and document deepfakes using 40+ ensemble models, not basic image scanning. - Reads skin texture, motion, lighting and depth irregularities - Detects the digital fingerprints unique to AI generators - Holds accuracy after compression, screenshots and stripped metadata - Three layers: capture integrity, liveness, forensics - Catches AI-generated IDs and splicing that OCR misses iBeta Level 3 conformance, 0% APCER and 0% BPCER.

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Hello Product Hunt!

I’m Aroosa Virk from , and I’m excited to introduce .

AI-generated faces, face swaps, and synthetic identities are becoming harder to distinguish from genuine users. Checking whether an image simply looks real isn't always enough, especially when manipulated content can pass basic image and OCR checks.

We built Shufti Deepfake Detection to look beyond the surface and identify signals that can reveal AI-generated or manipulated identities.

Why ?

  • 40+ Ensemble Models
    Combine multiple detection models instead of relying on a single image-scanning approach.

  • Look Beyond the Image
    Analyze signals such as skin texture, motion, lighting, and depth irregularities that can indicate manipulation.

  • Detect AI Fingerprints
    Identify digital patterns associated with AI-generated content and synthetic faces.

  • Resilient to Compression
    Detection remains effective when images or videos have been compressed, screenshotted, or stripped of metadata.

  • Three Detection Layers
    Combine capture integrity, liveness, and forensic analysis to examine different parts of the verification process.

  • Catch What OCR Can Miss
    Detect AI-generated IDs, document manipulation, and splicing that may not be visible through text extraction alone.

Built for Identity Verification

Deepfake Detection works as part of the wider identity verification process, helping teams identify manipulated faces and documents before they become part of a customer journey.

Shufti Deepfake Detection has iBeta Level 3 conformance and reports 0% APCER and 0% BPCER under the relevant evaluation conditions.

Who is it for?

Shufti Deepfake Detection is built for banks, fintechs, marketplaces, regulated businesses, and fraud teams that need to detect synthetic identities and manipulated verification attempts.

As AI-generated fraud becomes more accessible, we'd love to hear from the community: what do you think will be the hardest deepfake attack to detect over the next few years?

is live on Product Hunt. Give it a and let us know what you think.