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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. The engine reads skin texture, motion, lighting and depth irregularities, and detects the digital fingerprints unique to AI generators. Accuracy holds after compression, screenshots and stripped metadata. Three layers defend the session: capture integrity, liveness and forensics. iBeta Level 3 conformance, 0% APCER and 0% BPCER.

PH · launched Sep 23, 2026 · 1 upvote (top 69%) · 0 views

Niche: ai content detection software · 97 launches, 5 in the last 7 days ▼ -50% · Explore this niche →

Category and tags

  • Security
  • Observability & eval
  • B2B
  • AI-native
  • Commercial product
  • Developer Tools
  • Artificial Intelligence
  • Security

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Could you build this?

No Deepfake detection at enterprise scale requires training ensembles of computer vision models on proprietary synthetic media datasets and specialized adversarial ML expertise.

What it would actually take: The architecture requires high-throughput video/image processing pipelines (C++/CUDA, PyTorch/TensorRT) running specialized computer vision networks that analyze facial landmarks, frequency domain artifacts, photonic/rPPG blood flow signals, and GAN/diffusion noise fingerprints. Building this requires specialized computer vision researchers, continuous model retraining against novel generative architectures, and massive labeled forensic datasets.

Competitors

Other products that read as similar to this one : 111 launches clear the similarity bar, closest 8 shown.

Attention rank: #84 of 112 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 324 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.