Sealed Rose
Autonomous neural forensics, deepfake detection & cryptographic media verification.
The problem
Hyper-realistic generative video and cloned voices make digital impersonation and deepfake fraud trivial, leaving platforms, buyers, and creators unable to verify digital authenticity.
What we built
Sealed Rose delivers instantaneous multi-model neural media forensics, deepfake detection, and cryptographic proof of authenticity with zero data retention.
Sealed Rose provides autonomous digital media forensics and authenticity verification across video, images, and audio. Built on an ensemble of frame-by-frame temporal consistency detectors, optical flow discontinuity analyzers, and spectral audio models, it pinpoints AI generation from Sora, Kling, Veo, Wan 2.1, and Runway while guaranteeing complete client privacy through ephemeral in-RAM processing.
Highlights
- Frame-by-frame neural deepfake and face-swap detection across leading video models (Wan 2.1, Kling, Sora, Veo, Runway)
- Multi-model comparison matrix benching spatial anomalies, optical flow discontinuity, and temporal jitter
- 100% ephemeral in-RAM analysis with zero media data retained or stored
- Cryptographic origin seal and signed forensic PDF audit report generation
- Sub-450ms temporal inference with real-time audio and video streams
Inside the app
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