Deepfake detection for fact-checkers
Investigate manipulated media with forensic evidence. Produce debunks your audience can trust.
The Challenge
Misinformation is outpacing manual verification
Fact-checking teams face an exponential increase in synthetic and manipulated media.
AI-generated videos are becoming cheaper, faster, and harder to detect visually. Fact-checkers need forensic tools that go beyond pixel-level inspection — analyzing compression signatures, metadata, motion physics, and audio-visual alignment.
Manual frame-by-frame analysis doesn't scale. Automated tools that produce only a single score without explanation aren't credible enough for publication. Fact-checkers need explainable forensic results.
ClipForensics for Fact-Checkers
Explainable forensic evidence
Multi-module analysis
15 independent modules ensure no single detector failure causes a wrong verdict. Cross-validated evidence.
Confidence scoring
Every verdict includes a confidence interval. When evidence is weak, we say 'Inconclusive' rather than guessing.
Publishable reports
Reports detail per-module findings with evidence descriptions suitable for inclusion in fact-check articles.
Provenance checks
Verify content credentials and origin metadata to establish where footage came from before analyzing pixels.
Compression history
See how many times a video has been re-encoded. Complex encoding chains often correlate with manipulation.
URL ingestion
Paste URLs from YouTube, TikTok, Twitter, Facebook, and other platforms. No manual download required.
Integration
Fits your fact-checking workflow
ClipForensics is designed to be one tool in your verification toolkit — not a replacement for editorial judgment. Use it alongside reverse image search, geolocation, source verification, and your existing ClaimBuster or similar workflows.
Our API allows programmatic analysis for organizations processing high volumes of user-submitted content. See API documentation for details.