Faceoff Handles Synthetic Frauds from Deepfake Videos

Faceoff’s 8-model AI architecture is uniquely designed to detect and counter synthetic fraud by exposing biometric inconsistencies that deepfake videos cannot convincingly mimic.

Faceoff goes beyond visual forgery, identifying psychophysiological gaps that only real human behavior can produce — making it resilient against even advanced AI-generated fraud.

How Social Media Platforms Can Solve Their Problem Using Faceoff

Integration Strategy for Platforms:

1. API-Based Trust Scanner: Integrate Faceoff as a real-time or pre-upload content scanner, assigning a Trust Factor (1–10) to each video using lightweight API calls.
2. On-Premise & Private Cloud Compatibility: Social platforms can host the Faceoff engine on their own infrastructure, ensuring no video leaves their ecosystem, preserving user privacy.
3. Automated Flagging System: Based on Faceoff’s trust score, platforms can:
   1. Flag suspicious content for moderation
   2. Restrict distribution of low-trust content
   3. Inform viewers of AI-detected tampering
4. Content Authenticity Badge: Verified high-trust content can receive authenticity badges, increasing transparency for users and advertisers.

Benefits to Social Media Organisations:

• Protect platform integrity without sacrificing speed
• Comply with evolving global AI/media regulation
• Prevent scams, political manipulation, and defamation
• Build user trust by fighting misinformation at scale

Faceoff empowers platforms with proactive synthetic fraud mitigation using AI that thinks like a human — and checks if the video does too.