real-time video deepfake detection
Analyzes video streams in real-time to identify synthetic or manipulated video content, including deepfakes created through face-swapping, expression manipulation, or other video synthesis techniques. Processes video frames continuously to flag potential synthetic media during live streaming or post-production review.
audio deepfake detection
Analyzes audio files and streams to detect synthetic or manipulated speech, including voice cloning, speech synthesis, and voice conversion attacks. Identifies audio deepfakes that mimic real speakers or create entirely synthetic voices.
false positive analysis and model feedback
Analyzes detection false positives to identify patterns and improve model accuracy over time. Allows users to provide feedback on incorrect detections to help retrain and refine the underlying models.
image deepfake detection
Analyzes still images to identify synthetic or manipulated visual content, including AI-generated faces, face-swapped images, and digitally altered photographs. Detects artifacts and inconsistencies that indicate image synthesis or manipulation.
batch synthetic media scanning
Processes multiple video, audio, and image files in bulk to identify synthetic or manipulated content across a large dataset. Enables efficient scanning of content libraries, user uploads, or archived media without manual review of each item.
live-stream synthetic media monitoring
Continuously monitors live video and audio streams to detect and flag synthetic media in real-time, enabling immediate intervention during broadcasts. Integrates with streaming platforms to provide instant alerts when deepfakes are detected.
multi-modal synthetic media correlation
Analyzes video, audio, and image content together to identify inconsistencies between modalities that indicate synthetic media. Detects mismatches between lip-sync and audio, facial expressions and voice tone, or other cross-modal anomalies.
confidence scoring and explainability
Provides detailed confidence scores and explanations for synthetic media detections, showing which artifacts or features triggered the detection. Helps users understand why content was flagged and assess the reliability of the detection.
+3 more capabilities