resemble-detect

Deepfake detection identifies AI-generated or manipulated media across audio, image, video, and text formats. You submit a publicly accessible media URL to receive a structured verdict with authenticity scores, provenance details, and actionable next steps.

Media forensics provenance traces the origins of manipulated media through optional watermarking and intelligence queries. Source tracing, language detection, and emotion analysis provide richer context to verify media authenticity and track its distribution.

Identity verification compares detected speakers against known profiles during audio detection. Running alongside deepfake analysis, this beta capability helps confirm whether the voice matches a verified identity or is synthetically generated.

Asynchronous deepfake detection processes submitted media URLs without blocking your workflow. REST endpoints handle the request and return completed results containing confidence scores, transcription, and structured forensic insights when analysis finishes.

Deepfake detection works across audio, image, video, and text formats to determine authenticity. By submitting a publicly accessible URL, you receive confidence scores and structured insights regardless of the specific media type being investigated.

A complete media forensics workflow combines deepfake detection, intelligence queries, and identity verification. Submitting a media URL triggers asynchronous analysis, returning a structured verdict with provenance, scores, and next steps via REST endpoints.