About
Building voice integrity for the AI audio era
Multi axis forensic audio analysis that screens recordings for AI origin cues, replay artifacts, channel processing, and partial fabrication, then surfaces evidence for human review.
Our story
Developed from academic R&D in forensic audio analysis and now being built into a cloud based voice integrity platform.
The product screens audio for synthetic speech cues across four independent evidence axes: origin, replay, channel processing, and partial fabrication. It returns structured indicators for human review. It is deployed publicly at deepfakedetection.dev with a working analysis lab and case studies based on real world public audio incidents.
Outputs are experimental screening indicators for research, media verification, and awareness workflows, not legal proof of authenticity or fraud. Manual review is always recommended.
Team
Founder
Rana Areeb
Building DeepFakeDetection from forensic acoustics research into a practical voice integrity platform for media, security, and research teams.
Contact
For partnerships, research collaboration, or product questions, email us at the domain address below.