El sistema de detección de deepfakes más preciso del mundo

Deepsight is Incode's proprietary deepfake and liveness detection engine. It uses a multi-layer AI model to identify AI-generated faces, video injection attacks, and presentation attacks in real time — validated by Purdue University as the most accurate system in its class.

Deepsight achieves a 68x better false-positive rate in identity verification compared to the next-best commercial technology, independently validated by Purdue University's Machine Learning Lab. It operates in milliseconds, making it suitable for real-time identity verification flows.

A video injection attack occurs when a fraudster routes a synthetic or pre-recorded video feed into an identity verification system through a virtual camera driver — bypassing liveness checks that only analyze camera input. Deepsight detects injection attacks at the signal level, not just the visual level.

Liveness detection confirms that the person in front of the camera is physically present — not a photo, video, or deepfake. Without liveness detection, any biometric system can be spoofed with a printed photo or a deepfake video.

Yes. Deepsight is designed for real-world conditions — operating accurately across mobile cameras, webcams, variable lighting, and different skin tones, maintaining consistent performance at scale.