Deepsight protects organizations from deepfakes, AI-driven impersonation, camera injections, and device tampering with unmatched accuracy – because when identity can be faked, everything breaks.
Independent studies, customer stories and verified reviews validate the impact of Incode’s technology.

“We evaluated nine of the most widely used commercial deepfake detection systems and found that Incode’s detector achieved the highest accuracy in identifying fake samples, yielding the lowest false acceptance rate.”
- Shu Hu, Assistant Professor & Director, Purdue Machine Learning Lab
Ranked as the top-performing system in the benchmark across government, academic, and commercial detectors.
Generative AI now makes deepfakes easy to create, cheap to scale, and nearly impossible for humans or traditional systems to detect, creating an existential threat to digital trust.
Time it takes to generate a convincing deepfake with free AI tools.
Source: MIT Tech Review, 2023
Human accuracy in spotting deepfakes, barely better than chance.
Source: Cooke et al., 2024
Lost to identity fraud by U.S. banking customers in 2024.
Source: AARP/Javelin, 2024
Increase in fintech deepfake incidentsin 2023.
Source: Deloitte, 2024
Incode Deepsight is a multi-layered deepfake detection system that blocks fraud across multiple key attack points. By analyzing the behavioral, device and camera integrity, as well as the perception layers in real time, it ensures only real users are verified – stopping AI-driven impersonation fraud in its tracks.
Detect deepfakes, injections, and tampered devices with the world’s best deepfake detection system – with accuracy independently validated by Purdue University.
Fraud evolves quickly and strikes from multiple angles. Deepsight responds in real time, blocking deepfakes at the behavioral, integrity (device, camera), and perception layers (advanced multi-modal AI to liveness detection).
Threats to your business
Deepfakes and physical spoofs that bypass liveness checks
Virtual camera and manipulated video feeds
Devices running in emulators or tampered environments
Bots and automation that mimic real users
Adding new fraud detection layers can increase friction and overheads
Deepsight’s Solution
Detects deepfakes and spoofs with multi-modal analysis across video, motion, and depth.
Identifies virtual camera feeds with camera source validation
Detects tampered devices and emulators with device integrity checks
Flags automated behavior and high-frequency bot activity in real time
Provides frictionless protection, invisible to the end-user and not affecting verification speed
Fraudsters use deepfake selfies and videos to bypass biometric verification.
Attackers fool helpdesk agents with fake identities or manipulated videos.

better false-positive rate than the next-best commercial technology
surpassing human labelers across every test.
Orchestrate identity verification, compliance, and fraud prevention in one platform designed to grow with your business.