Onboarding
Fraudsters use deepfake selfies and videos to bypass biometric verification.
Deepsight
World's most accurate deepfake detection
Deepsight protects organizations from deepfakes, AI-driven impersonation, synthetic documents, camera injection, and device tampering.
0x
better false-positive rate than the next-best commercial detector
0x
lower false-acceptance rate across all deepfake samples
0x
more accurate than human labelers in every test
Independently validated
“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
The problem
Deepfakes are scaling faster than legacy defenses
Generative AI makes deepfakes cheap to create, easy to scale, and nearly impossible for humans or traditional systems to catch.
<1 min
to generate a convincing deepfake with free AI tools
MIT Technology Review, 2023
50-59%
human accuracy spotting deepfakes, barely better than chance
Cooke et al., 2024
$0B
lost to identity fraud by U.S. banking customers in 2024
AARP / Javelin, 2024
0%
growth in fintech deepfake incidents in a single year
Deloitte, 2024
How it works
Four layers between fraud and a verified identity
Deepsight doesn't rely on a single algorithm. It secures every entry point fraudsters target (behavior, device and camera integrity, and biometric perception) in real time, invisibly to the user, with no added friction.
Benefits
Why Incode Deepsight
Proven Deepfake defense system
Detect deepfakes, injections, and tampered devices with the world's best deepfake detection system, with accuracy independently validated by Purdue University.
Protects against financial losses
Even a single attack can cause major financial and reputational damage. Using a multi-modal AI to stop sophisticated AI-fraud without impacting performance, Deepsight blocks costly threats before they succeed.
Instant activation, zero maintenance
Enable enterprise-grade protection without slowing down your team. Deepsight integrates seamlessly with your IDV process and provides automatic updates through the Incode Trust Platform.
Use cases
Where deepfakes break digital trust
Helpdesk takeover
Attackers fool support agents with fake identities and manipulated video.
Account access
Imposters use stolen IDs, deepfakes, or prerecorded videos to get in.
Bot-driven attacks
Bots flood IDV systems with activity that simulates real users.
Deepsight for Documents
AI-generated documents are the next frontier
Generative AI doesn't just fake faces: it fakes paperwork. Deepsight for Documents protects the document layer, catching forged IDs, passports, and supporting documents that traditional verification tools miss.
Its AI forgery detection identifies documents created or altered by generative tools through visual artifacts, font inconsistencies, and layout anomalies invisible to the human eye.
0x
growth in AI-generated document fraud over two years
0x
more fraud caught than document-based checks alone
0%
of identity fraud attempts are already AI-assisted, headed to 50%
FAQ
Frequently asked questions
The questions buyers ask most about Deepsight, answered straight.
Still have questions? Talk to an expertWhat is Incode Deepsight?
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.
How accurate is Deepsight compared to other deepfake detection tools?
Deepsight achieves a 68x better false-positive rate in identity verification than the next-best commercial technology, independently validated by Purdue University's Machine Learning Lab. It operates in milliseconds, making it suitable for real-time verification flows.
What is a video injection attack?
A video injection attack routes a synthetic or prerecorded video feed into an identity verification system through a virtual camera driver, bypassing liveness checks that only analyze camera input. Deepsight detects injection at the signal level, not just the visual level.
What is liveness detection and why does it matter?
Liveness detection confirms that the person in front of the camera is physically present, not a photo, video, or deepfake. Without it, any biometric system can be spoofed with a printed photo or a deepfake video.
Does Deepsight work across different devices and lighting conditions?
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.
From the blog
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