Director of Product Management

Identity verification startup Incode launches Deepsight to detect deepfake video calls. Identity verification and authentication startup Incode Technologies Inc. is turning its attention to the challenge of artificial intelligence deepfakes with the launch of a new defensive system called Deepsight. With Deepsight, the startup is taking on a very specific problem with deepfakes, when artificial intelligence is used to generate a fake likeness of real people and impersonate them during video calls. This year has seen a big rise in the number of scammers using AI to clone voices, mimic faces and impersonate real people. Imagine a scenario where someone gets a frantic call from a best friend. Their voice is shaky as the friend explains they have been in an accident and urgently need some money. The caller recognizes the friend's voice immediately - they've known them for years, after all - but it's possible that voice might not be real. The increase in this kind of scam has been staggering. According to Identity Theft Resource Center's 2025 Trends in Identity report, cybercriminals are using advanced deepfake technologies to make such deception almost impossible for humans to detect, which is why such incidents have increased by 148% this year. Humans simply cannot know who they're dealing with anymore, which is why tools such as Deepsight are such an essential development. Incode says the ability to be able to tell real people apart from AI-generated fakes has become table stakes for security, and that's exactly what Deepsight aims to do. The new multimodal AI system is able to analyze video, motion and depth data simultaneously during video calls to surface any potential inaccuracies or inconsistencies that cannot easily be reproduced by generative AI. As Incode founder and Chief Executive Ricardo Amper explains, deepfakes are no longer just novelties posted on social media making fun of people and spreading misinformation. They have evolved to become a major weapon for fraudsters. "When identity can be faked, everything breaks," he said. "Deepsight restores trust by ensuring every capture shows a human user in front of the camera, not a deepfake." The Deepsight system employs a three-layer defense to help understand if a video caller is a real human or an AI fake, and the company claims that it's so accurate that not only will it identify any caller who's AI-generated, but even identify the generative AI model used to create it. Deepsight's behavioral layer works by spotting any subtle interaction anomalies from AI bots or fraud farms, while its integrity layer is used to verify the authenticity of the camera and device being used, so it can detect virtual media. Finally, there's a perception layer that helps to tell apart AI deepfakes from human users by analyzing modalities such as video, motion and depth. The company says Deepsight's effectiveness has already been proven in both the lab and in real world settings. In a recent study by Purdue University, which evaluated 24 deepfake detection systems, Deepsight achieved the highest accuracy and the lowest false acceptance rate among all commercially available tools, outperforming both academic and government models. Shu Hu, assistant professor at the School of Applied and Creative Computing and director of the Purdue Machine Learning and Media Forensics Lab at Purdue University, said it achieved the highest accuracy in identifying fake samples. "This outcome suggests that Incode demonstrates stronger robustness and reliability in challenging real-world scenarios," he added. Meanwhile, Incode's own internal tests reveal that Deepsight was ten-times more accurate than trained human reviewers at spotting AI-generated video callers. The results of these tests suggest that advanced systems are now essential for anyone who thinks they're likely to become the victim of a deepfake scam. Incode said the Deepsight system has already been deployed at a number of enterprises, including TikTok's parent company Bytedance Ltd. and banks such as PNC Bank, Scotiabank and Nubank. It added that it's helping to protect millions of users across more than 6 million live identity sessions so far. The system can be accessed now as part of the Incode Identity Platform, which also provides tools for KYC onboarding, authentication, step-up verification, workforce access and age verification. "AI will change how we live, work and connect," Amper said. "Our responsibility is to make sure it does not destroy the trust that holds it all together." Image: siliconangle/meta AI. 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Incode Agentic Identity links AI agents to verified humans. Incode Technologies has launched Agentic Identity, a solution that enables enterprises to verify, authorize, and continuously monitor autonomous AI agents that they interact with. By linking every agent to a verified human owner, enforcing explicit consent and scope controls, and tracking agent behavior in real time, Agentic Identity brings trust and accountability to the emerging agentic web. Many agents are already transacting, communicating, and making independent decisions, often without direct human supervision. While this is... More

Incode and the Virginia DMV win a Commonwealth Technology Award. Virginia DMV and Incode win the 2025 Commonwealth Technology Award for a privacy first identity verification system that matches selfies to DMV records to stop fraud. Incode Technologies, Inc. is excited to announce that the Virginia Department of Motor Vehicles (DMV) has been honored with a 2025 Commonwealth Technology Award. The Virginia DMV won the Cybersecurity and Privacy Initiatives - State category for its Identity Verification System of Record (SoR) Project, developed in partnership with Incode. The award was presented at the Commonwealth of Virginia's Innovative Technology Symposium, which "brings together more than 600 public-sector leaders, innovators, and changemakers who are shaping the future of technology in government." A breakthrough in Identity Verification. Together with the Virginia DMV, Incode Technologies, Inc. delivered a solution that integrates Incode's advanced identity-matching technology with the DMV's on-premises facial database. This program allows commercial customers, such as banks and truck rental companies, the ability to authenticate users by comparing a live selfie against the user's official DMV photo. * Prevents identity fraud by detecting duplicates and stolen credentials. * Enhances security for residents and businesses. * Streamlines digital interactions with faster, more seamless onboarding. * Safeguards privacy by keeping sensitive data securely hosted on-premises at the DMV, fully compliant with strict state and federal regulations. A new standard for digital trust. Its collaboration with the Virginia DMV represents a major step forward in securing Virginia's digital services. By empowering residents to verify their identities quickly, safely, and with confidence, the DMV and Incode are setting a new standard for trusted, privacy-first digital interactions. Driving measurable impact. The Commonwealth Technology Awards recognize the most innovative and impactful IT projects across Virginia. The SoR Project's win highlights how successful partnerships between forward-looking public agencies and trusted technology providers can deliver measurable impact. By working together, the Virginia DMV and Incode set a new benchmark for secure, citizen-first digital identity verification, one that balances convenience, security, and privacy. How it works. * Capture Data & Selfie - User enters ID info, scans a barcode, or scans their ID card. * Biometric Comparison - Incode compares the session vector against the DMV database vector. * Instant Result - A secure match/no-match response is returned. Easy onboarding options. * Enter state, name, and date of birth. * Scan the barcode on a driver's license. * Scan the ID card (front and/or back). This project serves as an example of how agencies and businesses can partner with technology providers to significantly reduce identity fraud, increase customer conversion rates, and enable fast, seamless onboarding. Shaping a new era of citizen security. As states and agencies across the country work to modernize services and protect citizens from emerging threats like generative AI, the Virginia DMV is leading the way. The SoR Project shows how responsibly implemented biometric identity verification, in collaboration with trusted partners, can deliver meaningful impact at scale. Incode Technologies, Inc. is proud to celebrate the Virginia DMV's success and honored to be their partner in advancing secure, citizen-first innovation. Incode was named a Leader in the 2025 Gartner(R) Magic Quadrant(TM) for Identity Verification. Download the report.