Sumsub
Sumsub is an all-encompassing verification platform that facilitates global customer onboarding, accelerates access, lowers expenses, and combats digital fraud effectively. By integrating robust verification processes with enhanced conversion rates across the globe, Sumsub offers a comprehensive suite tailored to diverse requirements, including KYC/AML checks, KYB verifications, payment fraud mitigation, and facial recognition authentication. This versatility not only streamlines operations for businesses but also enhances user experience, making it a preferred choice in the realm of digital verification solutions.
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Adaptive Security
Adaptive Security was founded in 2024 by seasoned entrepreneurs Brian Long and Andrew Jones. Since inception, the company has raised over $50 million from top-tier investors including OpenAI, Andreessen Horowitz, and executives from Google Cloud, Fidelity, Plaid, Shopify, and other industry leaders.
Adaptive defends organizations against sophisticated, AI-driven cyber threats such as deepfakes, vishing, smishing, and spear phishing. Its next-generation security awareness training and AI phishing simulation platform enables security teams to deliver ultra-personalized training that adapts to each employee’s role, access level, and exposure. This training leverages real-time open-source intelligence (OSINT) and features highly convincing deepfake content—including synthetic media of a company’s own executives—to mirror real-world attack vectors.
Through AI-powered simulations, customers can continuously assess and improve organizational resilience. Hyper-realistic phishing tests across voice, SMS, email, and video channels evaluate risk across every major vector. These simulations are fueled by Adaptive’s AI OSINT engine, giving teams deep visibility into how attackers might exploit their digital footprint.
Today, Adaptive serves global leaders like Figma, The Dallas Mavericks, BMC Software, and Stone Point Capital. With an industry-leading Net Promoter Score of 94, Adaptive is redefining excellence in cybersecurity.
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Reality Defender
Reality Defender offers a proactive platform that identifies and neutralizes deepfakes before they escalate into significant issues. The surge of disinformation fueled by deepfakes is alarming, as fraudulent AI methods have become more widely available. Serving as a crucial first line of defense against cybercrimes, Reality Defender responds to the rising tide of these attacks. It meticulously analyzes user-generated content for false elements through its API, Webhooks, and Web Apps, ensuring deepfake detection from day one. Users can access downloadable PDF reports and CSV files or receive immediate notifications about deepfakes via email. With a detection system of government-grade quality, crafted by leading AI research teams worldwide, Reality Defender equips organizations of all sizes with an intuitive layer of protection against the harmful impacts of deepfakes, fostering a safer digital environment for everyone involved.
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DeepFake-o-meter
An innovative platform equipped with state-of-the-art techniques for identifying deepfakes is now accessible for public use. Users have the capability to upload one video file from their computer at a time. Deepfakes refer to AI-generated altered media that can create deceptive portrayals of individuals and their behaviors, which can lead to serious consequences if exploited. The DeepFake-o-meter, developed by the UB Media Forensics Lab, is an open-source solution aimed at detecting deepfake technologies produced by external sources. It provides an intuitive service that analyzes deepfake content utilizing various sophisticated detection methods, ensuring that results are generated securely and confidentially. In addition, it includes an API framework that allows developers to incorporate their deepfake detection algorithms and run them on a remote server. This platform not only supports developers but also acts as a crucial resource for researchers in the field of digital media forensics, allowing them to evaluate and compare the effectiveness of different detection algorithms. By fostering collaboration and innovation, this comprehensive approach significantly strengthens efforts against the irresponsible use of deepfake technology. As a result, it contributes to a safer digital environment where misinformation can be effectively challenged.
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