Adaptive Security
Adaptive Security is OpenAI’s investment for AI cyber threats. Founded in 2024, Adaptive raised $50M+ from investors like OpenAI and a16z, as well as executives at Google Cloud, Fidelity, Shopify, and more.
Adaptive protects customers from deepfakes, vishing, smishing, and AI email phishing with its next-generation security awareness training and phishing simulations. Security teams prepare employees for advanced threats with highly customized training that is role-based, enriched with OSINT, and even features deepfakes of their own executives. Employees train on mobile or desktop and rate the content an incredible 4.9/5 on average.
Customers measure the success of their training program with AI-powered phishing tests. Realistic deepfake, voice, SMS, and email tests track risk across every vector.
Trusted by Figma, the Dallas Mavericks, BMC, and others, Adaptive boasts a world-class NPS of 94.
Want to learn more? Take a self-guided tour at adaptivesecurity.com.
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Sumsub
Sumsub is a full-cycle verification platform that secures every step of the user journey. With Sumsub’s customizable KYC, KYB, AML, Transaction Monitoring and Fraud Prevention solutions, you can orchestrate your verification process, welcome more customers worldwide, meet compliance requirements, reduce costs and protect your business.
Sumsub achieves the highest conversion rates in the industry—91.64% in the US, 95.86% in the UK, and 97.89% in Hong Kong—while verifying users in less than 50 seconds on average.
Sumsub’s methodology follows FATF recommendations, the international standard for AML/CTF rules and local regulatory requirements (FINMA, FCA, CySEC, MAS, BaFin).
Sumsub has over 2,000 clients across the fintech, crypto, transportation, trading, e-commerce and gaming industries including Bitpanda, Wirex, Avis, Bybit, Huobi, Kaizen Gaming, and TransferGo.
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FakeCatcher
Pioneered by Intel, the FakeCatcher deepfake detector analyzes “blood flow” in video pixels to determine a video’s authenticity in milliseconds. Integrated detection in editing software used by content creators and broadcasters. Detection as part of a screening process on user-generated content. Democratized deepfake detection via a common platform, enables any person or entity to confirm the authenticity of a video. Deepfakes are synthetic videos, images, or audio clips where the actor or the action of the actor is not real. ost deep learning-based detectors look at raw data to try to find signs of inauthenticity and identify what is wrong with a video. In contrast, FakeCatcher looks for authentic clues in real videos, by assessing what makes us human— subtle “blood flow” in the pixels of a video. When our hearts pump blood, our veins change color.
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