Cloud-Native Liveness Detection: Modernizing Fraud Prevention

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Traditional on-premise liveness detection systems can be costly, difficult to scale and maintain, and slow to respond to evolving fraud techniques such as AI-generated deepfakes, creating security and operational risks. Cloud-native alternatives provide elastic capacity, continuous deployment of updated AI models, reduced infrastructure management, and integration with broader security systems, allowing organizations to adapt more quickly to demand and emerging threats. The discussion presents Didit as an AI-native, modular cloud platform offering passive and active liveness checks, configurable verification workflows, detailed reports with confidence scores and risk warnings, and APIs and SDKs intended to simplify developer integration. Its pricing model, including Free Core KYC, no setup fees, and pay-per-successful-check billing, is positioned as a way for businesses to implement advanced identity verification with lower initial costs while maintaining a streamlined user experience.

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