Scaling Face Search (1:N) with the Didit Android SDK
Blog post from Didit
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Didit's Android SDK offers a streamlined solution for integrating 1:N Face Search into mobile applications, enhancing biometric identity verification and fraud prevention. The SDK, designed with a developer-first approach, simplifies the complex process of comparing new user biometrics against a database of verified identities, which is crucial for detecting duplicate accounts and synthetic identity fraud. It features configurable security settings, such as customizable facial similarity thresholds and automatic decline conditions, ensuring alignment with specific risk profiles. The SDK's modular AI-native architecture supports seamless integration, providing tools for camera handling, liveness detection, and NFC verification, while abstracting complexities to focus on user experience. Didit's free core KYC tier, absence of setup fees, and pay-per-successful-check model make it an accessible and cost-effective solution for businesses seeking to implement robust identity solutions. The platform emphasizes privacy and data security by encouraging minimal data retention and compliance with regulations, and it supports automated review workflows to streamline fraud prevention processes.
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