Didit Face Searchv1.1.0

During user registration, upload a selfie to check against all previously verified sessions. If a high similarity match is found (e.g., above 90%), flag the user as a potential duplicate to prevent multiple accounts under different identities, enhancing compliance and reducing fraud risk.

At event check-ins, capture attendee photos and search against a blocklist of banned individuals. Automatically decline entry if a blocklist match is detected, ensuring security without manual review, suitable for concerts or conferences.

Integrate with patient registration systems to compare new patient photos against existing records. Identify potential duplicate profiles to maintain accurate medical histories, reduce administrative errors, and improve data integrity in hospitals or clinics.

Verify gig workers during onboarding by searching their face against all approved sessions. Detect if the same person is registering under multiple profiles to enforce one-account-per-person policies, enhancing platform trust and safety.

Use during Know Your Customer (KYC) processes to compare user selfies with previously verified identities. Flag high-similarity matches for manual review to prevent identity fraud and ensure regulatory compliance in digital asset trading.

Charge customers based on the number of face search API calls made. Ideal for businesses with variable usage, such as startups or seasonal services, allowing low upfront costs and scalability as demand grows.

Offer monthly or annual subscription plans with bundled API credits and premium features like higher match limits or priority support. Targets enterprises with consistent verification needs, providing predictable billing and enhanced service levels.

License the face search technology as a white-label product for integration into third-party platforms, such as identity verification providers or security software. Includes customization and branding options for resellers.