ANONYMOUS AGE VERIFICATION
Confirm age without storing a single biometric trace.
Daksam Analytics Anonymous Age Verification estimates a customer’s age range from a liveness check and returns the result. No image stored. No biometric data retained. Only the basic details and the outcome kept on record.
Some sectors need to confirm age but cannot justify holding biometric data to do it. Online gaming platforms, dating apps, and digital entertainment services need to confirm user age without creating a biometric data obligation that goes far beyond what an age check actually requires.Daksam Analytics Anonymous Age Verification was built for exactly this situation. The customer takes a liveness check, the AI model estimates their age range, the result is returned, and the image is discarded. What stays on record is the outcome, not the evidence used to reach it.
THE CHALLENGE
Storing a Face to Confirm an Age Is More Than You Need to Keep
Age confirmation requires a check. It does not require a permanent record of the biometric data used to conduct it. For organisations in privacy-sensitive sectors, keeping an image after the check creates obligations that should not exist.
HOW IT WORKS
The Check Runs. The Image Does Not Stay.
Anonymous Age Verification runs a biometric age estimation from a liveness check. The image is discarded the moment the result is generated. Nothing biometric is retained after the check completes.
Verification Triggered
The customer reaches a point in your app or website where age confirmation is required. Your system triggers the Daksam Analytics SDK at that moment in the flow.
Liveness Check
The customer completes a liveness check confirming they are physically present. A photograph or pre-recorded video cannot pass this step. The check runs in real time.
Age Range Estimated
The AI model estimates the customer’s age range from the liveness capture. The estimation runs on the image at the point of capture and the result is generated immediately.
Image Discarded
The moment the age range result is generated, the image is discarded. No facial image, no biometric data, and no selfie is stored at any point after the check completes.
Result Returned and Stored
The age range result and the customer’s basic details are returned to your system and stored. The record contains the outcome, not the biometric data used to produce it.
CAPABILITIES
Age Confirmed. Biometrics Gone.
Every capability below runs on every Anonymous Age Verification event. The check is thorough. The data retained is minimal.
Biometric Age Estimation
AI model estimates age range from a liveness capture in real time. No document required. The estimation runs at the point of capture and the result is returned immediately.
Liveness Detection
Confirms the person completing the check is physically present and genuine. A photograph or pre-recorded video cannot pass the liveness step before age estimation runs.
Image Discard on Completion
The facial image used for age estimation is discarded the moment the result is generated. No image is stored, transferred, or retained anywhere in the system after the check.
Result Only Record
Only the customer’s basic details and the age range result are stored. No biometric data, no facial image, and no selfie is part of the retained record.
White-Label Presentation
The verification screen carries your institution’s branding throughout. Customers see your name, your colours, and your interface with no Daksam Analytics branding visible.
SDK Integration
Anonymous Age Verification integrates via SDK into your existing app or website. Trigger the check at any point in the customer journey without rebuilding the flow around it.
WHY CHOOSE US
Privacy-first age confirmation. Built for sectors that need it.
Four reasons privacy-sensitive organisations choose Daksam Analytics Anonymous Age Verification for their age confirmation requirements.
No Biometric Data Retained
The facial image used to estimate age is discarded the moment the result is generated. Nothing biometric is stored, transferred, or logged anywhere in the system after the check completes. The only record that exists is the age range result and the customer’s basic details. For organisations under data minimisation obligations, this removes a category of data they should never have needed to hold in the first place.
- Facial image discarded immediately after age range result is generated
- No biometric data stored, transferred, or retained anywhere in the system
- Only the result and basic customer details kept on record
Aligned With Data Minimisation Principles
Privacy frameworks including GDPR, India’s Digital Personal Data Protection Act, and equivalent regulations in the GCC require organisations to collect only the data necessary for the purpose. Storing a facial image to confirm an age threshold is difficult to justify under this principle. Anonymous Age Verification collects the data the check requires and discards everything beyond the result.
- Designed around data minimisation principles across multiple frameworks
- Aligned with GDPR, India’s DPDP Act, and GCC data protection requirements
- Retains only what is necessary: the result and basic customer details.
White-Label by Default
The Anonymous Age Verification screen carries your institution’s branding throughout. Your customers see your name, your colours, and your interface at every step of the check. No Daksam Analytics branding appears at any point. Organisations in privacy-sensitive sectors maintain complete brand consistency through the verification step the same way they do across the rest of the customer journey.
- Full white-label presentation on every screen in the verification flow
- Your brand, colours, and interface visible at every step
- No Daksam Analytics branding visible to the customer at any point
SDK Integration
Anonymous Age Verification integrates via SDK into your existing app or website. Trigger the age check at any point in the customer journey, before signup, after signup, or at the moment a customer tries to access an age-restricted feature. No rebuilding your flow. No additional infrastructure required.
- SDK integrates into any point in your app or website without rebuilding
- Trigger the check before signup, after signup, or at any point in between
- Works alongside other Daksam Analytics products in the same flow
FAQ
What privacy and compliance teams ask about Anonymous Age Verification.
Anonymous Age Verification estimates age range from a liveness check and discards the facial image the moment the result is generated. Nothing biometric is stored, transferred, or retained after the check completes. The only record that exists is the age range outcome and the customer’s basic details. It is designed specifically for organisations under data minimisation obligations where retaining a biometric image after the check creates obligations they do not need.
The customer’s basic details and the age range result are stored. The facial image used to run the estimation is discarded the moment the result is generated. No biometric data, no selfie, and no facial capture is part of the retained record at any point after the check completes.
Yes. The liveness check runs in full during every Anonymous Age Verification event. It confirms the person completing the check is physically present and genuine before the age estimation runs. A photograph or pre-recorded video cannot pass the liveness step. The check is thorough. The image used to conduct it is just not retained after the result is produced.
Anonymous Age Verification is designed around data minimisation principles that apply under GDPR, India’s Digital Personal Data Protection Act, and equivalent data protection frameworks in the GCC. By discarding the biometric capture after the check and retaining only the result, the product is designed to collect no more data than the purpose requires. We recommend your legal and compliance teams review the specific obligations applicable to your organisation and jurisdiction.
Via SDK. The check integrates into any point in your existing app or website without requiring you to rebuild your flow around it. Your product team decides when the age check triggers, before signup, after signup, or at the moment a customer tries to access an age-restricted feature. The SDK handles the check and returns the result to your system. Only the result and basic customer details are passed back and stored.
Age confirmed. Image gone. Result on record. Book a 30 minute demo and we will show you the full Anonymous Age Verification flow running, how the SDK integrates into your app or website, and what the white-label verification screen looks like for your customers.