On-device Age Estimation

The first on-device age assurance solution with enterprise-class privacy, accuracy, and security.

Incode protects the privacy of global enterprises

The Problem

Face biometric sharing concerns are growing fast

Modern social platforms, online gaming providers, adult content sites, and AI applications must verify user age to comply with global regulations. But users inherently distrust solutions that transmit their biometric data to a server.

63% of users have serious concerns about sharing their face.
(Identity Theft Resource Center)

Years of data breaches and privacy scandals have made users deeply uncomfortable sending their biometric data to external servers. That distrust creates measurable user drop-off, brand risk, and conversion damage.

The Challenge

Current privacy solutions come with critical gaps

Existing on-device solutions address the privacy problem, but introduce critical gaps that make them unsuitable for enterprise deployment.

Challenge 1: Security is broken

• Deepfakes, synthetic faces, and injection attacks can spoof the system
• A minor can pass as an adult — or an adult as a minor
• A spoofable solution creates direct regulatory liability

Challenge 2: Accuracy is compromised

• Legitimate users are incorrectly rejected
• Age thresholds must be raised to reduce risk
• More users are pushed into additional verification steps

The Solution

Privacy-designed age assurance without tradeoffs

Incode's On-device Age Estimation is the first solution to deliver enterprise-level privacy, accuracy, and security alongside end user convenience.

Privacy

• Age and liveness models run directly on the device. No biometric data ever leaves the user's phone; Incode has no technical path to the user's raw face.

0 facial images leave the user's device

Accuracy

• Server-level precision on-device. Consistent across demographics, skin tones, lighting, and devices.
• 1.08–1.19 Years MAE, optimized for both Adult and Youth age groups

Security

• 99% spoof detection technology against deepfakes, injection attacks, replay attacks, 3D masks, and virtual cameras. The same technology used by 8 of the top 10 U.S. banks.
• 1M+ face-related attacks stopped in 2026 by our technology

Convenience

• Age checks complete, on average, in under 5 seconds with automated capture and real-time guidance. Automatic rerouting when a check fails.
• 92% completion, on average, on the first try.

How it works

Incode's on-device facial age estimation analyzes a user's face in 4 steps to estimate their age, entirely on their device, without ever transmitting the image to a server.

01

The user takes a selfie

The user opens the age check and takes a selfie using their device camera.

02

Capture is automatic

Real-time guidance directs positioning and lighting. Capture triggers automatically once optimal conditions are met.

03

Models run on the device

Incode's AI returns an age range and liveness verdict locally. No biometric image or PII is transmitted.

04

Integrity check run

Incode analyzes metadata on its server to detect spoofing or tampering.

Boost user trust & brand loyalty

Privacy Lens

The face does not leave the device nor appear on screen. Customers can make the experience more privacy-preserving by replacing the raw camera stream with a Privacy Lens that hides the user's face during capture.

Verified by Incode

Privacy Lens

• Blur or pixelate your user's face so it's never visible, not even on their own screen.

Privacy resources

Explore how the Incode Privacy Architecture can protect your business.