AI Age Estimation: Evaluating Age with AI Technology

What is facial age estimation?

AI Age estimation & in-person age verification

Facial age estimation can be carried out by humans, technology or a combination of both to check that a person is old enough to purchase an age-related product or enter an age-restricted venue or area.

Humans estimate age by assessing various visual cues and lifestyle factors and associate certain characteristics with a specific age or age range. Anyone who works with age restricted goods or services are constantly performing age estimation, evaluating if the customer is old enough is an everyday activity.

Technology driven facial age estimation uses AI and machine learning algorithms to analyse a person’s facial features. Facial analysis software essentially uses different features of a customer’s face to evaluate and estimate their age.

As technology advances, blending both approaches is becoming progressively common for many industries, creating a more seamless, secure, and accurate age estimation process. Humans face many challenges when estimating age such as fatigue, confrontation and distractions, using technology can help staff make informed decisions and reduce any conflict.

Popular Applications

In a physical or in-person setting, age estimation is used for many applications and it has become increasingly important in various industries due to legal, regulatory and ethical factors:

Retail, Convenience & Vending : alcohol, tobacco, vape and lottery sales to prevent underage purchases.
Casino, Gaming & Amusement: on-machine age checks or preventing access to 18+ gaming zones to ensure player protection and underage gambling.

How age estimation technology works

Machine learning algorithms, trained on extensive datasets of facial images, learn patterns and correlations between facial features and age

The age estimation technology analyses a person’s facial features treating it like a pattern

The algorithm compares the patterns in the input image with its learned patterns to estimate the age

Age estimation doesn’t store or compare images to a database of known individuals, unlike facial recognition

The system processes a live facial image and provides an age estimation in real-time resulting in quick and efficient age checks

Benefits of our Age & Identity Solutions

The biometrics team have developed our own hardware and software, achieved by training specialised algorithms called Neural Networks. We train the Neural Networks by showing them millions of faces with known ages, allowing them to learn which facial features are related to a specific age. When a face appears in front of the device, the Neural Networks use what they have learned to estimate the person’s age.

Unlike other systems on the market, we do not use publicly available datasets for training or finetuning, favouring our own extensive datasets especially chosen to reduce gender and ethnic bias. This also makes our system and customer data more secure.

Our technology has received independent certification from the Age Check Certification Scheme (ACCS).

Accuracy Metrics include:

Overestimation: On average, overestimates 18-year-olds by 0.39 years.

Mean Absolute Error (MAE): The MAE, which measures the average difference between the estimated age and the actual age, is 0.94 years.

The Age Check Certification Scheme (ACCS) gave GDPR certification (ACCS 2:2021 Technical Requirements for Data Protection and Privacy) for our age estimation range, providing extra assurance for your business and customers.

Facial recognition technology is entirely different from age estimation technology. Age estimation is completely anonymous, meaning you cannot uniquely identify an individual from the data or the result presented. Furthermore, no data is stored on our the devices—everything processed is deleted immediately afterward and all processing is completed locally on the device and never sent over a public network.

We sell our age estimation products at a fixed, reasonable price which includes software updates and unlimited age checks. So there are no recurring or hidden costs, which are common across the industry. Costs would quickly mount up with a charge per age check – our philosophy is to ensure that age estimation technology is economical, ensuring availability for all business sizes.

While our products do not store any personal data or images of faces, the system can save analytical data. For example, it can record the number of checks performed, the times the checks were conducted, the age profile, and the gender of the customer.

All of this data is completely anonymous and customers cannot be identified, but it provides useful information that can be used to present an audit log of the age-check procedure, gather data on busy periods in the store, and analyse the gender and age profile of customers.

Watch Our Expert Webinar

Watch our on-demand webinar, hosted by Marketing Manager Dayna Patterson, where industry experts including retailers, Trading Standards, and biometric specialists discuss the challenges of human-led age checks and how technology like our MyCheckr can help. With powerful real-world insights, eye-opening statistics, and practical advice, the panel explores how biometric age estimation is shaping the future of compliance, reducing confrontation, and supporting Challenge 25 policies.