Trust Stamp Announces the Release of Its New Ai-Powered Age Estimation Technology

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Trust Stamp announces the release of its new AI-Powered Age-Estimation technology designed to allow both online and offline enterprises to estimate the age range of a user based upon the capture of a facial image

Trust Stamp, the Privacy-First Identity Company^TM has announced the commercial release of its new age-estimation technology using deep-learning algorithms.

Andrew Gowasack, Trust Stamp’s President, commented, “Understanding the age of online users is critical not only to ensuring that services and content appropriate for mature audiences are not accessed by minors but also ensuring that services that are expressly designed to allow young people to interact are not infiltrated by adult users. This is increasingly being recognized by legislative initiatives, and in some cases, algorithmic-based age estimation is expressly being authorized. As with any product of this type, our technology cannot provide an exact age for a user but does provide a confidence level as to an age range allowing platform operators to focus document-based age verification on a subset of their users.”

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Andrew Gowasack went on to say, “We recently participated in a bake-off against an industry leader in the age verification field and based upon the performance of our deep-learning technology in that test, we are now negotiating the first commercial implementation for the technology. We can deliver this technology as a SaaS application through our Orchestration Layer, as an on-prem installation, via an SDK for integration into mobile applications or, potentially, as a stand-alone application that can run on the edge without Internet access. Although our first potential customer is an online platform, the demand extends to offline venues and can remove the need for more intrusive in-person requirements. This is a very substantial and fast-growing market opportunity for us and an excellent compliment to our existing identity authentication services.”

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