Applied Recognition accepted into VMware technology partner program

Applied Recognition has been accepted into VMware’s Technology Alliance Partner Program (TAP) on the strength of Ver-ID Authenticator’s interoperability with VMware’s desktop virtualization products. Ver-ID Authenticator uses face recognition technology to secure access to any legacy network, reducing the potential for “data spills” and exposure to other cyber risks.

“Ver-ID Authenticator was designed ground-up to address the considerations that have slowed the deployment of multi-factor authentication (MFA)”, explains Ray Ganong, Applied Recognition’s Co-CEO. “CIOs and CISOs have acknowledged for some time the risks they’re taking without having deployed MFA, especially for remote network access, but have been frustrated by the lack of a solution that works, is affordable, is simple to deploy & manage, and doesn’t irritate their end-users with a complicated experience. Ver-ID Authenticator is the first and only biometric access control product which meets all these criteria.”

According to the announcement, Ver-ID Authenticator is implemented with a set of plug & play modules that integrate a Ver-ID Server with an organization’s directory service and end-point technologies. An Applied Recognition-provided mobile app is invoked when a user is logging in: the user takes a ‘selfie’, a method which securely authenticates any valid user, and which deters any authorized attempt at access.

“We’re pleased to have been accepted into VMware’s TAP program”, added Don Waugh, Applied Recognition’s Co-CEO. “We’ve made a substantial investment to ensure that Ver-ID Authenticator is able to work flawlessly with thin and zero clients, a technology domain where interoperability with VMware is, of course, critical. Both ARI and our channel partners are now looking forward to accelerated deployments of Ver-ID Authenticator at organizations that rely on VMware’s desktop virtualization products.”

Article Topics

access control  |  Applied Recognition  |  biometrics  |  facial recognition  |  mobile app  |  partner program