RealNetworks appoints Jay Burrell
02 May 2019 16:54 GMT

 RealNetworks has announced the appointment of Jay Burrell to the position of chief revenue officer (CRO) for computer vision.

Burrell will bring more than 20 years of leadership experience at esteemed companies, including executive roles at GE, IBM, and Microsoft. In this new role, Burrell will lead worldwide sales and business development for RealNetworks' facial recognition platform, SAFR, reporting to Max Pellegrini, Real's President.

"We are thrilled to have Jay join us to help take our SAFR business to the next level," said Rob Glaser, Founder and CEO of RealNetworks. "Jay brings deep experience from his work at well-respected and high-growth businesses. Further, he embodies the drive, focus and diligence required to make SAFR a market leading business that scales rapidly."

"The facial recognition market is growing at an exponential rate, with a variety of uses cases for businesses and individuals alike," said Burrell. "SAFR has already shown real market leadership with its performance and accuracy, but this is just the beginning. I have been following RealNetworks for some time, and the opportunity to be part of the recreation of an industry icon is exactly what a technology executive dreams of. I look forward to working with the incredibly innovative SAFR team to build on our momentum and grow into new markets and regions."

Prior to joining RealNetworks, Burrell served as the senior vice president and general manager of digital technology at GE Healthcare. In this role, he launched the digital platforms within one of the world's largest healthcare companies. Before that, he oversaw IBM Cloud as global vice president, where he was instrumental in the initial stage of IBM establishing itself as one the leading players in global cloud infrastructure and services.

SAFR is an AI-powered facial recognition solution, optimized for live video and architected to economically scale with high performance and rapid processing to detect and match millions of faces in real time. SAFR's 99.86% accuracy rate is balanced by industry-leading performance that delivers results 3-5 times as fast as competing facial recognition algorithms. In April 2019, published resultsfrom a National Institute of Standards and Technology (NIST) test found the SAFR algorithm tested as both the fastest and most compact amongst algorithms for wild images ­- faces in motion, under poor lighting conditions, misaligned, or partially obscured - with less than 0.025 FNMR. SAFR supports flexible deployment - including on-premises, cloud or hybrid - and is adaptable to a variety of use cases, including secure access, multi-factor authentication, liveness detection, door locks, lighting, analytics, reports, and more.

Industry Events