Do you have technical questions or need support for your Qognify installation?
June 24, 2021
New York — June 24, 2021: Qognify, a trusted advisor and technology solution provider for enterprise operations and safety, today announced it has joined NVIDIA Metropolis, a program designed to nurture and bring to market a new generation of applications and solutions that make the world’s most important spaces and operations safer and more efficient with advancements in AI vision.
Qognify offers various video management IoT solutions that help customers safeguard people and assets. The rise of IP camera deployments and the increasing number of video streams per installation, has made it more essential than ever to add an automated perception layer to the image stream through video analytics, to better understand how an enterprise’s space is being used. This is where NVIDIA with their Metropolis platform comes into play, because the system helps Qognify reliably detect and classify important objects in the video stream.
NVIDIA Metropolis makes it easier and more cost effective for enterprises, governments, and integration partners to leverage world-class AI-enabled solutions to improve critical operational efficiency and safety problems. The NVIDIA Metropolis ecosystem contains a large and growing breadth of partners who are investing in the most advanced AI techniques, most efficient deployment platforms, and use an enterprise-class approach to their solutions. Partners have the opportunity to gain early access to NVIDIA platform updates to further enhance and accelerate their AI application development efforts. Further, the program offers the opportunity for partners to collaborate with industry-leading experts and other AI-driven organizations.
Chen Porat, Vice President of R&D at Qognify, is excited: “The NVIDIA solution does all the heavy lifting for video analytics in combination with our Qognify Video Analytics platform we are planning to roll out to all of our VMS products in the future. It moves resource-intensive calculations to the GPU and thus gives back bandwidth to the CPU to manage other tasks needed by our physical security solutions.”