IronYun Introduces Next-Generation AI Search Solution for Video Surveillance Industry

IronYun, a next-generation cloud computing and big data video search software company, today announced the CAC-AI network video recorder (NVR) product line powered by NVIDIA GPUs, bringing artificial intelligence and deep learning to the video surveillance market.

A key advantage of using deep learning-based algorithms over legacy computer vision algorithms is that these systems can be continuously trained and improved with better and larger datasets. Real-world deep learning applications include handwriting and face recognition, language translation, object classification, medical imaging analysis, self-driving cars, and more.

Leveraging AI and the Cloud to Create a Plug-and-Play Surveillance Solution
IronYun’s new NVR product line is a breakthrough solution for the video surveillance market and uses a deep learning-based search engine. Instead of spending hours sifting through terabytes of video, now users can quickly identify objects such as cars, buses, luggage and pets, along with categorizing people by gender, age, attire, and more.

The CAC-AI video search application leverages the capabilities of IronYun’s CityEyes Cloud and virtualization platform, which plug-and-plays with many of the industry’s leading NVR systems, ensuring quick and easy deployment. To significantly accelerate the application’s rich deep learning capabilities, this new AI-enabled NVR is powered by NVIDIA GPUs.

“IronYun is pleased to partner with the leading GPU provider NVIDIA on bringing AI based video surveillance solutions to our customers.”says Paul Sun, President and CEO of IronYun. “The AI NVR appliance provides enterprise customers with unprecedented speed and performance in video search.”

“AI and GPUs will transform the video surveillance industry,” said Deepu Talla, vice president and general manager of the Tegra business unit. “Companies such as IronYun are able to process and intelligently analyze massive amounts of data through deep learning on NVIDIA GPUs.”