Nodeflux and Intel Offer Vision AI for Any Scale
December 01, 2025
Sponsored Blog
Computer vision is the AI application you’re most likely to see in most contexts these days. It seems that everyone is trying to develop smart cameras or Edge AI devices that can convert video data into intelligence.
Well, Nodeflux and its VisionAIre application are leading the way toward Vision AI, offering the practical flexibility of visual input compatibility alongside the versatility to be deployed at any scale.
VisionAIre is a vision AI integration platform for video analytics surveillance. It is designed to operate as the core and the brain of computer vision systems. Nodeflux claims to offer multiple benefits for users and customers, thanks to advanced AI algorithms and real-time video analytics. If leveraged to their full potential, these capabilities could redefine the possibilities of surveillance.
VisionAIre is most impactful in use cases that involve massive surveillance systems, according to Nodeflux, due to its inherent scalability and power. These include Smart City solutions like public safety video surveillance, sophisticated building security systems that need motion detection, capture, and even facial recognition, and integrated retail store optimization using cameras for in store execution and security enhancement.
VisionAIre consists of three main parts. It has a stream/snapshot platform, vision AI analytics, and an intuitive user interface dashboard. All these tools are best if deployed in Intel Core Ultra edge-AI embedded devices.
The Intel element is key to success for VisionAIre. Intel Core Ultra enables its versatile deployment at scale, ease of integration via open API, flexible visual input compatibility, and customizable dashboards. What’s more, Intel’s processors are flexible and scalable on any server, offering optimized configurations, even on existing multi-brand camera infrastructure and diverse sources such as CCTV/drones.
The list of Intel’s compatible processors is vast:
- Intel Core Ultra 9 Processor 285H (24M Cache, up to 5.40 GHz)
- Intel Core Ultra 7 Processor 265H (24M Cache, up to 5.30 GHz)
- Intel Core Ultra 7 Processor 255H (24M Cache, up to 5.10 GHz)
- Intel Core Ultra 5 Processor 235H (18M Cache, up to 5.00 GHz)
- Intel Core Ultra 5 Processor 225H (18M Cache, up to 4.90 GHz)
- Intel Core Ultra 9 Processor 185H
- Intel Core Ultra 7 Processor 165H
- Intel Core Ultra 7 Processor 155H
- Intel Core Ultra 5 Processor 135H
- Intel Core Ultra 5 Processor 125H
The shortest answer is this: if it's time to figure out how to engineer machine vision or AI-powered computer vision into your biggest networks, VisionAIre is ready and able to help.
Intel’s AI Edge Initiative
This blog is part of a series outlining Intel’s AI Edge initiative. Intel recently unveiled its Intel AI Edge Systems, Edge AI Suites, and Open Edge Platform. These are designed to help partners integrate AI into existing infrastructure and help them jumpstart development and increase trust in their system performance and security.
Intel is collaborating with its software partners to create and optimize AI for edge applications, as illustrated in this series of blog posts. Intel is working with its hardware platforms to specify AI Edge systems that allow for best-fit AI performance for key AI edge workloads and are available in a variety of power levels, sizes, and performance options.
To find out more, visit Intel Solution Hub Applications for Edge AI.
