October 14, 2022
Network service providers (NSPs) are between a rock and a hard place. As consumers use a larger variety of connected devices, their expectations for the connected experience are growing rapidly – it has to be optimized for every device. For NSPs, this optimization (as well as some core services) needs a reliable way to detect and identify devices on the network. At the same time, operating systems are increasing end-user privacy with techniques that obfuscate devices and make traditional identification methods obsolete.
Device context goes beyond its hostname or MAC address and provides more information about the type of the device, its hardware capabilities, latency sensitivity and applications that require a lot of bandwidth.
The Need for More Device Context
Device context is an essential part of the data-driven transformation of connected experiences. Knowing what a device is capable of allows the NSP to improve the device’s quality of service and optimize network resources for other devices.
CUJO AI has developed the industry-leading device intelligence solution that provides useful device context, ranging from 4K streaming capability for estimating bandwidth requirements, to hardware specifics that can transform how NSPs approach multi-band Wi-Fi connectivity optimization for every device in the home.
As consumer expectations grow, network service providers that have access to more device context will have a massive advantage in optimizing, improving, and monitoring the connected experience and quality of service for every device in the home. On top of that, these NSPs will be able to make more informed business decisions throughout their organizations.
Getting Device Context with CUJO AI
CUJO AI is set to offer its machine learning device intelligence solution – Explorer – to all interested network service providers. Explorer not only reliably identifies over 50,000 device models, but also offers extensive device context for key device types. As a stand-alone solution, it can be used without committing to a single tool or CPE vendor, and, as evidenced by our existing deployments to identify over 1.7 billion devices, Explorer’s API access provides easy integration to any existing NSP data system.
Explorer’s device intelligence is trained by using machine learning on the largest real-life dataset of devices, the extensive device context it provides is truly unmatched, ranging from a device’s chipset capabilities, to the most important applications that impact the connected experience in the home.
To find out more about why device intelligence is crucial for transforming connected experiences, stay tuned for the release of our latest white paper on device intelligence.