Cisco has unveiled a new computing platform designed specifically for AI workloads on the edge.
Announced at the company’s annual partner summit, Cisco Unified Edge will combine computing, networking, and storage capabilities in a single platform to provide “real-time AI inference” and support for agentic AI workloads.
Cisco said the new platform is aimed primarily for organizations operating in data-intensive sectors, such as healthcare, manufacturing, and retail.
The networking giant noted it has “partnered closely” with customers across the aforementioned industries to design the platform.
"Today’s infrastructure can’t meet the demands of powering AI at scale,” said Cisco president and CPO, Jeetu Patel.
“As AI agents and experiences proliferate, they will naturally emerge closer to where customers interact and decisions are made – the branch office, retail store, factory floor, stadium, and more.
“That’s where compute needs to live. With our Unified Edge we’re making it easier to power AI in the real world with flexible, secure systems that are simple to deploy, operate, and scale as demand grows.”
So what can customers expect from the new edge AI platform?
Under the hood of Cisco Unified Edge
Cisco Unified Edge is designed primarily for enterprises looking to run AI workloads and inferencing in a localized setting, removing the need for costly cloud-based infrastructure.
The platform can be scaled based on changing storage needs, which Cisco said will remove the need for “rip-and-replace upgrades”.
“The modular chassis offers CPU and GPU configurations, redundant power and cooling, high-performance SD-WAN networks, and pre-validated designs to support today’s applications and those yet to be imagined,” the company said in a statement.
Notably, Cisco aims to simplify integration of the platform, describing it as a “zero-touch deployment” system that can be easily managed through Cisco Intersight. This means considerations such as scaling and upgrades can be carried out without the need for “on-site specialist skills”.
ThousandEyes and Splunk integrations will also be available for Cisco Unified Edge, the company added, as well as built-in security features.
“Security is built-in at the device level and can extend to applying zero trust to every access, segmentation, and protection applications and AI models,” Cisco explained.
“This approach addresses the expanded attack surface at the edge, helping secure AI operations from physical and cyber threats.”
AI at the edge gains momentum
The announcement from Cisco marks the latest in a string of moves from big tech providers to bring AI closer to the edge, meaning data is processed closer to the source as opposed to relying on cloud infrastructure services.
There are a number of key advantages for businesses in this regard, according to Forrester, particularly with regard to latency and processing speed.
“Moving AI processing to edge devices enables rapid insights that traditional cloud-based setups can’t match,” Forrester VP and principal analyst Michele Goetz noted in a 2024 blog post.
“For sectors like healthcare and manufacturing, architects should prioritize proximity to offset latency. Low-latency, highly distributed architectures allow endpoints (e.g., internet-of-things sensors or local data centers) to make critical decisions autonomously.”
As ITPro noted in February 2025, hosting AI workloads at the edge also offers distinct advantages in terms of security.
In hosting data on localized devices, this essentially allows enterprises to keep a closer eye on storage and reduce exposure to unauthorized access.
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