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NetApp and Cisco have introduced new FlexPod AI solutions aimed at simplifying and securing enterprise AI deployments.
The additions extend the FlexPod converged infrastructure line that the companies have developed jointly for years. They target organisations building AI systems without having to assemble separate compute, networking and storage components.
The new offerings are designed for several stages of AI adoption, from large enterprise deployments to departmental inferencing and retrieval-augmented generation workflows, as well as edge environments running containerised and virtualised workloads.
Integrated platform
NetApp provides storage and data management elements, including NetApp AFX and the NetApp AI Data Engine, while Cisco supplies networking and security components linked to its Secure AI Factory with NVIDIA and Nexus One portfolio. The systems use pre-tested, validated designs intended to reduce integration work for IT teams.
That positioning reflects a broader market shift as businesses move from AI pilots to production systems and face the practical demands of data handling, governance, infrastructure management and cybersecurity.
Dallas Olson, Chief Commercial Officer at NetApp, said AI workloads were increasing pressure on data infrastructure across enterprise environments. He also pointed to operational savings customers had already seen from existing FlexPod deployments.
"As IT teams are tasked with delivering reliable, consistent performance across environments, AI workloads are placing increasing demands on their data infrastructure," said Dallas Olson, Chief Commercial Officer at NetApp.
"NetApp and Cisco's longstanding partnership on FlexPod has already proven effective, saving customers up to 20 percent of their time in infrastructure management and maintenance. Now, we are applying our combined expertise to modern challenges to accelerate AI adoption while reducing risk with built-in security," added Olson.
Broader deployment
The companies are pitching the new systems to customers that want to run AI closer to where their data already resides, rather than moving large datasets into separate environments. In practice, that means combining storage that can scale independently from compute with networking and security controls across the AI pipeline.
For enterprise deployments, the architecture is positioned for uses such as retrieval-augmented generation and semantic search. NetApp said future functionality in its AI Data Engine will cover data discovery, preparation and governance, and will integrate with the NVIDIA AI Data Platform reference design.
Cisco said the security layer is intended to address AI-specific risks, including data exposure, governance gaps and compliance issues. The networking side is built around what Cisco describes as a deterministic fabric designed to improve utilisation of accelerated computing resources and reduce the time needed to complete AI jobs.
Jeremy Foster, General Manager and Senior Vice President at Cisco, said customers now expected security to be built into AI infrastructure from the start, rather than added later.
"As organisations move from AI experimentation to real‐world deployment, security can't be an afterthought. It has to be built in from the start," said Jeremy Foster, General Manager and Senior Vice President at Cisco.
"By collaborating with NetApp to extend Cisco Secure AI Factory with NVIDIA to our validated FlexPod solution, we're helping customers address AI‐specific risks such as data exposure, governance gaps, and compliance challenges while simplifying how AI infrastructure is deployed and operated," added Foster.
NVIDIA involvement
NVIDIA is also involved through its enterprise reference architectures and AI data platform design. The collaboration gives NetApp and Cisco a way to align their products with infrastructure patterns already familiar to customers building AI factories around NVIDIA technology.
Jason Hardy, Vice President, Storage Technologies at NVIDIA, said the key issue for many companies was not simply access to data, but whether their infrastructure included the tools to discover, govern and prepare it for production AI use.
"Enterprises are sitting on vast amounts of data, but without the discovery, governance and preparation built into the infrastructure itself, enterprises will struggle to power production AI," said Jason Hardy, Vice President, Storage Technologies at NVIDIA.
"NetApp AI Data Engine, co-engineered on the NVIDIA AI Data Platform and validated with the Cisco Secure AI Factory with NVIDIA, gives organisations the secure, AI-ready data foundation to deploy AI factories on FlexPod infrastructure at scale," added Hardy.
Channel support
The announcement also drew support from World Wide Technology, which said it would use its testing environment to validate the architectures in practical customer scenarios. That suggests NetApp and Cisco are seeking backing from implementation partners as they try to move buyers from proof-of-concept work into broader deployment.
Brian Bartell, Practise Manager, Compute & Storage at World Wide Technology, said the addition of AI features to FlexPod could shorten the path from early concept work to deployment.
"The new AI capabilities in FlexPod expand our ability to help customers navigate the AI era with confidence," said Brian Bartell, Practise Manager, Compute & Storage at World Wide Technology.
"Through our long-standing partnerships with NetApp and Cisco, the introduction of NetApp's AI Data Engine, and the ability to validate these architectures hands-on in WWT's AI Proving Ground, we can compress the time from concept to execution, giving our customers a pre-tested, industry-leading foundation to move at the speed of the market and unlock the power of their data," added Bartell.