AI is no longer a side initiative — it’s becoming the foundation of enterprise transformation. To meet the demand for scalable, secure and operationally effective deployments, Nutanix Inc. and Nvidia Corp. have partnered to define a new AI blueprint for the modern enterprise.
Nutanix’s Tarkan Maner and Nvidia’s Kevin Deierling discuss AI blueprints with theCUBE.
Their goal: help organizations move beyond experimentation to fully integrated, agentic AI operations that drive competitive advantage across industries.
“Blueprints are how we build agentic flows,” said Kevin Deierling (pictured, right), senior vice president of networking and storage at Nvidia. “Now you have AI as it used to be — you would ask a question and get an answer … one-shot foundational models for inferencing. Today, inferencing is much more interesting and effective, so it’s agentic AI. We have AIs talking to AIs; we have reasoning models. Putting those together, we call that a blueprint.”
Deierling and Tarkan Maner (left), chief commercial officer of Nutanix, spoke with theCUBE’s John Furrier and Bob Laliberte at Nutanix .NEXT, during an exclusive broadcast on theCUBE, News Media’s livestreaming studio. They explored how Nutanix and Nvidia are reshaping enterprise AI by delivering tightly integrated solutions, blueprint-driven deployments and a strategic focus on scalability, efficiency and business value. (* Disclosure below.)
The AI blueprint in detail
The AI blueprint is a pre-architected solution designed to simplify and accelerate the deployment of AI across diverse industries. Rather than starting from scratch, businesses can use these blueprints to implement intelligent workflows quickly, tailored to specific use cases such as fraud detection, legal document management or customer service, according to Maner.
“We work with law firms, and they are crazy about document management, but intelligent document management,” he said. “Today, all these people are working on this search, managing documents. Guess what? Now with specific blueprints for law firms, with our compute storage data management, the Kubernetes layer will deliver the right blueprint with Nvidia to deliver applications to support those law firms to do this.”
Blueprints include integrated orchestration, storage and compute capabilities — with security and manageability baked in. Beyond single-turn question-answering, the current age of agentic AI means that multiple agents interact, reason and build on each other’s output. This complexity demands tightly integrated platforms, which the Nutanix-Nvidia partnership delivers, according to Deierling.
“This is where it’s great with a partner like Nutanix,” he said. “They’ve got their entire storage and unified storage platform. All of the securities and access controls that are built into that can flow into the AI workflows and the blueprint, so that when you look up something, you’re seeing only the data that you’re allowed to see and querying against that data.”
The AI factory is reshaping how companies approach AI deployment. Enterprises are beginning to treat AI deployments like industrial production lines, moving from simple model training to large-scale inferencing and agentic operations. For this to work, platforms must scale effortlessly and efficiently, according to Maner.
“We’re talking about thousands of nodes, hundreds of thousands of cores transforming and getting ready for these AI-specific workloads,” he said. “For one of our financial services customers, we’re now doing a fraud detection application, all agentic. The entire application is going to run on thousands of cores, and the entire deployment is through an agent-based model running on our security manageability automation capabilities. And the key thing is scale.”
Here’s the complete video interview, part of News’s and theCUBE’s coverage of Nutanix .NEXT:
(* Disclosure: TheCUBE is a paid media partner for Nutanix .NEXT. Neither Nutanix Inc., the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or News.)
Photo: News
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