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NetApp and NVIDIA Collaborate to Redefine Enterprise AI

NetApp and NVIDIA Collaborate to Redefine Enterprise AINetApp has unveiled an advanced generative AI data vision and end-to-end integrated solutions that combine NVIDIA AI software and accelerated computing with NetApp intelligent data infrastructure for enterprise retrieval augmented generation (RAG) to power the future of agentic AI applications.

This will bring new capabilities to the NetApp ONTAP unified storage operating system that can leverage a new NetApp global metadata namespace to unify data stores for the tens of thousands of enterprises that trust NetApp for their data infrastructure. It opens up exabytes of enterprise data stored across clouds and on-premises infrastructure to drive RAG capabilities that can put enterprises’ entire data estate to work, accelerating next-generation agentic AI applications.

The solution brings together proven NetApp AIPod architecture with NetApp ONTAP and the NetApp BlueXP unified control plane, with NVIDIA NeMo Retriever and NIM microservices, which are part of the NVIDIA AI Enterprise software platform.

“To power AI applications and drive transformative progress for their business, enterprises must unlock the potential of their data,” said Harv Bhela, Chief Product Officer at NetApp. “Combining the NetApp data management engine and NVIDIA AI software empowers AI applications to securely access and leverage vast amounts of data, paving the way for intelligent, agentic AI that tackles complex business challenges and fuels innovation.”

With the new NetApp AI capabilities built into NetApp AIPod – certified for NVIDIA DGX BasePOD infrastructure and NVIDIA OVX solutions— and managed through BlueXP, NetApp customers will be able to easily discover, search, and curate data on-prem and in the public cloud based on a set of criteria, honouring existing policy-based governance criteria.

Once the data collection has been established through NetApp BlueXP, it can be dynamically connected to NVIDIA NeMo Retriever, where the dataset will be processed and vectorised to be accessible for enterprise GenAI deployments with appropriate access controls and privacy guardrails. This creates the foundation for a generative AI flywheel to power next-generation agentic AI applications that can autonomously and securely tap into data to complete a broad range of tasks to support customer service, business operations, financial services and more.

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Rashmi

I’m a passionate writer who loves storytelling and enjoys exploring different topics. Whether it's writing articles or engaging stories, I aim to inform and inspire readers. With each piece I create, my goal is to connect with people, engage them, and offer new perspectives that encourage meaningful discussions.

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