How NetApp And NVIDIA Help Partners Make Their Production Data AI Ready

For partners, one of the biggest AI revenue opportunities right now, beyond infrastructure, is solving the data problem. Many AI projects slow down simply because the data is not ready.

In this CRNtv interview, host Sydney Neely speaks with Craig Weinstein of NVIDIA and Kristine Wedum of NetApp about how partners can make production data AI-ready, reduce time to market and scale AI solutions.

Sydney: From your perspective, how would you describe the AI opportunity you see for enterprises right now?

Craig: AI is top of mind for every enterprise, but only around 40% of AI prototypes make it into production today. Data availability and data quality are cited as probably the most important barriers. Most of the untapped data that we are seeing still sits with enterprises and is not being used. It is totally unstructured. Things like email, PDFs, chat, audio and video logs—much of it is dark and not very useful.

That is where the NVIDIA AI data platform comes in. It is continuously transforming unstructured, multimodal data into AI-ready data as a background operation that embeds GPU acceleration. It is actually doing it right into the data path. Data is prepared in place to minimize copies and making sure we are preserving security and keeping AI systems ready.

I will close with this: companies like NetApp are working really hard with NVIDIA. They are trying to build their own data platform to make sure the designs customers want are AI-ready and that the architectures and infrastructure are ready for enterprises to trust.

Sydney: How does the NetApp AI Data Engine, built on NVIDIA’s AI Data Platform, enable partners to create new business opportunities?

Kristine: NetApp’s AI Data Engine, or AIDE as we often refer to it, in its most simple form answers the question Craig was speaking to. How do we get enterprise data actually usable for AI? One of the biggest challenges for customers in having successful AI projects is that data readiness piece.

When you combine that with the fact that 40% of unstructured enterprise data is actually sitting on a NetApp solution, it gives us an incredible opportunity for our partner ecosystem to have an elevated conversation with their customers. It gets outside of just a capacity conversation and more into a strategic solution that is going to allow that customer’s data, no matter where it sits in the data estate, to be both agent- and pipeline-ready, maximizing its value.

Sydney: For partners who are already selling AI Factory, how does leading with both AI Factory and AI Data Platform create long-term opportunities?

Craig: AI factories are creating a huge new market opportunity for solution providers. We are seeing enterprises looking for help to architect, integrate and operate these full-stack accelerated computing environments that are built on NVIDIA technology.

NVIDIA’s AI Factory is a full-stack solution for the entire AI lifecycle that manufactures intelligence at scale. The AI Data Platform integrates accelerated computing into enterprise storage to make sure the enterprise data is already AI-ready.

When partners lead with both, they are connecting an AI factory to a continuous stream of AI-ready data, which positions them to make sure they are selling systems and solutions that drive outcomes. These solution providers are well positioned to build high-value recurring services plus advisory. They are also combining lab, integration and managed services that help customers run AI environments, most importantly, reliably and efficiently as they expand to new use cases and applications.

Sydney: Now that NetApp’s AI Data Platform and AI Data Engine are here, what do the first 30 days look like for partners who want to start building momentum around this?

Kristine: In the first 30 days, we really want to encourage our partners to keep it simple. The first call to action is to start with discovery. Reach out to your top customers, help them see if they have any of that dark data that was mentioned already in-house and show them that with the AI Data Platform they can get real-time insights from that unstructured data without having to move it or expose it.

The next step is getting hands-on. We really want to encourage customers to stay away from creating anything from scratch. Leverage local demo centers and reference architectures that are already out there, because that is going to be the fastest path to value.

Last, but certainly not least, get connected. Our ecosystem is at its strongest when we are working together and have a unified solution and message.

With NVIDIA and NetApp, partners have a scalable way to turn production data into AI-ready data. For more information on how partners can get started, visit netapp.com/nvidia.