NetApp updates data platform to address AI data challenges

NetApp has launched a new AI data engine designed to help companies manage and govern unstructured data across complex systems.

NetApp Malaysia has added new features to its enterprise data platform, with a focus on helping companies manage data for AI use. The update addresses a common issue in AI projects: handling and controlling large amounts of data across different locations and systems.

At the center of this update is the NetApp AI Data Engine (AIDE). The company developed it with NVIDIA and aligned it with NVIDIA's AI Data Platform design. The system brings together tools for storing, managing, and preparing data used in AI workloads.

NetApp said AIDE helps companies find, organize, and govern unstructured data. This type of data, which includes documents, images, and videos, often sits across many systems. By improving how this data is handled, companies may use more accurate and current information throughout the AI process. This includes steps such as data selection, processing, and deployment into applications or AI agents.

"Despite massive investments and market pressures to leverage AI for improved productivity and enhanced business decision making, data challenges are bottlenecking projects before they even reach production," said NetApp chief product officer Syam Nair in a statement.

"To take back control of their data, customers need a mature enterprise-grade data platform that was designed disaggregated and intelligent from the beginning so that storage, services, and control scale independently without lock-in."

One of AIDE's main features is a global metadata catalog that updates on a continuous basis. It allows users to search data beyond basic file labels by analyzing content and adding more context to it. This approach reduces the need to move data between systems, which can lower costs and limit security risks.

NetApp plans to release AIDE to a small group of early users and partners later this month. A wider rollout is expected in the coming months.

The company also plans to expand support for software tools used in AI development. These include platforms tied to Microsoft Azure AI, Google Cloud Vertex AI, and frameworks such as LangChain. The goal is to allow companies to use AIDE across both on-site systems and cloud environments.

Future updates will add more deployment options. These include support for NVIDIA RTX PRO 4500 and 6000 Blackwell GPUs, along with NetApp storage systems such as AFF A-Series, AFF C-Series, and FAS. NetApp also plans to expand support for hybrid cloud setups, visual data types, and AI systems that rely on autonomous agents.

The company is also working with Cisco to support enterprise AI systems. Cisco's FlexPod AI platform combines computing, storage, networking, and security tools into a single system.

Jeremy Foster, senior vice president and general manager of Cisco Compute, said FlexPod AI brings together the full stack needed to support AI systems. He explained that using NetApp AIDE allows companies to run AI closer to where their data is stored, which can help speed up data pipelines and shorten the time it takes to see results.

NetApp also plans to support NVIDIA STX, a modular storage design built for large-scale AI systems. The system uses NVIDIA Vera Rubin and BlueField-4 DPUs to improve power use, data flow, and security. It also aims to better link AI computing systems with stored data.

Jason Hardy, vice president of storage technologies at NVIDIA, said companies are looking for better ways to manage growing data volumes as AI use increases. He noted that integrating with NVIDIA's AI Data Platform gives companies a structure to manage data more efficiently for large-scale AI deployments.