NetApp has announced the acquisition of DataPelago, a California-based innovator in AI data infrastructure. DataPelago is widely recognized for engineering novel solutions that eliminate systemic data processing bottlenecks commonly disrupting artificial intelligence and advanced analytics workloads.
The acquisition represents a structural expansion of the NetApp technology portfolio. By natively coupling GPU-accelerated data processing with the core storage layer, the integration establishes NetApp as a primary enabler of zero-copy data activation for enterprise AI ecosystems.
Overcoming the Data Preparation Deadlock in Enterprise AI
While artificial intelligence represents a major technological paradigm shift, modern enterprises frequently discover that the primary obstacle to production-grade deployment lies in data management. Organizations face severe friction when trying to prepare, govern, and activate distributed datasets fast enough to power live AI pipelines. Resolving this bottleneck requires moving accelerated computing resources directly to the specific environments where information is generated and housed. DataPelago directly addresses this architectural challenge by shifting accelerated compute functions into the data layer itself, rather than treating processing as a separate layer above it.
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“As AI models and the chips that power them get ever more effective, enterprises need data infrastructure that is just as intelligent and powerful to harness the potential of their data,” said George Kurian, Chief Executive Officer at NetApp. “NetApp is leading the industry in helping customers drive innovation and generate business value by giving them full command of their most important asset: their data. With DataPelago, we are extending our ability to help customers understand and process their data with the agility required to unleash competitive advantage.”
Eliminating the ‘Copy Tax’ via the Nucleus Processing Engine
At the core of DataPelago’s product portfolio is Nucleus, a universal data processing engine built to leverage heterogeneous accelerated computing across mixed CPU and GPU environments. By executing complex transformations directly at the storage tier instead of migrating massive datasets across the network to external compute clusters, Nucleus minimizes infrastructure operational costs by up to 80% while yielding processing speeds up to 10 times faster than legacy methodologies.
Crucially, by removing the requirement to continuously replicate and transfer information from active operational frameworks over to specialized AI environments, the platform eliminates a primary operational bottleneck holding back enterprise AI scaling. DataPelago’s proprietary technology is currently live across multiple enterprise-scale verticals, optimizing resource efficiency while accelerating data-intensive production workloads.
“DataPelago is on a mission to eliminate the data processing bottlenecks that prevent AI innovation from reaching its full potential,” said Rajan Goyal, Founder and Chief Executive Officer of DataPelago. “Joining NetApp gives us the opportunity to combine our breakthrough processing technology with the industry’s best data infrastructure portfolio. Enterprises have invested billions in GPUs and AI models, but their data remains fragmented, leaving valuable computing resources to sit idle rather than putting these investments to work. Together, we’re positioned to help customers simplify and accelerate AI deployment at scale.”
“DataPelago’s Nucleus engine brings software-defined acceleration directly to the storage layer, processing data across CPUs and GPUs so enterprises can prepare, govern, and activate their data for AI without moving it. This is true zero-copy activation,” said Syam Nair, Chief Product Officer at NetApp. “NetApp manages more enterprise data across more environments than anyone in the industry. The next phase of AI will be won by those who make that data work at the source, and the DataPelago team brings the technical depth and velocity to get us there faster.”