Solidigm targets the intelligence layer as agentic inference pushes storage to center stage
The shift from model training to agentic inference is forcing a fundamental rethink of how artificial intelligence infrastructure is built and which components carry the most strategic weight. What was once treated as commodity plumbing is now being recognized as the intelligence layer where raw data becomes actionable intelligence.
The rise of sovereign AI deployments and enterprise AI clusters is compounding that pressure, as organizations from hyperscalers to regional governments race to build out high-performance compute stacks that can sustain continuous inference at scale. Storage has quietly moved from afterthought to forethought in those conversations, according to Greg Matson (pictured), senior vice president and head of marketing and products at Solidigm, a trademark of SK Hynix NAND Product Solutions Corp.
“It started a couple of years ago with training, where the need for high-capacity, high-performance storage very adjacent to the GPUs was all of a sudden center stage,” Matson said. “But now at the inference, as we go from last year into this year inference phase into agentic inference, it’s exploding even more. … Storage is actually a whole new storage tier that’s being created to extend the memory for the system. … I almost call it the intelligence layer is now being housed on storage.”
