Artificial intelligence (AI) is getting all of the headlines, but IT infrastructure is where the real pressure is building. Across industries, organizations are discovering that traditional storage architectures — built around silos, manual provisioning and rigid scaling — simply can’t keep up with modern data demands. In response, Everpure is advancing a new model: the Enterprise Data Cloud. 

At a high level, the idea is straightforward. Instead of managing fragmented storage systems across on-premises and cloud environments, IT teams operate a unified data platform that abstracts complexity and delivers cloudlike agility everywhere. 

But according to Shawn Rosemarin, Everpure’s vice president of research and development for customer engineering, the shift is long overdue. “Storage is the last piece of the data center that really never grew up,” he says. “If you look at compute, networking, applications — they’ve all evolved dramatically. Storage has largely stayed the same.”

Why AI Is Breaking Traditional Storage Methods 

The rise of AI has exposed just how outdated many storage environments have become. Unlike traditional enterprise applications, AI workloads demand extreme performance, massive scale and seamless access to distributed data. That combination is pushing legacy architectures beyond their limits. 

“The biggest issue is getting data to GPUs fast enough,” Rosemarin explains. “Traditional storage was never designed to deliver tens of...