In February 2026, a transition and rebrand took place that reflects the growth in how enterprises think and manage their data.
Everpure, formerly Pure Storage, made this shift – progressing from a traditional storage management company to an autonomous infrastructure and holistic data management enterprise.
To discuss this transition and the opportunities Everpure’s growth presents, Channel Insider spoke with Chadd Kenney, VP of Product Management at Everpure, at Pure Accelerate 2026, the company’s flagship conference, in Las Vegas.
Everpure’s evolution into data intelligence
Kenney explained that effective data management requires both intelligent infrastructure as a foundation and an understanding of the data’s context and semantics.
Everpure is pursuing both goals simultaneously to improve infrastructure automation while advancing data intelligence capabilities.
“We’ve been going through an evolution from storage management –where we started off building simple storage – to autonomous infrastructure, where we build governance, policies, and intelligence around the infrastructure stack,” said Kenney.
“Now, we’re moving into data management at the highest levels. In order to effectively manage data, you’ve got to be able to create autonomy within the infrastructure stack while also understanding the context and semantics of the data on top of it.”
Why Everpure is focusing on operationalizing data
The organization has built on the Enterprise Data Cloud from the previous year, shifting the focus from creating a unified data plane and intelligent control plane to helping customers operationalize those capabilities.
The new capabilities the organization has deployed are aimed at simplifying management, improving compliance, balancing infrastructure resources, and enabling deeper data understanding.
Customers are increasingly wanting control and understanding of their data rather than managing isolated applications, Kenney explained. The goal now is to eliminate silos and enable data to be used more effectively for AI, analytics, development, and business operations.
“The transition is really focused around moving from the application-centricity that exists today into more of a data-centric model,” said Kenney.
“Customers want more control around their data and want to be able to understand it more realistically so they can use it not just for AI, but also for application development and analytics. It’s about breaking down the silos that exist today.”
Customers continue to struggle with complex IT and storage environments
According to Kenney, many of Everpure’s recent innovations stemmed from customer frustrations with fragmented storage environments and operational complexity.
The first step was unifying disparate systems, followed by creating mechanisms that translate business intent into infrastructure actions through compliance and automation.
“Customers have been challenged because data has traditionally been very siloed across different storage stacks,” said Kenney. “Most people didn’t know what they had. The first step was helping unify that into one virtualized environment and getting rid of those silos. A lot of that came from customer complaints about the complexity of managing different systems.”
Expanding opportunities for channel partners
Kenney mentioned that partners will play a critical role in helping customers transition from siloed environments to virtualized data environments.
As data management becomes more strategic, resellers, MSPs, and other partners gain opportunities for higher-level business discussions on governance, compliance, and policy rather than focusing solely on infrastructure.
“Partners are helping customers evolve through this transition. We’re building the tools, but they’re out there helping customers move from very siloed environments into this virtualized model and helping them rationalize their data,” said Kenney.
“It opens up new opportunities for them to talk about the data side of the house, not just the infrastructure side.”
Data efficiency, discovery, and security risks
Organizations often maintain multiple copies of the same data, consuming unnecessary capacity and resources.
Better discovery and classification can identify redundant copies, reduce storage requirements, and improve operational efficiency.
“As you understand the data, you start to find that there are many copies of the same data sitting out there,” explains Kenney. “By understanding, classifying, and discovering it, you can find those copies that may not be useful. There’s an obvious opportunity to reduce data copies and reduce the amount of storage infrastructure required.”
Redundant and forgotten copies of data create security and compliance risks for enterprises. These unmatched data copies often lack the protections of production environments and may expose organizations to data leakage or misuse.
Kenney explains that organizations need stronger governance over data lifecycles. Policies governing retention, deletion, and access can reduce risk, prevent the use of outdated information, and limit unnecessary data proliferation.
“If you think about a policy that says after 30 days a data copy used for testing should be deleted, most organizations don’t have those kinds of controls in place,” Kenney said. “Somebody may have left and their data is still sitting there, open for someone to potentially attack. Having policies and controls around the data is a key component of making sure you don’t proliferate copies everywhere.”
Why more companies need to focus on data governance and compliance
Moving forward, Kenney expects organizations to focus first on understanding their data and ensuring compliance over the next few years.
Over time, those insights will be connected back to infrastructure policies, creating tighter alignment between the nature of the data and how it’s managed.
Ultimately, this foundation will support AI-driven workflows and shared enterprise-wide context, Kenney says.
“I think for the most part enterprises don’t really understand the data they have,” said Kenney. “The first step is understanding where sensitive information exists and making sure it’s managed in a compliant way. As time goes on, you’ll start applying that understanding back into the infrastructure so that the policies align with what the data actually is.”
Everpure’s new branding evokes a new mission: helping organizations eliminate silos, understand their data where it resides, apply governance and compliance policies more effectively, and create a shared data context to support future AI-driven operations.