Everpure Connects Data Intelligence to Policy-Driven Infrastructure Control

Key Highlights

• Data Intelligence File Edition expands visibility into unstructured data across enterprise file and cloud repositories, while the broader platform adds deeper classification and contextualization.
• Automated Data Intelligence workflows connect sensitivity classifications with Fusion policies, linking data discovery with continuous governance and infrastructure action.
• Pure1 Configuration Advisor consolidates array-by-array configuration sprawl into a smaller set of fleet policies that customers can review, modify, and execute.
• Everpure’s Unified Data Plane spans block, file, and object, while a common policy framework across those protocols remains on the roadmap.
• New sovereignty research shows spending and executive attention rising faster than organizations’ ability to implement consistent governance.

The News

At its Pure Accelerate London 2026 event, Everpure announced expansions to its Enterprise Data Cloud with Data Intelligence File Edition, native MCP access, a multi-cloud classification engine, Pure1 Configuration Advisor, automated Data Intelligence workflows, Portworx Observability, enterprise file enhancements, AI infrastructure updates, and additional virtualization support. The company also introduced its 2026 Global Data Sovereignty Report, based on 2,100 respondents in eight countries. The announcements extend Everpure’s Universal Data Intelligence, the Unified Data Plane, and the Intelligent Control Plane. For more information, read the official Everpure press release.

Analyst Take

Everpure’s February 2026 rebranding marked an inflection point in the company’s positioning and ambitions. Before the name change, Everpure had already expanded beyond array-level infrastructure through Evergreen, Pure1, Fusion, Portworx, enterprise file, cyber resilience, cloud services, and AI infrastructure. The company's new identity also helps clarify the largest strategic objective: manage enterprise data through a common layer of intelligence, governance, and control, then apply that architecture to a broader set of applications, AI workloads, and data services. ActiveCluster for File extended policy-driven availability and mobility deeper into enterprise file. Data Stream moved Everpure further into AI data pipelines. Universal Data Intelligence added data understanding to an architecture already spanning the Unified Data Plane and Intelligent Control Plane.

In our view, the new releases connect those pieces by giving Everpure a clearer view of what data is, where it resides, and how infrastructure should treat it. Data Intelligence File Edition gives customers a metadata-level view across CIFS/SMB, NFS, OneDrive/SharePoint, and Google Workspace, helping them identify stale, exposed, concentrated, or inefficient data without first inspecting file contents. The broader Data Intelligence platform can then inspect content, classify sensitive information, and establish relationships among data elements, moving from identifying what data exists to understanding what it relates to, which policies apply, and what action should follow.

Context as the Control Point

Automated Data Intelligence workflows continuously discover and classify sensitive data, associate those classifications with storage volumes, and let Fusion execute data policy. Everpure can use that context to keep regulated or sensitive data inside defined enclaves on an ongoing basis. Pure1 Configuration Advisor addresses the same problem from the infrastructure side. Enterprise storage estates accumulate years of configuration decisions, leaving protection settings, QoS, retention periods, and local baselines inconsistent from array to array.

Configuration Advisor analyzes the estate, groups existing configurations into a smaller set of recommended policies, shows the effect of proposed changes, and lets customers review or export those recommendations before execution. In Everpure’s demonstration for analysts, Configuration Advisor analyzed nearly 3,500 volumes across nine arrays, identified 132 distinct configurations, and mapped them into five proposed protection policies. Pure1 workflows then applied the approved changes across the fleet. Configuration Advisor generates nonbinding recommendations that customers can modify, including policy groupings, retention periods, and time windows. Pure1 then automates the approved changes across the fleet. That model brings more consistency to existing volume policies without removing customer control. The Unified Data Plane already spans block, file, and object, but Configuration Advisor does not yet apply one policy model across those data types. Broader protocol support will come in later versions, leaving policy unification as the next architectural step for Everpure and, more broadly, an industry challenge as vendors coordinate and standards continue to develop.

File, block, and object use different enforcement mechanisms, but customers still want consistent rules for sensitive data, residency, protection, and access. Context gives Everpure a way to separate policy intent from the mechanism used to enforce it. Customers could define rules centrally while the control plane translates those rules into actions appropriate to each data type. That would extend the common foundation from infrastructure consistency into governance consistency.

Everpure’s sovereignty research quantifies the gap between policy intent and execution. The company reports that 90% of respondents said sovereignty is core to their IT strategy, while 64% have not formally embedded a sovereignty strategy. Eighty-six percent increased spending during the past year, yet 56% still lack the skills, staff, or capacity to deliver. Sixty-two percent lack full visibility into who can access, control, and manage their data, even as 88% believe a sovereignty failure could put senior executives’ jobs at risk.

HyperFRAME Research Lens found a similar gap in enterprise AI and infrastructure management. In our State of the Enterprise AI Stack (1H 2026) research, 78% of respondents said AI is strategically important, but only 14% described their data architecture as AI-ready. In our State of Enterprise Infrastructure & Operations (1H 2026) study, 52% cited complexity as a major concern, while 90% saw value in unified management and only about one in six had achieved it. Everpure’s Data Intelligence and control-plane strategy addresses those constraints by tying data visibility and context to policy and infrastructure action.

Everpure has entered the S&P 500 and laid out a larger growth model spanning its core business, AI, Modern Data Software, and hyperscale. Its recent financial analyst meeting set ambitious FY27 and FY28 revenue expectations, and investors responded positively to the company’s AI and hyperscale positioning. Meeting those expectations will require Everpure to expand policy coverage beyond its current volume-oriented implementation and convert the broader Enterprise Data Cloud architecture into sustained customer adoption.

What Was Announced

Data Intelligence File Edition extends visibility across hybrid and multi-cloud file environments including CIFS/SMB, NFS, OneDrive/SharePoint, and Google Workspace. It uses metadata to identify stale data, exposure, concentration, and capacity-reclamation opportunities before deeper content inspection. Everpure is adding Pure1-based installation, native MCP access for querying findings through enterprise LLMs, and broader multi-cloud classification with enhanced Microsoft Purview integration and webhooks.

Everpure is expanding the Unified Data Plane with Evergreen//One SLA improvements, Purity DeepReduce, KVA performance enhancements for AI inference, Azure Red Hat OpenShift on Everpure Cloud, Portworx Flexible Storage for AI workloads, Red Hat AI Factory reference architectures, and additional enterprise file controls. The company continues to position the data plane as a common foundation for block, file, and object supporting workloads from archive and data protection through databases, analytics, HPC, and AI.

Pure1 Configuration Advisor enters beta with system-generated recommendations for reducing configuration sprawl across a fleet. Customers can assess policies by application, protection requirement, performance, array, or location, review the impact before approval, and export recommendations in JSON or Markdown. Automated Data Intelligence workflows also enter beta, connecting sensitivity classifications with storage volumes and Fusion policy execution. Portworx Observability adds cluster health, alerts, events, workload impact, root-cause analysis, and remediation guidance.

Everpure’s Global Data Sovereignty Report surveyed 2,100 respondents across the UK, France, Germany, Australia, Japan, Korea, Singapore, and India. Respondents included CEOs, CIOs, CTOs, CISOs, and AI and data-governance decision makers at organizations with at least 1,000 employees. The research documents persistent gaps between sovereignty priorities, visibility, staffing, and execution.

Looking Ahead

Data Intelligence can extend Everpure’s reach into security, governance, application, and AI teams, while Configuration Advisor and Fusion deepen the infrastructure relationship. Enterprise file remains a large opportunity, and AI infrastructure and hyperscale add new entry points. Broader protocol support in Configuration Advisor would extend fleet policy beyond its current volume-oriented implementation, while wider use of Data Intelligence classifications in automated workflows would show whether customers are willing to let data context influence infrastructure behavior continuously. The clearest proof will come when customers use intelligence, policy, and control together across more of the data estate.

Everpure’s software, AI, and hyperscale portfolio must also support the financial expectations now attached to the company. Growth depends on expanding existing customer relationships, reaching new buyers, and producing revenue beyond the core storage business. The new releases connect data context with infrastructure action more directly, so adoption and protocol coverage determine how much that architecture contributes to Everpure’s growth model.