Everpure unveils data primacy framework to fix AI's broken foundation with governance-first approach
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Enterprise Data Cloud blueprint powers AI data strategy
Everpure launches Enterprise Data Cloud blueprint to guide AI data strategy Fragmented data, siloed infrastructure and reactive portfolios are problems that every enterprise has to deal with, and fixing them efficiently requires a completely new operating model -- one that the Enterprise Data
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Everpure CEO - 'AI makes data primacy necessary, but the organizational challenge needs a senior leader driving it'
Today Everpure outlined its data primacy thesis - introducing products that include Data Intelligence, Data Stream, and the evolving Intelligent Control Plane - and the architectural argument that 50 years of application-centric enterprise IT must now invert. This morning's CEO Q&A provided us with
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Everpure & WWT on building data-ready AI infrastructure
Everpure and WWT say data-ready AI infrastructure starts with clean, governed data Getting to production-ready AI requires much more than fast storage because enterprises need data-ready AI infrastructure that's built on clean, governed and well-understood data before any meaningful deployment can
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"Data primacy" - Everpure's pitch to invert the app-centric enterprise
In Las Vegas this week, ahead of the main-stage keynotes, Everpure took press and analysts through announcements that aim to turn its February's rebrand into a longer-term product strategy. When Pure Storage became Everpure, I wrote that dropping "storage" was a coherent extension of the company's
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Data centric model pivot drives Everpure's brand evolution
Everpure shifts from hardware to data-centric model as governance emerges as the key to AI returns Enterprises racing to deploy artificial intelligence are discovering that the bottleneck is not compute or models, but rather the failure to adopt a data centric model to resolve unmanaged,
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AI-ready data foundations fuel enterprise AI
Data context and governance are the missing ingredients keeping enterprise AI from scaling The next phase of enterprise AI is shifting focus from models to the data that fuels them, with organizations increasingly investing in AI-ready data foundations. As regulatory requirements grow and data
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Everpure Unveils Data-Primacy Architecture for the AI Era
New Everpure Data Intelligence enables discovery, context, and governance at the source -- turning fragmented enterprise data into an automated, AI-ready foundation. Everpure today announced new capabilities to help businesses securely fast-track enterprise AI initiatives while maintaining
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Autonomous infrastructure unlocks live data for AI agents
Autonomous infrastructure breaks data silos to accelerate enterprise AI Data intelligence is becoming the next battleground for enterprise AI and autonomous infrastructure as companies discover that copying information into dashboards and data lakes is too slow for agentic workloads. The shift is
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Everpure Announces Data Stream to Expand AI-Ready Data Offerings
New capability provides definitive implementation path for production AI, allowing customers to make their data AI-ready for natural language, search, and analysis of unstructured data. Everpure today announced the availability of Everpure Data Stream, which brings advanced AI capabilities
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Data primacy could build reliable AI infrastructure
Data primacy puts Everpure at the center of enterprise AI: theCUBE's Pure Accelerate 2026 keynote analysis As artificial intelligence transforms the enterprise, the old model of managing data in application-controlled silos is breaking down. The companies that will win the AI era are those that
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Everpure Unveils Data-Primacy Architecture for the AI Era
Everpure announced new capabilities to help businesses securely fast-track enterprise AI initiatives while maintaining visibility and control over all their data. Anchored by the introduction of Everpure Data Intelligence (formerly 1touch.io) and new updates to the Enterprise Data Cloud, these
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Everpure accelerates AI workloads with Data Stream and unveils data-primacy architectural vision
Everpure accelerates AI workloads with Data Stream and unveils data-primacy architectural vision Big-data storage company Everpure Inc., formerly known as Pure Storage, is rethinking enterprise data architectures to facilitate better access and scalability for artificial intelligence
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Everpure launched its Enterprise Data Cloud blueprint and data primacy framework at Pure Accelerate 2026, arguing that 50 years of app-centric enterprise IT must invert to make AI work. CEO Charlie Giancarlo revealed he personally chairs weekly coordination meetings for 18 months to implement the shift internally, highlighting that data primacy is more a political challenge than a technology problem.
Everpure pivots to data primacy as AI exposes enterprise architecture flaws
Everpure introduced its data primacy framework at Pure Accelerate 2026, making the case that artificial intelligence has reached a breaking point with traditional enterprise architecture
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. The company's AI data strategy centers on a fundamental inversion: treating data as the primary asset and pushing applications downstream, reversing 50 years of app-centric enterprise design4
. CEO Charlie Giancarlo argues that while data silos have existed for decades, agentic AI makes incoherent data actively dangerous rather than merely inconvenient, as AI agents act on whatever data they receive without human judgment to reconcile inconsistencies2
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Source: diginomica
The shift addresses a critical failure mode in enterprise AI. According to IDC research presented at the event, 54% of AI projects never reach production, representing zero AI return on investment for companies that have committed significant capital
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. Phil Goodwin, research vice president at IDC, identified data governance as the number one reason AI projects fail, followed by data access issues caused by fragmentation across data silos5
.Enterprise Data Cloud blueprint maps path from fragmentation to autonomous operations
Everpure's Success Blueprint provides a structured maturity model spanning ten capability areas across three dimensions: agility, cyber resilience, and scalability
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. Stephanie Richardson, vice president of product marketing at Everpure, explained that the framework helps organizations assess current vulnerabilities and chart a prescriptive path toward unified, governed data environments1
. The blueprint delivers through three mechanisms: maturity assessments, self-service guides for each progression level, and facilitated workshops where Everpure experts coordinate shared AI data strategy with customer teams before purchase decisions1
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Source: SiliconANGLE
Richardson illustrated concrete progression using operational efficiency, where teams move from manual provisioning tasks to automated workflows, then to policy-driven workload rebalancing, ultimately reaching autonomous operation against preset SLAs
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. Everpure attached specific business outcome metrics to each capability area, tracking efficiency gains, power reduction, and reduced audit times to build evidence for returns at every maturity step1
.Data Intelligence and Data Stream address the data-ready AI infrastructure gap
Everpure Data Intelligence, built on the 1touch.io acquisition announced during February's rebrand, is now generally available
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. The platform discovers structured and unstructured data across entire estates, including inside databases like SQL Server and Oracle, scans for sensitive information such as PII and PHI, tracks lineage, and maps raw data to business meaning through a semantics knowledge graph4
. Critically, it works across any infrastructure, not just Everpure arrays5
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Source: SiliconANGLE
Ashish Gupta, former CEO of 1touch.io and now General Manager for Data Management, cited a large credit card company that reduced DSAR request response time from 21 person-hours to 30 seconds
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. With over 7,000 requests daily, the cost reduction proved substantial4
. Everpure Data Stream, also available now, prepares classified data for AI by calculating vector embeddings that feed retrieval and generation, cutting data preparation from months to minutes4
. Built on NVIDIA's AI Data Platform reference design, it runs on FlashBlade and scales to FlashBlade//EXA for GPU-cloud workloads4
.Related Stories
Partners shift from speeds and feeds to consultative data curation services
The conversation around data-ready AI infrastructure has moved decisively away from performance benchmarks toward data preparation, according to Hope Galley, vice president of Americas partner sales at Everpure, and Justin Field, technical solutions architect at World Wide Technology, Everpure's global partner of the year
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. Field noted that customer discussions now center on data curation, ensuring underlying data is clean and contextualized before any AI investment3
. WWT operates AI proving grounds and advanced technology centers where customers validate infrastructure decisions at scale before committing, removing risk from large investments3
.Galley emphasized that partners who adopt consultative approaches and cross-functional selling into the C-suite are winning in the current market
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. Everpure's Evergreen//One consumption model adds flexibility, letting customers scale storage commitments aligned with AI project timelines rather than being constrained by supply chain uncertainties3
. Evergreen//One Overdrive, arriving in Q3, will absorb traffic spikes up to 25% above baseline without permanent upgrades4
.Data primacy requires senior leadership commitment and cross-functional alignment
Charlie Giancarlo acknowledged that data primacy presents more of a political problem than a technology problem, requiring organization-wide investment rather than isolated departmental efforts
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. Application proliferation reflects workflows comfortable for individual organizations, and consolidating core workflow elements requires cross-functional agreement2
. Giancarlo revealed that Everpure itself is undergoing this transformation through an internal program called Mercury, which he has personally driven by attending coordination meetings every single week for 18 months2
. He expects the full journey to take approximately two and a half years total2
.Lynn Lucas, chief marketing officer at Everpure, explained that the rebrand from Pure Storage reflects the strategic expansion into data management and data intelligence, targeting chief data officers and chief AI officers who might perceive "storage" as limiting
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. The data-centric model distinguishes itself from traditional ETL approaches through metadata that maps how different repositories relate without requiring data movement2
. This addresses the fundamental objection that defeated previous data integration efforts: avoiding yet another copy2
. Chief Technology Officer Rob Lee pointed to open table formats like Iceberg and Parquet as early phases of this shift on the analytics side, arguing the transactional side must now follow4
.References
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