Pure Storage Elevates AI and Cyber Resilience with New Platform

The News

Pure Storage announced major advancements across its Pure Storage Platform, introducing native cyber resilience features, expanded AI integrations, and a new sustainability-focused Impact Report. Highlights include the launch of Pure Storage Cloud for unified data mobility, CrowdStrike and Veeam integrations for threat detection and recovery, and NVIDIA Dynamo and Azure VMware partnerships to scale AI performance.

Analysis

Pure Storage’s latest innovations reflect a central truth of modern enterprise IT, being that AI readiness begins with data control and security resilience. As organizations race to operationalize generative and agentic AI, theCUBE Research and ECI Research data shows 74.3% of enterprises now list AI/ML as a top investment priority, while 68.3% rank security and compliance among their top spending areas.

Pure’s updated platform could merge these imperatives by bringing cyber resilience and AI optimization under one roof. With native threat detection at the storage layer, real-time SIEM integration through CrowdStrike Falcon, and Cyber Resilience-as-a-Service via Veeam, Pure is positioning data infrastructure not just as storage but as the first line of defense against modern AI-driven threats.

From Storage to Enterprise Data Cloud

The expansion of the Pure Storage Enterprise Data Cloud marks a notable evolution beyond storage infrastructure. By introducing Pure Storage Cloud, the company enables data unification across on-premises, edge, and multicloud environments, a crucial foundation for AI workflows that demand continuous access to live data.

Developers and data engineers can now move workloads fluidly across environments without refactoring, thanks to Azure Native Integration for VMware, and manage them through Portworx + Pure Fusion. This integrated ecosystem may give enterprises a single control plane for data mobility, performance optimization, and AI pipeline orchestration. The addition of Pure1 AI Copilot and integration with NVIDIA Dynamo further advance this goal, combining intelligent workload guidance with accelerated inference at reduced energy cost.

Managing Data Sprawl

Until now, developers often had to navigate fragmented architectures, mixing cloud-native pipelines, on-premises storage arrays, and separate security tools. This fragmented data management slowed AI experimentation-to-production cycles and exposed gaps in visibility and compliance. theCUBE Research and ECI Research ‘s Day 0 and Day 1 findings show that 50.7% of developers still rely on manual configuration, and 41.1% cite security visibility as a top challenge.

By consolidating storage, security, and AI orchestration under a single platform, Pure Storage aims to simplify these workflows, reducing friction across teams and accelerating data access for model training, inference, and compliance auditing.

AI with a Smaller Carbon Footprint

Pure’s 2025 Impact Report highlights a growing concern across the industry: how to scale AI while keeping energy consumption and carbon emissions in check. This focus on “sustainable AI infrastructure” aligns with trends across data centers, where vendors like Equinix and Infinidat are also emphasizing efficiency metrics.

Pure’s approach combines high-performance flash with power efficiency and density improvements, enabling enterprises to train and deploy AI workloads responsibly. When paired with its unified data control, these sustainability advances strengthen Pure’s narrative of “AI without waste” where performance and environmental stewardship coexist.

Looking Ahead

Pure Storage’s shift from “storage vendor” to data control and AI enablement platform aligns to a broader industry transition. The future of AI infrastructure lies in converged architectures where data mobility, security, and sustainability are managed as code.

This could mean fewer silos and faster iteration. AI pipelines can now be built atop storage layers that are self-protecting, AI-optimized, and cloud-portable. The integration of Pure Fusion, Portworx, and Pure1 AI Copilot creates a strong foundation for agentic AI applications that need trusted, always-available data sources.

If Pure successfully operationalizes this vision, it could change what “enterprise data cloud” means, shifting the narrative from storage capacity to AI capability, resilience, and responsible innovation.

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Samantha Weston

With over 15 years of hands-on experience in operations roles across legal, financial, and technology sectors, Sam Weston brings deep expertise in the systems that power modern enterprises such as ERP, CRM, HCM, CX, and beyond. Her career has spanned the full spectrum of enterprise applications, from optimizing business processes and managing platforms to leading digital transformation initiatives.

Sam has transitioned her expertise into the analyst arena, focusing on enterprise applications and the evolving role they play in business productivity and transformation. She provides independent insights that bridge technology capabilities with business outcomes, helping organizations and vendors alike navigate a changing enterprise software landscape.

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Paul Nashawaty

Paul Nashawaty, Practice Leader and Lead Principal Analyst, specializes in application modernization across build, release and operations. With a wealth of expertise in digital transformation initiatives spanning front-end and back-end systems, he also possesses comprehensive knowledge of the underlying infrastructure ecosystem crucial for supporting modernization endeavors. With over 25 years of experience, Paul has a proven track record in implementing effective go-to-market strategies, including the identification of new market channels, the growth and cultivation of partner ecosystems, and the successful execution of strategic plans resulting in positive business outcomes for his clients.
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