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Pure Storage Expands Enterprise Data Cloud to Power AI-Driven Workloads

Pure Storage Enterprise Data Cloud AI

New platform innovations bring unified data control across cloud and on-premises, helping enterprises scale AI securely and sustainably

Pure Storage® (NYSE: PSTG), the pioneer in advanced data storage technologies and services, has announced significant enhancements to its Enterprise Data Cloud architecture, expanding its platform into the public cloud to help businesses unlock the full potential of AI.

As enterprises accelerate AI adoption, the challenge has shifted from simply storing data to managing, mobilizing, and securing it across distributed infrastructures. The Enterprise Data Cloud unifies block, file, and object data management under one architecture, ensuring end-to-end control, automation, and cyber resilience across cloud, core, and edge.

“In today’s AI era, access to data is everything.” — Rob Lee, Pure Storage

“At a time when AI depends on data accessibility and security, success relies on having your data available everywhere and manageable from a single, intelligent control plane,” said Rob Lee, Chief Technology Officer at Pure Storage.

“Managing data, not just storing it, is now the foundation for AI-readiness.” — Rob Lee, Pure Storage

Key announcements include:

  • Pure Storage Cloud, with native Azure integration, offering seamless data migration and enterprise-grade resiliency for hybrid environments.
  • Portworx® integration with Pure Fusion, extending unified management to modern, containerized applications.
  • Pure1 AI Copilot expansion, enabling natural language-based system monitoring and troubleshooting.
  • Next-gen FlashArray portfolio and Purity Deep Reduce, improving performance while cutting infrastructure costs and energy use.

Pure Storage is also integrating with NVIDIA Dynamo to accelerate AI inference workloads, underscoring its role in making AI infrastructure more efficient, scalable, and sustainable.

With these innovations, Pure Storage positions itself as a critical enabler of the AI economy, ensuring that enterprises can unify, govern, and scale data while lowering costs and carbon footprint.

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