Everpure Announces Data Stream to Expand AI-Ready Data Offerings

As organizations increasingly deploy AI agents to automate complex tasks, they are constrained by significant challenges. These include ingesting enterprise data for AI use, maintaining strict data security and governance, and building infrastructure capable of scaling to meet the demands of AI. Everpure Data Stream addresses these friction points by reducing raw data preparation from months to minutes, enforcing stream-level access controls that keep information securely within the corporate network, and providing a scale-out architecture that lets storage and compute scale independently to match changing model requirements.

"We are undergoing a massive capital supercycle in AI, where the defining factor between industry icons and those who disappear is the ability to adapt," said Robert Lee, Chief Technology Officer, Everpure. "The winning AI architecture requires a unified platform that allows businesses to start small with immediate use cases and seamlessly scale to exabyte capacity. Everpure solves this challenge by delivering a trusted, secure, and high-performance data pipeline that accelerates time-to-results for an enterprise's data."

Bridging Data Readiness and Production AI

To be truly ready for AI, data must be classified, curated, cleaned, secured and scaled. Everpure enables these outcomes end-to-end on the AI path.

Classify, contextualize, and govern your data

Enterprise data is heavily fragmented across SaaS, cloud, on-premises, and mainframe environments, turning data integration and migration into a costly barrier for secure accurate AI system deployment. Everpure Data Intelligence (formerly 1touch) solves this by discovering, classifying, and contextualizing enterprise information at its source to map data dependencies into a data relationship graph. This universal data intelligence layer makes data understanding and relationships available via APIs and the Model Context Protocol (MCP), delivering highly relevant, accurate data inputs to AI models.

Additionally, as AI systems and agents interact directly with data, Data Intelligence provides attribute-based access controls with security and governance policies—ensuring rigorous compliance across all AI workloads to guarantee enterprise-grade trust.

Convert raw data for AI use

The availability of Everpure Data Stream accelerates enterprise AI projects by removing cost and complexity barriers. Everpure Data Stream extends upon the NVIDIA AI Data Platform reference design to deliver the foundation enterprises need to seamlessly convert unstructured data into real-time AI results. By replacing manual data ingestion and manipulation with a GPU accelerated pipeline from ingestion to inference, Data Stream helps organizations see results faster.

"Building the next generation of AI factories requires a data architecture that seamlessly bridges secure, governed enterprise data with accelerated computing," said Jason Hardy, Vice President of Storage Technology at NVIDIA. "Everpure's integration with the NVIDIA AI Data Platform provides the infrastructure foundation organizations need to scale from AI experimentation to full-production intelligence."

Everpure is also developing next generation AI solutions with NVIDIA STX, a modular foundation for AI-native storage using NVIDIA Vera and the NVIDIA Vera BlueField-4 STX storage processor. This collaboration focuses on bringing acceleration, security and intelligent data services closer to enterprise data as organizations deploy agentic AI at scale.

Scale performance across all workloads

Fragmented storage pipelines starve AI compute clusters, stalling training and inference. To prevent this, FlashBlade delivers ultra-low latency and leverages KV Cache Accelerator to optimize memory efficiency during inference. Powered by the non-disruptive Evergreen architecture, organizations can start with FlashBlade//S and scale seamlessly to FlashBlade//EXA for GPU-cloud scale, effortlessly expanding from data stream to large AI factories. Finally, Portworx provides the container platform needed to seamlessly deploy, manage, and run these AI pipelines from the edge to the core data center.

"Idle GPUs are economically destructive," said Sabur Mian, CEO and Founder of STN. "We standardized on Everpure FlashBlade because it eliminates the data bottlenecks that typically stall massive AI workloads. FlashBlade//EXA allows us to scale thousands of GPUs with up to 800 Gbps of throughput per node while maintaining rock-solid latency, driving up to 20% performance improvement for our customers."

By delivering on these capabilities within a single, cohesive architecture, Everpure eliminates the temptation to build yet another wave of fragmented data silos. A new, commissioned IDC Global AI Readiness Survey¹ reveals that 94% of IT leaders identify data quality as the absolute determining factor in AI success. Everpure's unified foundation gives enterprises the long-term flexibility and agility required to adapt as the broader AI landscape continues to evolve.

Additional Resources

• Tune into the livestream of Everpure's Accelerate 2026 mainstage keynote, which begins at 9am PDT on June 17-18, 2026, at www.everpuredata.com.
• CEO Perspective: Putting Data First
• IDC Report | Why AI Projects Fail: Revealing the Data Infrastructure Gap | Everpure
• Learn more about Everpure Data Stream.

About Everpure

Everpure (NYSE: P) allows organizations to take control of their data with an industry-leading, ever-evolving storage and data management platform. We help companies unleash the power of their data by ensuring it is accessible, intelligent, and ready to perform in the AI era. We make data management effortless while simultaneously scaling performance and significantly reducing energy consumption. With one of the highest Net Promoter Scores for over a decade, Everpure is the choice of the world's most innovative organizations. For more information, visit www.everpuredata.com.

The release timing of any discussed functionality remains at Everpure's sole discretion. The information provided is not a commitment to deliver discussed functionality based on any timeline.

¹ IDC White Paper, sponsored by Everpure, "Why AI Projects Fail: Revealing the Data Infrastructure Gap," #US54552726-WP, June 2026.

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SOURCE Everpure