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Hammerspace to Showcase How Enterprises Can Dramatically Improve AI Infrastructure Efficiency at RAISE Summit 2026


News provided by

Hammerspace

Jul 06, 2026, 08:00 ET

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Hammerspace to demonstrate how data orchestration improves AI economics by accelerating time-to-value, reducing time-to-first-token and keeping GPUs continuously productive.

REDWOOD CITY, Calif., July 6, 2026 /PRNewswire-PRWeb/ -- Hammerspace, the high-performance data platform for AI anywhere, today announced its senior executive team will participate in RAISE Summit 2026, taking place July 8–9 at the Carrousel du Louvre in Paris. At Booth 3B, Hammerspace will demonstrate how enterprises can win the AI infrastructure race before the first token by eliminating one of AI's largest hidden constraints: data readiness.

As enterprise inference and RAG deployments accelerate, AI economics are not defined by GPU counts or storage performance alone. AI outcomes depend on how quickly environments become productive, how rapidly workloads gain access to the right data, and how efficiently infrastructure keeps GPUs generating useful output.

"Hammerspace changes the operating model for enterprise AI by making data available where AI workloads need it, without forcing organizations into months of storage procurement, migration and manual data movement."

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The Hammerspace Data Platform addresses these challenges by unifying the data estate on existing storage and automating data orchestration to make data available where GPUs need it without large-scale data migration or new storage procurement.

At RAISE Summit, attendees will learn how Hammerspace improves three metrics that determine AI success:

  • Time to Very First Token: Reducing the time required to make enterprise data AI-ready so projects can begin in days instead of months.
  • Time to First Token: Orchestrating and pre-positioning data so AI workloads can begin generating results faster.
  • Time per Token: Continuously supplying GPUs with the right data to improve utilization and lower the effective cost of AI operations.

"AI leadership has been shaped by model innovation, infrastructure scale and access to data," said David Flynn, founder and CEO of Hammerspace. "The next challenge is efficiency: how quickly organizations can activate their own enterprise data and turn it into useful AI output without unnecessary delay, cost or operational complexity."

Traditional AI deployment models often treat AI readiness as an infrastructure project, requiring organizations to acquire new storage, build new environments and migrate data before productive work can begin. Hammerspace's Data Platform instead treats AI readiness as a data availability challenge, enabling organizations to use data in place across existing storage systems and cloud environments while creating a unified global namespace for AI workloads.

By continuously discovering, orchestrating and positioning data where AI workloads need it, Hammerspace reduces idle GPU cycles, minimizes unnecessary data movement and helps organizations improve productive GPU utilization while lowering cost per token.

Hammerspace's Data Platform enables organizations to:

  • Activate enterprise data in place across existing storage systems and cloud environments
  • Eliminate storage procurement and migration delays that traditionally postpone AI initiatives
  • Unify distributed data through a global namespace without creating additional silos
  • Pre-position data before workloads require it, reducing time to first token
  • Continuously orchestrate active data throughout AI pipelines to maximize GPU productivity

Organizations using traditional storage-first AI data approaches may spend between 14 and 30 weeks acquiring infrastructure and migrating data before productive AI work begins. Hammerspace can reduce that timeline to as little as a few days to one week, representing acceleration of up to 70x.

"Hammerspace changes the operating model for enterprise AI by making data available where AI workloads need it, without forcing organizations into months of storage procurement, migration and manual data movement," Flynn added. "That means teams can start faster, use existing infrastructure more efficiently, and keep AI pipelines supplied with the data required to produce results."

Executive Speakers at RAISE Summit

David Flynn will present on the Main Stage on July 8, sharing how organizations can rethink AI infrastructure around the economics that matter most: speed to token generation, continuous GPU productivity and cost-efficient AI operations.

Molly Presley, Hammerspace SVP of Global Marketing, will present on July 9 on the Grace Hopper Stage in a session titled "The Data Problem: What AI Actually Runs On," examining why data readiness, not infrastructure procurement, has become the defining challenge for enterprise AI.

For more information about Hammerspace at RAISE Summit 2026, visit:

https://hammerspace.com/event/raise-summit-2026/

Learn More

  • More on the Hammerspace AI Solutions
  • Blog: How Hammerspace's AI Data Platform Solution Enables AI Anywhere
  • White Paper: Hammerspace Data Platform

About Hammerspace

Hammerspace is the high-performance data platform built to simplify and optimize AI infrastructure at scale. It makes all your data immediately accessible – anywhere across on-premises and cloud environments – without copying or migrating data into new silos. By integrating with existing storage, networking, and applications, Hammerspace creates a unified, high-speed data backbone for AI, enabling organizations to accelerate every stage of the AI pipeline while eliminating data silos.

Media Contact
Kim Pegnato, Hammerspace, 1 781-835-7118, [email protected], www.hammerspace.com

SOURCE Hammerspace

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