Hitachi iQ Studio

Accelerate AI and HPC workloads with mission-ready file services built for federal environments.

Hitachi iQ Studio delivers high-performance, AI-optimized file services that enable federal agencies to build, train, and scale AI and HPC workloads, securely and efficiently, across on-premises and hybrid environments. Designed for data-intensive missions, iQ Studio eliminates bottlenecks between data and compute while maintaining full control, compliance, and operational predictability.

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Overview

AI Workloads Are Outpacing Legacy File Infrastructure

Federal agencies are rapidly adopting AI, machine learning, and high-performance computing to advance mission priorities, from intelligence analysis and scientific research to logistics optimization and cyber defense. However, legacy file systems were not designed to support the scale, throughput, and concurrency required by modern, GPU-accelerated AI pipelines.

As data volumes grow and architectures become more distributed, agencies face slow data access, fragmented storage environments, and increased operational complexity. Hitachi iQ Studio addresses these challenges with a purpose-built, AI-optimized file services platform that removes data bottlenecks and keeps AI workloads running at the speed of mission.

Solution

Enterprise File Services Built for Federal AI Missions at Scale

Hitachi iQ Studio is an integrated, software-defined file services solution designed to support AI, ML, and HPC workloads running on modern GPU and CPU architectures. It provides a unified, high-performance data layer that feeds compute environments without compromising security, governance, or operational control.

Built to operate in secure, on-premises and hybrid environments, iQ Studio enables agencies to modernize AI infrastructure while maintaining alignment with federal compliance, data sovereignty, and acquisition requirements.

By removing data access bottlenecks and simplifying file services management, Hitachi iQ Studio helps federal teams focus on mission outcomes, not infrastructure tuning.