Stock Markets June 15, 2026 10:48 AM

Sharon AI Expands Data Foundation With 600PB VAST Deployment for Sovereign AI

Large-scale VAST AI Operating System roll-out aimed at supporting sovereign AI workloads across Australia and Asia-Pacific

By Ajmal Hussain
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SHAZ

SharonAI Holdings said it will standardize on the VAST AI Operating System to provision 600 petabytes of storage across its AI cloud infrastructure. The deployment is positioned as the primary data layer for the company’s sovereign AI offering in Australia and the Asia-Pacific region and is described by the partners as one of the region’s largest sovereign AI data foundations.

Sharon AI Expands Data Foundation With 600PB VAST Deployment for Sovereign AI
SHAZ
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Key Points

  • 600PB VAST deployment will serve as the foundational data layer for Sharon AI’s sovereign AI infrastructure in Australia and Asia-Pacific.
  • Partners estimate the deployment equates to supporting roughly 100,000 GPUs using a benchmark of 6PB per 1,000 GPUs for large-scale workloads.
  • VAST AI Operating System features include a single global namespace and built-in multi-tenancy with performance SLAs and isolated controls.

SharonAI Holdings Inc. (NASDAQ:SHAZ) announced an expanded collaboration with VAST Data that will see the VAST AI Operating System deployed at 600 petabytes across Sharon AI’s cloud infrastructure, and the company's shares rose 6.7% on Monday following the news.

The storage deployment is intended to serve as the core data layer for Sharon AI’s sovereign AI infrastructure, supporting a range of customers - government, enterprise, research, and AI-native organizations - throughout Australia and the Asia-Pacific region. The partners framed the rollout as a major step in providing an onshore, high-performance data foundation for sensitive and strategic workloads.

VAST and Sharon AI quantified the 600PB build as equivalent to the data backbone needed for roughly 100,000 GPUs, using a benchmark of 6PB of optimized AI storage per 1,000 GPUs for large-scale workloads. The firms characterized the implementation as one of the largest sovereign AI data foundations in the Asia-Pacific market.

The VAST AI Operating System is built around a DASE architecture intended to remove traditional storage performance bottlenecks by operating as a parallel distributed system. Key platform features noted by the partners include a single global namespace that allows processors to access data without copying or moving petabytes, and integrated multi-tenancy that provides isolation, performance service-level agreements, and separate controls for each customer.

"Our customers refuse to choose between keeping their data sovereign and running AI at full speed - they need both at the highest level," James Manning, Co-Founder and CEO of Sharon AI, said in a company statement. "Standardizing on the VAST AI Operating System at this unprecedented 600PB scale gives us exactly that: a rock-solid, high-performance foundation we can scale confidently as demand for sovereign AI across Australia and Asia-Pacific accelerates."

The announcement emphasizes the partnership’s role in enabling Australia’s development of independent, high-performance AI capability while retaining sensitive workloads and strategic data onshore. The companies said they will continue engineering collaboration as Sharon AI’s customer workloads expand.


Key points

  • The 600PB VAST deployment will form the primary data layer for Sharon AI’s sovereign AI infrastructure across Australia and the Asia-Pacific region.
  • The partners estimate the storage is equivalent to supporting about 100,000 GPUs, based on a benchmark of 6PB per 1,000 GPUs.
  • Features of the VAST AI Operating System highlighted include a single global namespace and built-in multi-tenancy with performance SLAs and isolated controls.

Risks and uncertainties

  • The companies note they will need to continue engineering collaboration as Sharon AI’s customer workloads scale - ongoing technical coordination is therefore an explicit dependency.
  • The announcement underlines customer demand for both sovereignty and high AI performance; meeting both requirements at scale is presented as a core challenge the deployment seeks to address.
  • The effectiveness of the 600PB deployment to serve the targeted workloads depends on the claimed benchmark equivalencies and operational delivery at this scale.

Risks

  • Continued engineering collaboration is required as Sharon AI’s customer workloads scale - coordination and technical work remain necessary.
  • Meeting customers’ dual requirement for data sovereignty and high-performance AI at scale is a central challenge the deployment must address.
  • Operational delivery at the claimed 600PB scale must match benchmark expectations to support the targeted large-scale workloads.

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