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Netweb Technologies Introduces Tyrone ParallelStor Velox — A Unified Data Platform  Powering AI, HPC, and Enterprise Infrastructure 

Netweb Technologies today announced Tyrone ParallelStor  Velox, a Unified Data Platform with parallel file system capabilities, designed to address one of  the most critical challenges in modern computing: the data bottleneck in AI infrastructure. 

As organizations scale AI workloads and deploy increasingly powerful GPU clusters, a  fundamental constraint has emerged, while compute performance has advanced rapidly, data  infrastructure has not kept pace. 

AI performance is no longer limited by compute; it is limited by data. 

Fragmented storage environments, duplicated datasets, and inconsistent access models are slowing  down AI pipelines, underutilizing expensive compute resources, and increasing operational  complexity. ParallelStor Velox is built to solve this problem. 

A Data Backbone for AI-Scale Infrastructure 

Velox acts as a high-performance data backbone for AI, HPC, and enterprise workloads, ensuring  that data can be accessed, moved, and processed at the speed modern compute demands. 

By unifying data across flash, disk, tape, and cloud into a single global namespace, Velox  eliminates silos and enables seamless, high-speed access across environments. 

This allows AI pipelines, analytics frameworks, and enterprise applications to operate on a single,  consistent data layer — without duplication or delays. 

Designed to Eliminate the Data Bottleneck 

Traditional storage architectures were built for capacity. Velox is engineered for data velocity and  scale. 

To further accelerate AI data pipelines, Velox supports advanced data path optimization  technologies.: 

  • High-throughput data pipelines to feed GPU clusters efficiently 
  • Concurrent access at scale for AI training, simulation, and analytics 
  • Consistent performance across distributed environments 
  • Elimination of redundant data copies across file and object workloads 
  • Support for NVIDIA GPUDirect Storage, enabling direct data transfer between storage and  GPU memory, bypassing CPU overhead and significantly reducing latency for AI/ML  workloads  

The result is higher GPU utilization, faster model training, and improved infrastructure efficiency.

Unified Data Across Hybrid and Distributed Environments 

Modern enterprises operate across data centers, edge locations, and multi-cloud environments. This  fragmentation introduces inefficiencies, increases storage costs, and limits agility. 

Velox addresses this by providing: 

  • A single unified data platform across on-prem and cloud environments • Multi-protocol access (POSIX, NFS, SMB, S3/Swift, Hadoop) on the same dataset • Policy-driven data lifecycle management, aligning performance and cost with data usage 

Data is automatically placed on the appropriate tier — from high-performance flash to cost-efficient  object storage or tape — without changing how users and applications access it. 

Built for Sovereign and Mission-Critical Infrastructure 

ParallelStor Velox is designed for data-intensive, high-growth sectors, including: 

  • AI & HPC / Research – powering model training, simulations, and advanced analytics • Government & Public Sector – enabling sovereign data infrastructure with unified control and  compliance 
  • BFSI – supporting real-time analytics, risk modeling, and regulatory data environments 

Built in India, Velox aligns with the growing need for sovereign AI infrastructure, offering  organizations greater control, security, and scalability over their data environments. 

Leadership Perspective 

“AI infrastructure is only as effective as the data layer behind it. Without high-performance data  pipelines, even the most advanced compute systems remain underutilized,” said Swastik  Chakraborty, VP, Netweb Technologies. 

“With Tyrone ParallelStor Velox, we are enabling organizations to move beyond fragmented  storage and adopt a unified data platform that can keep pace with AI, HPC, and enterprise  workloads at scale.” 

Key Capabilities 

  • AI-Ready Data Backbone – Optimized for high-throughput, low-latency access • Unified Data Platform – Single global namespace across storage tiers 
  • Parallel Performance at Scale – High IOPS and throughput with scalability • Multi-Protocol Access – POSIX, NFS, SMB, S3/Swift, Hadoop 
  • Intelligent Data Lifecycle Management – Automated tiering 
  • Enterprise-Grade Security & Resilience – Built-in protection and governance 

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