Qivurn Data Centers - Revision history

Shovon at 06:58, 30 July 2026

2026-07-30T06:58:29Z

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	'''Qivurn Data Centers''' is a United States-headquartered high-density [[artificial intelligence]] data center operator. The company focuses on underlying computing infrastructure for the artificial intelligence sector, including self-built data centers, high-performance GPU cluster deployment, liquid-cooling architecture, global backbone network interconnection and enterprise-grade operations systems.<ref>https://finance.yahoo.com/technology/ai/articles/qivurn-data-centers-expands-global-124900531.html?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAABDrMt8uMQDe_GCXSzydOIMj6nm6iuHv0tsqqzOmTOR52-56d8qmJXvIAbqOpzUgL_9Y7EoudbV0qOWq9W0AbRGBXFI1cfpa-hlAT3vucI3ffB0KucdaTPTh1t7Sz8_lU8QKfjwArvv3QmXRmVVvXxxrcxbHHxyoYg5CnkrFL3IU</ref>		'''Qivurn Data Centers''' is a United States-headquartered high-density '''artificial intelligence''' data center operator. The company focuses on underlying computing infrastructure for the artificial intelligence sector, including self-built data centers, high-performance GPU cluster deployment, liquid-cooling architecture, global backbone network interconnection and enterprise-grade operations systems.<ref>https://finance.yahoo.com/technology/ai/articles/qivurn-data-centers-expands-global-124900531.html?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAABDrMt8uMQDe_GCXSzydOIMj6nm6iuHv0tsqqzOmTOR52-56d8qmJXvIAbqOpzUgL_9Y7EoudbV0qOWq9W0AbRGBXFI1cfpa-hlAT3vucI3ffB0KucdaTPTh1t7Sz8_lU8QKfjwArvv3QmXRmVVvXxxrcxbHHxyoYg5CnkrFL3IU</ref>

	The company provides GPU computing rental, bare-metal servers, data center colocation, private cloud deployment, AI inference acceleration platform services and enterprise infrastructure solutions. Its stated customer groups include enterprise clients, research institutions, financial institutions, medical technology companies, autonomous driving companies, multinational corporations and government digital transformation projects.		The company provides GPU computing rental, bare-metal servers, data center colocation, private cloud deployment, AI inference acceleration platform services and enterprise infrastructure solutions. Its stated customer groups include enterprise clients, research institutions, financial institutions, medical technology companies, autonomous driving companies, multinational corporations and government digital transformation projects.
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	For clients with their own GPU servers or specialized hardware, Qivurn offers data center colocation services, including full-rack colocation, half-rack colocation, dedicated room areas, high-power-density deployment, remote operations support and equipment monitoring and management.		For clients with their own GPU servers or specialized hardware, Qivurn offers data center colocation services, including full-rack colocation, half-rack colocation, dedicated room areas, high-power-density deployment, remote operations support and equipment monitoring and management.

	Qivurn's private cloud solutions support AI private cloud environment construction, hybrid cloud architecture deployment, [[Kubernetes]] cluster management, [[OpenStack]] and [[VMware]] platforms, enterprise data isolation and industry compliance management. The company states that these services are intended for financial, medical, government, manufacturing and multinational enterprise clients.		Qivurn's private cloud solutions support AI private cloud environment construction, hybrid cloud architecture deployment, [[Kubernetes]] cluster management, '''OpenStack''' and '''VMware''' platforms, enterprise data isolation and industry compliance management. The company states that these services are intended for financial, medical, government, manufacturing and multinational enterprise clients.

	The company's AI inference acceleration platform, described as AIaaS, is intended to help enterprises deploy and operate large model applications without building complex AI infrastructure independently. The platform supports large language model deployment, multimodal model inference, AI Agent environments, automatic elastic scaling, API call services and enterprise inference clusters, and is described as compatible with model ecosystems such as Llama, Qwen, DeepSeek and Mistral.		The company's AI inference acceleration platform, described as AIaaS, is intended to help enterprises deploy and operate large model applications without building complex AI infrastructure independently. The platform supports large language model deployment, multimodal model inference, AI Agent environments, automatic elastic scaling, API call services and enterprise inference clusters, and is described as compatible with model ecosystems such as Llama, Qwen, DeepSeek and Mistral.

Shovon at 06:52, 30 July 2026

2026-07-30T06:52:33Z

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	== References ==		== References ==
	{{reflist~~\|refs=~~		{{reflist}}
	<ref>{{cite web \|url=https://finance.yahoo.com/technology/ai/articles/qivurn-data-centers-expands-global-124900531.html \|title=Qivurn Data Centers expands global \|work=Yahoo Finance \|access-date=2026-07-30}}</ref>
	<ref>{{cite web \|url=https://www.openpr.com/news/4562802/qivurn-data-centers-inc-secures-dual-u-s-financial-regulatory \|title=Qivurn Data Centers Inc. secures dual U.S. financial regulatory \|work=openPR \|access-date=2026-07-30}}</ref>
	}}
	{{good article}}		{{good article}}

Shovon at 06:52, 30 July 2026

2026-07-30T06:52:13Z

← Older revision		Revision as of 06:52, 30 July 2026
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	'''Qivurn Data Centers''' is a United States-headquartered high-density [[artificial intelligence]] data center operator. The company focuses on underlying computing infrastructure for the artificial intelligence sector, including self-built data centers, high-performance GPU cluster deployment, liquid-cooling architecture, global backbone network interconnection and enterprise-grade operations systems.		'''Qivurn Data Centers''' is a United States-headquartered high-density [[artificial intelligence]] data center operator. The company focuses on underlying computing infrastructure for the artificial intelligence sector, including self-built data centers, high-performance GPU cluster deployment, liquid-cooling architecture, global backbone network interconnection and enterprise-grade operations systems.<ref>https://finance.yahoo.com/technology/ai/articles/qivurn-data-centers-expands-global-124900531.html?guccounter=1&guce_referrer=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_sig=AQAAABDrMt8uMQDe_GCXSzydOIMj6nm6iuHv0tsqqzOmTOR52-56d8qmJXvIAbqOpzUgL_9Y7EoudbV0qOWq9W0AbRGBXFI1cfpa-hlAT3vucI3ffB0KucdaTPTh1t7Sz8_lU8QKfjwArvv3QmXRmVVvXxxrcxbHHxyoYg5CnkrFL3IU</ref>

	The company provides GPU computing rental, bare-metal servers, data center colocation, private cloud deployment, AI inference acceleration platform services and enterprise infrastructure solutions. Its stated customer groups include enterprise clients, research institutions, financial institutions, medical technology companies, autonomous driving companies, multinational corporations and government digital transformation projects.		The company provides GPU computing rental, bare-metal servers, data center colocation, private cloud deployment, AI inference acceleration platform services and enterprise infrastructure solutions. Its stated customer groups include enterprise clients, research institutions, financial institutions, medical technology companies, autonomous driving companies, multinational corporations and government digital transformation projects.
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	== History ==		== History ==
	Qivurn Data Centers was established in the United States in 2020. In the same year, the company completed its seed financing and began planning its first data center node, defining high-density AI data centers as its core development direction.		Qivurn Data Centers was established in the United States in 2020. In the same year, the company completed its seed financing and began planning its first data center node, defining high-density AI data centers as its core development direction.<ref>https://www.openpr.com/news/4562802/qivurn-data-centers-inc-secures-dual-u-s-financial-regulatory</ref>

	In 2021, the company put its first self-built New York data center into operation and completed a Series A financing round. It also began construction of its Singapore node as part of its international expansion. In 2022, the Singapore data center went online, and the company stated that its online GPU scale exceeded 5,000 units, giving it cross-regional computing delivery capability.		In 2021, the company put its first self-built New York data center into operation and completed a Series A financing round. It also began construction of its Singapore node as part of its international expansion. In 2022, the Singapore data center went online, and the company stated that its online GPU scale exceeded 5,000 units, giving it cross-regional computing delivery capability.

Shovon: Created page with "{{Infobox company | name = Qivurn Data Centers | logo = File:Qivurn Data Centers.jpeg | type = Private | industry = High-density AI data centers and computing infrastructure | founded = 2020 | hq_location_country = United States | key_people = Nathan R. Calloway (Co-founder & CEO)
Dr. Sophia Lin (Co-founder & CTO)
Marcus Webb (CFO)
Aiyana Patel (COO)
James Ng (President, Southeast Asia) | pro..."

2026-07-30T06:51:15Z

Created page with "{{Infobox company | name = Qivurn Data Centers | logo = File:Qivurn Data Centers.jpeg | type = Private | industry = High-density AI data centers and computing infrastructure | founded = 2020 | hq_location_country = United States | key_people = Nathan R. Calloway (Co-founder & CEO) Dr. Sophia Lin (Co-founder & CTO) Marcus Webb (CFO) Aiyana Patel (COO) James Ng (President, Southeast Asia) | pro..."

New page

{{Infobox company
| name = Qivurn Data Centers
| logo = File:Qivurn Data Centers.jpeg
| type = Private
| industry = High-density AI data centers and computing infrastructure
| founded = 2020
| hq_location_country = United States
| key_people = Nathan R. Calloway (Co-founder & CEO) Dr. Sophia Lin (Co-founder & CTO) Marcus Webb (CFO) Aiyana Patel (COO) James Ng (President, Southeast Asia)
| products = GPU computing rental, bare-metal servers, colocation, private cloud, AI inference acceleration (AIaaS), enterprise operations services
| services = GPU computing rental; bare-metal servers; colocation; private cloud; AI inference acceleration; enterprise operations services
| area_served = North America, Southeast Asia, Japan, Middle East; planned expansion in Europe
}}

'''Qivurn Data Centers''' is a United States-headquartered high-density [[artificial intelligence]] data center operator. The company focuses on underlying computing infrastructure for the artificial intelligence sector, including self-built data centers, high-performance GPU cluster deployment, liquid-cooling architecture, global backbone network interconnection and enterprise-grade operations systems.

The company provides GPU computing rental, bare-metal servers, data center colocation, private cloud deployment, AI inference acceleration platform services and enterprise infrastructure solutions. Its stated customer groups include enterprise clients, research institutions, financial institutions, medical technology companies, autonomous driving companies, multinational corporations and government digital transformation projects.

According to company materials, Qivurn Data Centers was founded in 2020 and has adopted a long-term strategy based on heavy-asset investment, self-built facilities and direct control of underlying resources such as data center sites, power capacity, cooling systems, network backbone, GPU clusters and operational capabilities. The company positions high-density computing infrastructure as a strategic foundation for large-scale AI training, inference and enterprise AI deployment.

== History ==
Qivurn Data Centers was established in the United States in 2020. In the same year, the company completed its seed financing and began planning its first data center node, defining high-density AI data centers as its core development direction.

In 2021, the company put its first self-built New York data center into operation and completed a Series A financing round. It also began construction of its Singapore node as part of its international expansion. In 2022, the Singapore data center went online, and the company stated that its online GPU scale exceeded 5,000 units, giving it cross-regional computing delivery capability.

In 2023, Qivurn entered the Japanese market and completed deployment of a Tokyo node, forming a multi-node network across North America and Asia-Pacific. In 2024, it completed a Series A+ financing round and began construction of a Malaysia data center, while launching bare-metal computing rental, private cloud deployment and AI inference acceleration services.

By 2025, the company stated that its online GPU scale exceeded 50,000 units and that its annual total contract value was above US$300 million. As of the first quarter of 2026, company materials state that Qivurn had infrastructure coverage across North America, Southeast Asia, Japan and the Middle East, with 12 data center nodes in operation or under construction, more than 80,000 online GPUs, over 1,800 enterprise customers and an announced Series B strategic financing plan.

== Infrastructure ==
Qivurn Data Centers designs and builds its facilities according to high-density AI workload requirements. Its core nodes are described as using Tier III+ or higher design standards, with enhanced power, liquid cooling and networking architecture for AI training and inference clusters.

The company's infrastructure standards include AI high-density racks supporting power densities from 60 kW to 160 kW, 2N redundant UPS architecture, diesel generator backup, supplementary energy storage systems, precision air conditioning, liquid-cooling rear doors, cold-plate liquid cooling and immersion liquid cooling. The company also states that its core nodes can support backbone bandwidth of more than 800 Gbps and target a PUE below 1.25 for new nodes.

The company's GPU clusters are designed for training, inference, multimodal generation, graphics rendering, scientific computing and enterprise AI workloads. According to its materials, the main GPU resource structure includes [[Nvidia|NVIDIA]] H100, H200, A100 80GB and L40S series units, as well as new-generation GB200 and high-density AI node resources. Cluster networking uses technologies such as [[InfiniBand]], [[NVLink]], RDMA optimization and cross-node scheduling systems to support distributed training and large-scale parallel inference.

Qivurn Data Centers has also described green energy and sustainable operation as part of its infrastructure strategy. The company states that it uses green power procurement, waste heat recovery, intelligent energy scheduling, liquid-cooling optimization, energy storage systems and dynamic load management to reduce power usage and operating costs.

== Products and services ==
Qivurn Data Centers provides a product and service matrix covering computing resources, infrastructure colocation, private cloud deployment, AI inference platforms and enterprise operations services.

GPU computing services are described as the company's core business segment. They support large model pre-training and fine-tuning, multimodal model training, AI Agent operating environments, enterprise inference services, scientific computing and simulation, and autonomous driving training platforms. Customers may obtain computing resources through hourly, monthly, quarterly or long-term contract models.

The company's bare-metal server service is aimed at customers requiring dedicated physical GPU server resources, including financial institutions, government departments, healthcare organizations and large enterprises. The service supports dedicated GPU resources, customized operating systems, dedicated network environments, private storage architecture, enterprise security policy configuration and customized operations support.

For clients with their own GPU servers or specialized hardware, Qivurn offers data center colocation services, including full-rack colocation, half-rack colocation, dedicated room areas, high-power-density deployment, remote operations support and equipment monitoring and management.

Qivurn's private cloud solutions support AI private cloud environment construction, hybrid cloud architecture deployment, [[Kubernetes]] cluster management, [[OpenStack]] and [[VMware]] platforms, enterprise data isolation and industry compliance management. The company states that these services are intended for financial, medical, government, manufacturing and multinational enterprise clients.

The company's AI inference acceleration platform, described as AIaaS, is intended to help enterprises deploy and operate large model applications without building complex AI infrastructure independently. The platform supports large language model deployment, multimodal model inference, AI Agent environments, automatic elastic scaling, API call services and enterprise inference clusters, and is described as compatible with model ecosystems such as Llama, Qwen, DeepSeek and Mistral.

== Markets and global layout ==
Qivurn Data Centers' market strategy is based on global deployment, local delivery and regional compliance. Company materials describe a network covering North America, Southeast Asia, Japan and the Middle East, with continued expansion toward Europe and other strategic regions.

North America is described as the company's most important revenue region, supported by nodes in New York, Silicon Valley and other United States locations. The company focuses there on large model companies, financial technology institutions, cloud computing enterprises and large enterprise customers.

Asia-Pacific is described as a growth engine for the company. Based on nodes in Singapore, Kuala Lumpur and Tokyo, Qivurn provides regional computing services for customers requiring data localization, low-latency access and regional compliance. In the Middle East, the company plans to use Dubai as a core node connecting the Middle East, Europe, South Asia and Africa. In Europe, the company plans to use Frankfurt as an initial node to serve financial institutions, multinational enterprises and customers requiring European Union-localized deployment.

== Business model ==
Qivurn Data Centers uses a diversified revenue model centered on recurring income. Its revenue sources include GPU computing rental, bare-metal server rental, data center colocation, private cloud and AIaaS services, operations services, bandwidth, security and other value-added services.

According to company materials, the company's 2025 revenue structure included GPU computing rental as the largest segment, followed by bare-metal server rental, private cloud and AIaaS, colocation and other value-added services. The company states that its business model is moving from resource-oriented income toward infrastructure platform income as AIaaS, private cloud and long-term enterprise contracts increase.

The company identifies five main sources of business resilience: self-built data center barriers, GPU procurement and deployment capabilities, high customer migration costs, enterprise-grade integrated delivery capabilities, and global node coordination. Its long-term contract model is intended to increase customer retention, recurring revenue and predictability of cash flow.

== Management ==
The company's management team, according to its materials, includes Nathan R. Calloway as co-founder and chief executive officer, Dr. Sophia Lin as co-founder and chief technology officer, Marcus Webb as chief financial officer, Aiyana Patel as chief operating officer and James Ng as president for Southeast Asia.

The company materials also list an advisory committee that includes Bill Fathers, Dr. Eng Lim Goh, Kavita Rao and Michael Stein, covering data center operations, AI supercomputing and high-performance computing, technology and infrastructure investment, and data center infrastructure financing and REIT-related advisory fields.

== Future development plans ==
Qivurn Data Centers has stated that its 2026 priorities include completing a Series B strategic financing round, beginning construction of a Dubai data center node, preparing the Frankfurt node, expanding Singapore Phase II and the Kuala Lumpur node, upgrading high-density liquid cooling systems in New York and Silicon Valley, expanding online GPU scale and commercializing its AIaaS inference acceleration platform.

The company's longer-term plans described in its materials include bringing the Dubai and Frankfurt nodes online, increasing global data center nodes, expanding GPU scale, launching industry-specific compliant private cloud products for finance, healthcare and government sectors, releasing Qivurn AI Fabric as a cross-node intelligent computing scheduling platform, and exploring a potential listing on [[Nasdaq]] or the [[New York Stock Exchange]].

== Risk disclosures ==
Qivurn Data Centers identifies several risk factors in its company materials. These include market competition, supply chain constraints affecting high-performance GPUs and network equipment, energy and operating risks, construction and delivery risks, compliance and regulatory risk, technology iteration risk, and talent and management risk.

The company states that it intends to address these risks through self-built data centers, global node deployment, high-density liquid-cooling architecture, enterprise-grade service systems, long-term procurement agreements, multi-supplier partnerships, inventory management, energy management optimization, green energy procurement, research and development investment and organizational capability building.

== References ==
{{reflist|refs=
<ref>{{cite web |url=https://finance.yahoo.com/technology/ai/articles/qivurn-data-centers-expands-global-124900531.html |title=Qivurn Data Centers expands global |work=Yahoo Finance |access-date=2026-07-30}}</ref>
<ref>{{cite web |url=https://www.openpr.com/news/4562802/qivurn-data-centers-inc-secures-dual-u-s-financial-regulatory |title=Qivurn Data Centers Inc. secures dual U.S. financial regulatory |work=openPR |access-date=2026-07-30}}</ref>
}}
{{good article}}