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Cudo Compute

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uuid00069hy

Namestring
Cudo Compute
Legal namestring
Cudo Ventures Limited
Websiteurl
cudocompute.com
Company typeenum
Private
Founded yearint
2021
Descriptiontext

Cudo Compute (legal entity: Cudo Ventures Limited) is a UK-based, privately held AI infrastructure company that designs, commissions, and operates enterprise-grade NVIDIA GPU clusters for production AI training and inference workloads. The company addresses end-to-end deployment constraints — land, power, and compute — by integrating site selection, hardware procurement through NVIDIA Preferred Partner channels, NVIDIA reference-aligned cluster design covering InfiniBand fabrics, high-performance storage (VAST, WEKA, DDN, NetApp), and direct liquid cooling for GB200/GB300 NVL72 rack-scale systems, with 24/7 SRE-led operations under a single accountable model. The product portfolio spans Hopper (H100, H200), Blackwell (B100, B200, B300, GB200 NVL72, GB300 NVL72), and pre-launch Vera Rubin (VR200) hardware, delivered in ISO 27001-certified data centres across North America, Europe, the UK, and MENA.

The business generates revenue through three streams: managed GPU cluster services on multi-year contracts, subscription or usage-based cloud GPU compute with OPEX consumption models compatible with bare metal, enterprise, and GPU-as-a-service structures, and one-time professional services for deployment, commissioning, and benchmarking. Customer segments include large enterprises requiring dedicated clusters from 128 to 40,000+ GPUs, AI-first companies and frontier model developers prioritising access to latest-generation hardware, and government and sovereign AI initiatives requiring jurisdiction-specific infrastructure with data residency, GDPR, CCPA, and FedRAMP-aligned controls. Commercial go-to-market is exclusively enterprise field sales with quote-based pricing, no public list rates, and primary intake through website enquiry forms targeting multi-year contracts.

The company has secured 250MW+ of contracted power capacity by end of 2026 with a 750MW+ target by end of 2027 and a multi-GW pipeline including exclusive European sites with power commitments and grid underwriting. Founder and CEO Matt Hawkins, who previously founded C4L, leads a senior team of seven executives including CTO Tim Dyce (ex-CERN and European Bioinformatics Institute), CFO David Bell, CSO Mark Denney (former CIO of HMRC and Barclays), and COO Lee Woodham with an explicit Series B mandate. No institutional funding rounds, revenue figures, or valuation disclosures are available.

Short descriptiontext

Cudo Compute is a UK-based AI infrastructure company that designs, commissions, and operates production-scale NVIDIA GPU clusters for enterprise, government, and AI-first customers across North America, Europe, UK, and MENA, leveraging NVIDIA Preferred Partner supply chain access and an integrated land-power-compute delivery model.

Operating statusenum
Operating
Ownership categoryenum
Headcount rangeband
11–50
akta.pro rankint
HeadquartersBournemouth, United Kingdom
HQ citystring
Bournemouth
HQ countrystring
United Kingdom
HQ regionstring
Europe
Markets served

Serves global market

Offices3 records

Each record includes

City, Country, Type, Description, Source

Keyword5 values
gpu cloud infrastructure, ai infrastructure services, bare metal gpu, enterprise ai compute, data center operations
Industry4 codes
1AI Compute Cloud & GPU-as-a-Service
CodeHDAAAAAKPrimaryYes
2GPU/Accelerator Compute Servers
CodeHDABADACPrimaryNo
3GPU-Accelerated & AI Training/Inference Servers
CodeHDACABAGPrimaryNo
4GPU-Accelerated HPC Systems
CodeHDACAOACPrimaryNo
NAICS code2 codes
  • Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services51821
  • Computer Systems Design and Related Services5415
SIC code2 codes
  • Electronic Computers3571
  • Services-Computer Integrated Systems Design7373
Product category
GPU Cloud Infrastructure
Social media profiles1 record
GTM motion2 records

Each record includes

Type, Description, Source

Revenue model3 records
1Managed GPU cluster services
TypeManaged Services
Description

Dedicated bare-metal GPU clusters managed by CUDO from deployment through 24/7 operations. Includes cluster commissioning, monitoring, firmware lifecycle management, and L3 support. Revenue recognised as a recurring managed services contract.

cudocompute.com
2Cloud GPU compute (subscription / usage-based)
TypeSubscription Recurring
Description

GPU compute access via subscription or consumption-based models. OPEX consumption models for predictable spend across hardware generations. Compatible with bare metal, enterprise, and GPU-as-a-service commercial structures.

cudocompute.com
3End-to-end deployment and commissioning services
TypeProfessional Services
Description

Deployment services covering site readiness assessment, rack deployment, cooling infrastructure, networking, OS and driver provisioning, and cluster benchmarking before handoff. One-time professional services revenue at deployment.

cudocompute.com
Marketing channels6 records

Each record includes

Title, Type, Stage, Description, Source

Distribution channels1 record

Each record includes

Title, Type, Scope, Target buyer, Description, Source

Cost components6 values
Infrastructure, Supply Chain, Technology or R&D, Personnel, Operations, Marketing or Sales
Pricing details3 tiers
1Bare metal GPU clusters — dedicated physical GPUs with no contention
ModelOtherBilling cadenceMulti-year contract
Notes

Complete control over physical machine. Renewable energy powered. No noisy neighbours. SpectrumX local networking, 300Gbps external connectivity, NVMe SSD storage. Quote-based pricing.

cudocompute.com
2Enterprise GPU infrastructure — custom cluster and colocation solutions
ModelSubscriptionBilling cadenceAnnual
Notes

Powerful GPU clusters, scalable data centre colocation, large GPU quantities, expert installation, and scale-as-demand-grows. OPEX consumption models for predictable spend across hardware generations.

cudocompute.com
3Dedicated AI clusters — single-tenant GPU environments
ModelOtherBilling cadenceMulti-year contract
Notes

Isolated resources, defined operating boundaries, and predictable performance for production AI workloads. Deployment begins at 128 GPUs, extending to environments of up to 40,000 GPUs.

cudocompute.com
GTM typeB2B
B2B
Offering typeServices
Services
Core offering1 text field

CUDO Compute designs, commissions, and operates dedicated NVIDIA GPU clusters for enterprise AI training and inference workloads. The full-lifecycle offering covers site selection, power provisioning, hardware procurement through OEM channels (Dell, Lenovo, Supermicro, HPE), cluster deployment with NVIDIA reference-aligned architectures, and 24/7 operations across ISO 27001-certified facilities in North America, Europe, UK, and MENA. Deployments begin at 128 GPUs and scale to environments of up to 40,000 GPUs.

Differentiator
Functional benefit
Problem solved
Quantifiable outcome1 of 4 values shown
  • 4,000+ GPU cluster deployed across North America, Europe, and the Middle East in approximately two months from contract to production acceptance
+3 more records
Product overview1 text field

Cudo Compute is an AI infrastructure company that designs, commissions, and operates production GPU clusters for enterprise AI workloads. The portfolio spans multiple GPU generations: Hopper (H100, H200), Blackwell (B100, B200, B300, GB200 NVL72, GB300 NVL72), and upcoming Vera Rubin (VR200). Core offerings include GPU Cluster Services (bare metal dedicated clusters), AI Factories (industrial-scale turnkey infrastructure), AI Infrastructure Managed Services (full lifecycle operations), and Enterprise AI Solutions (sovereign-ready multi-region deployments). All products are built on NVIDIA architectures with ISO 27001 and SOC 2-aligned security, deployed across North America, Europe, UK, and MENA. Cudo also publishes the 'Land. Power, Compute.' industry report covering infrastructure constraints in AI deployment.

Product and service13 records
1GPU Cluster Services
CategoryManaged GPU Infrastructure
Description

Dedicated NVIDIA GPU clusters (H100, H200, B200, B300, GB200 NVL72, GB300 NVL72) for AI training, inference, and HPC workloads, deployed and operated by CUDO with 24/7 monitoring, firmware management, and NVIDIA escalation paths. Targets enterprises and government entities requiring clusters from 128 GPUs to 40,000+ GPUs.

2AI Factories
CategoryManaged AI Infrastructure
Description

Industrial-scale AI infrastructure designed, built, and operated for production AI workloads. Combines power-first site selection, high-density GPU deployment, and end-to-end operational management under a single accountable model.

3AI Infrastructure Managed Services
CategoryManaged AI Infrastructure
Description

Full-lifecycle AI infrastructure management from site selection through commissioning and 24/7 operations. Covers power provisioning, cooling, networking, storage, and cluster lifecycle including patching and firmware management.

4Enterprise AI Solutions
CategorySovereign AI Infrastructure
Description

Dedicated, managed AI environments for organisations transitioning from pilot to production. Includes sovereign-ready infrastructure with data residency, compliance controls, and multi-region deployment across ISO 27001 and SOC 2-aligned facilities.

5NVIDIA HGX B200
CategoryGPU Compute Product
Description

8-GPU Blackwell node delivering 3X faster training and 15X faster inference than H100, with 192 GB HBM3e per GPU. Designed for frontier model training, production inference at scale, HPC, and sovereign AI deployments.

6NVIDIA HGX B300
CategoryGPU Compute Product
Description

8-GPU Blackwell Ultra node with over 100 PFLOPS dense FP4, up to 288 GB HBM3e per GPU. Built for AI reasoning and large model training at node scale.

7NVIDIA GB200 NVL72
CategoryGPU Compute Product
Description

Liquid-cooled rack-scale system with 72 Blackwell GPUs and 36 Grace CPUs in a single NVLink domain. Delivers 30X faster real-time LLM inference for trillion-parameter models with up to 13.5 TB HBM3e.

8NVIDIA GB300 NVL72
CategoryGPU Compute Product
Description

72-GPU Blackwell Ultra rack-scale system delivering over 1,000 PFLOPS dense FP4 and 20 TB HBM3e. Up to 10X lower inference latency and 5X higher throughput per megawatt versus Hopper for AI reasoning, large-scale training, and agentic AI workloads.

9NVIDIA H100
CategoryGPU Compute Product
Description

Hopper-generation GPU available in PCIe and SXM form factors. 640 GB total HBM2e across 8 GPUs. Supports AI inference, deep learning, and HPC workloads on mature, widely available hardware.

10NVIDIA H200
CategoryGPU Compute Product
Description

Hopper-generation GPU with 1.1 TB total HBM3e (141 GB per GPU). Accelerates AI training and inference on larger models with enhanced memory bandwidth versus H100.

11NVIDIA B100
CategoryGPU Compute Product
Description

Blackwell-architecture GPU delivering up to 1.5 TB total HBM3e and 112 PFLOPS FP8 tensor performance. Accelerates trillion-parameter LLM inference and supports deep learning and HPC workloads.

12NVIDIA Vera Rubin (VR200)
CategoryGPU Compute Product
Description

Next-generation NVIDIA platform built from six co-designed chips (Rubin GPU, Vera CPU, NVLink 6, ConnectX-9, BlueField-4, Spectrum-6). Up to 3.5X more compute and 2.8X more memory bandwidth per GPU versus Blackwell B200, with CUDO preparing managed Vera Rubin clusters for H2 2026.

13Bare Metal GPU Service
CategoryGPU Compute Product
Description

Fully accessible dedicated GPU clusters providing physical machine control with no shared instances or virtual partitions. Includes renewable energy power, no noisy neighbours, NVMe SSD storage, SpectrumX local networking, and 300 Gbps external connectivity.

Scale indicator10 records

Each record includes

Type, Value, Description, Source

Partnership4 partners
Strategic tierFlagshipTypeStrategic or Co-development PartnerAnnounced on2025-12-04
Description

Singularity Compute (for-profit infrastructure arm of SingularityNET) launched its first enterprise-grade NVIDIA GPU cluster in Sweden in partnership with Conapto. The cluster is managed and operated by CUDO and underpins ASI:Cloud, providing scalable AI inference via OpenAI-compatible APIs for enterprises and ASI Alliance partners. Phase I launched with early customer onboarding, additional hardware and new locations planned.

Strategic tierCoreTypeStrategic or Co-development Partner
Description

Swedish data centre operator partnering with Singularity Compute and CUDO to host GPU clusters at a sustainable facility in Sweden. The facility hosts SingularityNET's ASI:Cloud underpinned by CUDO-operated infrastructure. Stefan Nilsson, COO of Conapto, noted alignment on operational excellence, customer experience, and transparent partnerships built on trust.

Strategic tierFlagshipTypeTechnology or Integration
Description

As an NVIDIA Preferred Partner, CUDO deploys platforms aligned to NVIDIA B200, B300, and GB300 designs, ensuring architecture integrity, supply certainty, and production-grade stability. Direct hardware access through established OEM channels (Dell, Lenovo, Supermicro, HPE). NVIDIA reference-aligned cluster architectures covering InfiniBand fabrics, high-performance storage, power, cooling, and rack layout.

Strategic tierCoreTypeStrategic or Co-development Partner
Description

Telegram's Cocoon AI decentralised privacy-preserving AI network is powered by GPU infrastructure deployed by AlphaTON Capital and operated through CUDO Compute's marketplace. AlphaTON Capital structured GPU cluster investment specifically to support Telegram's Cocoon AI and generate revenue through external GPU rentals via CUDO's platform.

Recent move6 records

Each record includes

Date, Type, Title, Description, Source

Expansion highlight6 records

Each record includes

Type, Description

Peers10 records
TypeBroad incumbent
Description

NVIDIA's own DGX Cloud delivers dedicated NVIDIA GPU clusters as a service via partners like CoreWeave and Equinix. It competes for the same enterprise AI workloads as CUDO but from the hardware vendor itself, with broader NVIDIA portfolio integration.

TypeRegional player
Description

OVHcloud is a European-headquartered cloud provider offering H100 and earlier-generation GPU instances with strong data residency positioning. Comparable to CUDO's European sovereign and regulated AI focus, though with broader cloud services and weaker NVIDIA Preferred Partner positioning.

TypeDirect peer
Description

CoreWeave is a specialist GPU cloud provider built on NVIDIA hardware, offering bare-metal and virtualized GPU compute to AI labs and enterprises. It is the most direct competitor to CUDO Compute in dedicated NVIDIA GPU cluster services for training and inference.

TypeDirect peer
Description

Lambda provides GPU cloud instances and on-premise GPU clusters (HGX H100, B200) for AI training and inference, with similar enterprise customer targeting and NVIDIA-centric stack. Comparable to CUDO's cluster and managed services offerings.

TypeBroad incumbent
Description

Azure provides ND H100 v5 and Blackwell-based GPU virtual machines for AI training and inference, integrated with Azure AI services. Hyperscaler breadth and OpenAI partnership make it a broad incumbent competing for the same enterprise cluster deals as CUDO.

TypeDirect peer
Description

Crusoe operates large-scale, power-first AI cloud infrastructure sited near stranded or renewable energy. Its strategy of securing cheap, abundant power for GPU clusters mirrors CUDO's land-power-compute thesis and addresses similar enterprise AI workloads.

TypeDirect peer
Description

Nebius is an AI infrastructure provider operating full-stack GPU clusters across multiple geographies, with emphasis on NVIDIA hardware and enterprise AI customers. Comparable in vertical integration from data center to GPU cloud services.

TypeDirect peer
Description

Together AI runs an AI cloud platform on top of large-scale NVIDIA GPU clusters, serving frontier model developers and enterprises with inference and training. Overlapping customer base and GPU-as-a-service delivery model make it a close comparable to CUDO.

TypeBroad incumbent
Description

AWS offers H100 and Blackwell GPU instances via EC2 P5 and emerging P6 families, alongside Bedrock, SageMaker, and global data center footprint. As a hyperscaler, AWS competes with CUDO for enterprise AI workloads but with broader services and scale.

TypeBroad incumbent
Description

Google Cloud's A3 and A4 instances offer H100 and Blackwell GPUs tightly integrated with Vertex AI and Google's networking stack. As a hyperscaler, Google is a broad incumbent competitor for dedicated enterprise AI cluster deployments.

Market position
Strengths5 records

Each record includes

Headline, Details, Source

Weaknesses5 records

Each record includes

Headline, Details, Source

Competitive moat5 records

Each record includes

Type, Details

Key risks6 records

Each record includes

Headline, Details, Source

Key highlights7 records

Each record includes

Headline, Details, Source

Customer concentration

Classification, Details

Named customers2 records

Each record includes

Name, Industry, Type, Use case, Source, UUID

Segment3 records

Each record includes

Title, Type, Primary, Description, Pain point addressed, Use case, Source

Ideal customer profile3 records

Each record includes

Profile, Firmographic size, Sales motion, Sales cycle length, Buying structure, Purchase trigger, Buyer persona, Geography, Industry vertical, Primary use case, Description, Pain points, Evidence proof points, Target buyer

Technology focused
Yes
API detail
Has APIbool
No

Docs URL, Description

Integration10 records

Each record includes

Title, Type, Description, Source

AI capability6 records

Each record includes

Type, Description, Source

AI maturity
App detail

Has app

Feature5 records

Each record includes

Title, Differentiator, Description, Source

Core technology
Revenue estimate
Valuation estimate
Number of profiles
Profiles7 records

Each record includes

Name, Designation, Designation category, Overview, Profile commentary, Source

No data
Compliance9 records

Each record includes

Name, Class, Description

Funding overview

Funding stage, Last funding date, Total funding USD

Funding rounds

Each record includes

Round, Amount USD, Date, Pre money valuation, Total investors, Investors, News

Investors

Each record includes

Name, Type, Date of entry, Rounds participated, Website

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Each record includes

Name, Acquisition type, Announced date, Completed date, Status, Website, News

Investment

Each record includes

Name, Round, Announced date, Lead investor, Website, News

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Cudo Compute

GPU Cloud Infrastructurecudocompute.com

Cudo Compute is a UK-based AI infrastructure company that designs, commissions, and operates production-scale NVIDIA GPU clusters for enterprise, government, and AI-first customers across North America, Europe, UK, and MENA, leveraging NVIDIA Preferred Partner supply chain access and an integrated land-power-compute delivery model.

What Cudo Compute does

Cudo Compute (legal entity: Cudo Ventures Limited) is a UK-based, privately held AI infrastructure company that designs, commissions, and operates enterprise-grade NVIDIA GPU clusters for production AI training and inference workloads. The company addresses end-to-end deployment constraints — land, power, and compute — by integrating site selection, hardware procurement through NVIDIA Preferred Partner channels, NVIDIA reference-aligned cluster design covering InfiniBand fabrics, high-performance storage (VAST, WEKA, DDN, NetApp), and direct liquid cooling for GB200/GB300 NVL72 rack-scale systems, with 24/7 SRE-led operations under a single accountable model. The product portfolio spans Hopper (H100, H200), Blackwell (B100, B200, B300, GB200 NVL72, GB300 NVL72), and pre-launch Vera Rubin (VR200) hardware, delivered in ISO 27001-certified data centres across North America, Europe, the UK, and MENA.

The business generates revenue through three streams: managed GPU cluster services on multi-year contracts, subscription or usage-based cloud GPU compute with OPEX consumption models compatible with bare metal, enterprise, and GPU-as-a-service structures, and one-time professional services for deployment, commissioning, and benchmarking. Customer segments include large enterprises requiring dedicated clusters from 128 to 40,000+ GPUs, AI-first companies and frontier model developers prioritising access to latest-generation hardware, and government and sovereign AI initiatives requiring jurisdiction-specific infrastructure with data residency, GDPR, CCPA, and FedRAMP-aligned controls. Commercial go-to-market is exclusively enterprise field sales with quote-based pricing, no public list rates, and primary intake through website enquiry forms targeting multi-year contracts.

The company has secured 250MW+ of contracted power capacity by end of 2026 with a 750MW+ target by end of 2027 and a multi-GW pipeline including exclusive European sites with power commitments and grid underwriting. Founder and CEO Matt Hawkins, who previously founded C4L, leads a senior team of seven executives including CTO Tim Dyce (ex-CERN and European Bioinformatics Institute), CFO David Bell, CSO Mark Denney (former CIO of HMRC and Barclays), and COO Lee Woodham with an explicit Series B mandate. No institutional funding rounds, revenue figures, or valuation disclosures are available.

Cudo Compute firmographics

Firmographics
Name
Cudo Compute
Legal name
Cudo Ventures Limited
Website
https://cudocompute.com
Company type
Private
Founded year
2021
Operating status
Operating
Headcount range
11–50 employees
Short description
Cudo Compute is a UK-based AI infrastructure company that designs, commissions, and operates production-scale NVIDIA GPU clusters for enterprise, government, and AI-first customers across North America, Europe, UK, and MENA, leveraging NVIDIA Preferred Partner supply chain access and an integrated land-power-compute delivery model.
Ownership category
akta.pro rank

Cudo Compute industry classification

Industry
Product category
GPU Cloud Infrastructure
NAICS
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821), Computer Systems Design and Related Services (5415)
SIC
Electronic Computers (3571), Services-Computer Integrated Systems Design (7373)
akta.pro primary industry
AI Compute Cloud & GPU-as-a-Service (HDAAAAAK)
akta.pro secondary industries
GPU/Accelerator Compute Servers (HDABADAC), GPU-Accelerated & AI Training/Inference Servers (HDACABAG), GPU-Accelerated HPC Systems (HDACAOAC)

Keywords

  • Gpu cloud infrastructure
  • Ai infrastructure services
  • Bare metal gpu
  • Enterprise ai compute
  • Data center operations

Where Cudo Compute is headquartered

Location

Headquarters

HQ city
Bournemouth
HQ country
United Kingdom
HQ region
Europe

Offices3 records

Markets served

Cudo Compute business model

Business model
GTM type
B2B
Offering type
Services
Cost components
Infrastructure, Supply Chain, Technology or R&D, Personnel, Operations, Marketing or Sales

Revenue model

  1. Managed GPU cluster services: Dedicated bare-metal GPU clusters managed by CUDO from deployment through 24/7 operations. Includes cluster commissioning, monitoring, firmware lifecycle management, and L3 support. Revenue recognised as a recurring managed services contract.
  2. Cloud GPU compute (subscription / usage-based): GPU compute access via subscription or consumption-based models. OPEX consumption models for predictable spend across hardware generations. Compatible with bare metal, enterprise, and GPU-as-a-service commercial structures.
  3. End-to-end deployment and commissioning services: Deployment services covering site readiness assessment, rack deployment, cooling infrastructure, networking, OS and driver provisioning, and cluster benchmarking before handoff. One-time professional services revenue at deployment.

Pricing tiers

ModelBillingPrice
OtherMulti-year contractBare metal GPU clusters — dedicated physical GPUs with no contention
SubscriptionAnnualEnterprise GPU infrastructure — custom cluster and colocation solutions
OtherMulti-year contractDedicated AI clusters — single-tenant GPU environments

Go-to-market motion2 records

Distribution channels1 record

Marketing channels6 records

Cudo Compute product offering

Product offering

Core offering

CUDO Compute designs, commissions, and operates dedicated NVIDIA GPU clusters for enterprise AI training and inference workloads. The full-lifecycle offering covers site selection, power provisioning, hardware procurement through OEM channels (Dell, Lenovo, Supermicro, HPE), cluster deployment with NVIDIA reference-aligned architectures, and 24/7 operations across ISO 27001-certified facilities in North America, Europe, UK, and MENA. Deployments begin at 128 GPUs and scale to environments of up to 40,000 GPUs.

Product overview

Cudo Compute is an AI infrastructure company that designs, commissions, and operates production GPU clusters for enterprise AI workloads. The portfolio spans multiple GPU generations: Hopper (H100, H200), Blackwell (B100, B200, B300, GB200 NVL72, GB300 NVL72), and upcoming Vera Rubin (VR200). Core offerings include GPU Cluster Services (bare metal dedicated clusters), AI Factories (industrial-scale turnkey infrastructure), AI Infrastructure Managed Services (full lifecycle operations), and Enterprise AI Solutions (sovereign-ready multi-region deployments). All products are built on NVIDIA architectures with ISO 27001 and SOC 2-aligned security, deployed across North America, Europe, UK, and MENA. Cudo also publishes the 'Land. Power, Compute.' industry report covering infrastructure constraints in AI deployment.

Differentiator

Problem solved

Functional benefit

Products and services

  • GPU Cluster Services Dedicated NVIDIA GPU clusters (H100, H200, B200, B300, GB200 NVL72, GB300 NVL72) for AI training, inference, and HPC workloads, deployed and operated by CUDO with 24/7 monitoring, firmware management, and NVIDIA escalation paths. Targets enterprises and government entities requiring clusters from 128 GPUs to 40,000+ GPUs.
  • AI Factories Industrial-scale AI infrastructure designed, built, and operated for production AI workloads. Combines power-first site selection, high-density GPU deployment, and end-to-end operational management under a single accountable model.
  • AI Infrastructure Managed Services Full-lifecycle AI infrastructure management from site selection through commissioning and 24/7 operations. Covers power provisioning, cooling, networking, storage, and cluster lifecycle including patching and firmware management.
  • Enterprise AI Solutions Dedicated, managed AI environments for organisations transitioning from pilot to production. Includes sovereign-ready infrastructure with data residency, compliance controls, and multi-region deployment across ISO 27001 and SOC 2-aligned facilities.
  • NVIDIA HGX B200 8-GPU Blackwell node delivering 3X faster training and 15X faster inference than H100, with 192 GB HBM3e per GPU. Designed for frontier model training, production inference at scale, HPC, and sovereign AI deployments.
  • NVIDIA HGX B300 8-GPU Blackwell Ultra node with over 100 PFLOPS dense FP4, up to 288 GB HBM3e per GPU. Built for AI reasoning and large model training at node scale.
  • NVIDIA GB200 NVL72 Liquid-cooled rack-scale system with 72 Blackwell GPUs and 36 Grace CPUs in a single NVLink domain. Delivers 30X faster real-time LLM inference for trillion-parameter models with up to 13.5 TB HBM3e.
  • NVIDIA GB300 NVL72 72-GPU Blackwell Ultra rack-scale system delivering over 1,000 PFLOPS dense FP4 and 20 TB HBM3e. Up to 10X lower inference latency and 5X higher throughput per megawatt versus Hopper for AI reasoning, large-scale training, and agentic AI workloads.
  • NVIDIA H100 Hopper-generation GPU available in PCIe and SXM form factors. 640 GB total HBM2e across 8 GPUs. Supports AI inference, deep learning, and HPC workloads on mature, widely available hardware.
  • NVIDIA H200 Hopper-generation GPU with 1.1 TB total HBM3e (141 GB per GPU). Accelerates AI training and inference on larger models with enhanced memory bandwidth versus H100.
  • NVIDIA B100 Blackwell-architecture GPU delivering up to 1.5 TB total HBM3e and 112 PFLOPS FP8 tensor performance. Accelerates trillion-parameter LLM inference and supports deep learning and HPC workloads.
  • NVIDIA Vera Rubin (VR200) Next-generation NVIDIA platform built from six co-designed chips (Rubin GPU, Vera CPU, NVLink 6, ConnectX-9, BlueField-4, Spectrum-6). Up to 3.5X more compute and 2.8X more memory bandwidth per GPU versus Blackwell B200, with CUDO preparing managed Vera Rubin clusters for H2 2026.
  • Bare Metal GPU Service Fully accessible dedicated GPU clusters providing physical machine control with no shared instances or virtual partitions. Includes renewable energy power, no noisy neighbours, NVMe SSD storage, SpectrumX local networking, and 300 Gbps external connectivity.

Quantifiable outcome

  • 4,000+ GPU cluster deployed across North America, Europe, and the Middle East in approximately two months from contract to production acceptance
  • +3 more outcomes

Companies that use Cudo Compute

Customer profile

Named customers2 records

Segments3 records

Ideal customer profiles3 records

Cudo Compute technology and API

Technology

Technology focussed Yes

API detail

Has API
No
API docs
API detail

Core technology

AI maturity

App detail

Integration10 records

AI capability6 records

Feature5 records

Cudo Compute partnerships and signals

Strategic signal

Partnerships

Four partnerships are on record, tiered flagship and core.

  • SingularityNET / Singularity ComputeflagshipStrategic or Co-development Partner · 4 December 2025Singularity Compute (for-profit infrastructure arm of SingularityNET) launched its first enterprise-grade NVIDIA GPU cluster in Sweden in partnership with Conapto. The cluster is managed and operated by CUDO and underpins ASI:Cloud, providing scalable AI inference via OpenAI-compatible APIs for enterprises and ASI Alliance partners. Phase I launched with early customer onboarding, additional hardware and new locations planned.
  • ConaptocoreStrategic or Co-development PartnerSwedish data centre operator partnering with Singularity Compute and CUDO to host GPU clusters at a sustainable facility in Sweden. The facility hosts SingularityNET's ASI:Cloud underpinned by CUDO-operated infrastructure. Stefan Nilsson, COO of Conapto, noted alignment on operational excellence, customer experience, and transparent partnerships built on trust.
  • NVIDIAflagshipTechnology or IntegrationAs an NVIDIA Preferred Partner, CUDO deploys platforms aligned to NVIDIA B200, B300, and GB300 designs, ensuring architecture integrity, supply certainty, and production-grade stability. Direct hardware access through established OEM channels (Dell, Lenovo, Supermicro, HPE). NVIDIA reference-aligned cluster architectures covering InfiniBand fabrics, high-performance storage, power, cooling, and rack layout.
  • TelegramcoreStrategic or Co-development PartnerTelegram's Cocoon AI decentralised privacy-preserving AI network is powered by GPU infrastructure deployed by AlphaTON Capital and operated through CUDO Compute's marketplace. AlphaTON Capital structured GPU cluster investment specifically to support Telegram's Cocoon AI and generate revenue through external GPU rentals via CUDO's platform.

Scale indicators10 records

Recent moves6 records

Expansion highlights6 records

Cudo Compute competitors and assessment

Company assessment

Broad incumbents

  • NVIDIA DGX Cloud: NVIDIA's own DGX Cloud delivers dedicated NVIDIA GPU clusters as a service via partners like CoreWeave and Equinix. It competes for the same enterprise AI workloads as CUDO but from the hardware vendor itself, with broader NVIDIA portfolio integration.
  • Microsoft Azure (ND H100 v5): Azure provides ND H100 v5 and Blackwell-based GPU virtual machines for AI training and inference, integrated with Azure AI services. Hyperscaler breadth and OpenAI partnership make it a broad incumbent competing for the same enterprise cluster deals as CUDO.
  • Amazon Web Services (EC2 P5/P6): AWS offers H100 and Blackwell GPU instances via EC2 P5 and emerging P6 families, alongside Bedrock, SageMaker, and global data center footprint. As a hyperscaler, AWS competes with CUDO for enterprise AI workloads but with broader services and scale.
  • Google Cloud (A3/A4 instances): Google Cloud's A3 and A4 instances offer H100 and Blackwell GPUs tightly integrated with Vertex AI and Google's networking stack. As a hyperscaler, Google is a broad incumbent competitor for dedicated enterprise AI cluster deployments.

Regional players

  • OVHcloud: OVHcloud is a European-headquartered cloud provider offering H100 and earlier-generation GPU instances with strong data residency positioning. Comparable to CUDO's European sovereign and regulated AI focus, though with broader cloud services and weaker NVIDIA Preferred Partner positioning.

Direct peers

  • CoreWeave: CoreWeave is a specialist GPU cloud provider built on NVIDIA hardware, offering bare-metal and virtualized GPU compute to AI labs and enterprises. It is the most direct competitor to CUDO Compute in dedicated NVIDIA GPU cluster services for training and inference.
  • Lambda Labs: Lambda provides GPU cloud instances and on-premise GPU clusters (HGX H100, B200) for AI training and inference, with similar enterprise customer targeting and NVIDIA-centric stack. Comparable to CUDO's cluster and managed services offerings.
  • Crusoe Energy: Crusoe operates large-scale, power-first AI cloud infrastructure sited near stranded or renewable energy. Its strategy of securing cheap, abundant power for GPU clusters mirrors CUDO's land-power-compute thesis and addresses similar enterprise AI workloads.
  • Nebius: Nebius is an AI infrastructure provider operating full-stack GPU clusters across multiple geographies, with emphasis on NVIDIA hardware and enterprise AI customers. Comparable in vertical integration from data center to GPU cloud services.
  • Together AI: Together AI runs an AI cloud platform on top of large-scale NVIDIA GPU clusters, serving frontier model developers and enterprises with inference and training. Overlapping customer base and GPU-as-a-service delivery model make it a close comparable to CUDO.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks6 records

Key highlights7 records

Customer concentration

Cudo Compute social profiles

Digital presence

Cudo Compute compliance and trust

Trust signal

Compliance9 records

Cudo Compute financial estimates

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Valuation estimate

Cudo Compute leadership team

Management profile

Number of profiles

Profiles7 records

Cudo Compute funding detail

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Funding overview

Funding rounds

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Funding detail is available on the Subscription and Enterprise plan.Contact sales →

Cudo Compute M&A and investment

M&A and investment

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M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Cudo Compute

What does Cudo Compute do?

CUDO Compute designs, commissions, and operates dedicated NVIDIA GPU clusters for enterprise AI training and inference workloads. The full-lifecycle offering covers site selection, power provisioning, hardware procurement through OEM channels (Dell, Lenovo, Supermicro, HPE), cluster deployment with NVIDIA reference-aligned architectures, and 24/7 operations across ISO 27001-certified facilities in North America, Europe, UK, and MENA. Deployments begin at 128 GPUs and scale to environments of up to 40,000 GPUs.

Is Cudo Compute a public or private company?

Cudo Compute is a private company. It is classified as founder individual operated bootstrapped and is currently operating.

When was Cudo Compute founded?

Cudo Compute was founded in 2021. It employs 11 to 50 people.

Where is Cudo Compute based?

Cudo Compute is headquartered in Bournemouth, United Kingdom, in the Europe region.

How does Cudo Compute make money?

Three revenue lines are on record. Managed GPU cluster services are the primary driver. The others are cloud GPU compute (subscription / usage-based) and end-to-end deployment and commissioning services.

Who are Cudo Compute's main competitors?

Broad incumbents on record are NVIDIA DGX Cloud, Microsoft Azure (ND H100 v5), Amazon Web Services (EC2 P5/P6) and Google Cloud (A3/A4 instances). OVHcloud is listed as a regional player. Direct peers are CoreWeave, Lambda Labs, Crusoe Energy, Nebius and Together AI.

Does Cudo Compute have an API?

No public API is recorded for Cudo Compute.

What industry is Cudo Compute in?

Cudo Compute's product category is GPU Cloud Infrastructure. Its primary akta.pro industry code is HDAAAAAK, AI Compute Cloud & GPU-as-a-Service, with a secondary code of HDABADAC, GPU/Accelerator Compute Servers. Its NAICS code is 51821 and its SIC code is 3571.

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Live signals
TechRadarThe five things governments must get right to attract AI investmentThis opinion piece by CUDO Compute CEO Matt Hawkins argues that governments seeking AI investment must shift focus from abstract policy ambitions to physical infrastructure requirements—specifically energy, compute access, and deployment speed.TechRadarUK’s sky-high electricity costs are quietly pushing AI firms overseas as cheaper markets lure away critical workloads and future innovationHigh electricity costs in the UK are causing AI firms to relocate workloads overseas, with 20% of UK firms having already moved workloads out and 72% of UK respondents identifying the United States as the most attractive market for new AI cluster capacity. A survey of over 700 senior AI decision-makers by CUDO Compute found that a third of UK organizations say energy costs are limiting their ability to scale AI operations, and cost and performance outweigh sovereignty considerations for 43% of organizations when deciding where to deploy AI tools. The research highlights a disconnect between the UK's AI sovereignty ambitions and the lack of power infrastructure to support them, with the US already benefiting from the UK's inaction as more AI workloads migrate overseas each week.The RegisterUK firms to deploy AI projects abroad as energy costs riseAccording to a report by rent-a-GPU firm CUDO Compute, one in five UK firms have already moved AI workloads abroad due to high energy costs, with a third of UK organizations saying energy costs are limiting their ability to scale AI infrastructure. The UK has some of the highest electricity prices in the developed world, and 32 percent of AI-first companies are considering relocating workloads overseas—a direct threat to the government's ambitions to make Britain a global AI leader. The US ranks as the most attractive location for new AI deployment, followed by India and Eastern Europe, as organizations increasingly prioritize proximity to available power over proximity to end users.CudocomputeNVIDIA GPU benchmark: H100 vs A100 vs L40SCUDO Compute conducted a controlled benchmark comparing three NVIDIA GPUs—H100 SXM, A100 PCIe, and L40S—under identical software stacks using an end-to-end BERT-base masked-LM fine-tune workload. The H100 delivered 12x faster training throughput and 7x faster inference versus the A100, achieving the lowest cost-per-token at $0.88 per 10M training tokens and $0.026 per 1M inference tokens, while the L40S offered the most cost-effective inference at $0.023 per 1M tokens. The study provides a workload-based GPU selection playbook for ML engineers to optimize cost-efficiency on CUDO Compute's cloud platform.GlobeNewswireAlphaTON Capital Announces $82.5 Million Strategic GPU Infrastructure Investment to Power Privacy-First Decentralized AI after Successful Pilot Launch of Telegram’s Cocoon AIAlphaTON Capital Corp announced agreements to acquire and deploy a 1,000+ Nvidia B200 GPU high-performance compute cluster valued at approximately $68 million, representing a total project capitalization of $82.5 million financed through $30 million in equity and $52.5 million in debt from Vertical Data. The GPU cluster will power Telegram's Cocoon AI decentralized privacy-preserving artificial intelligence network while generating revenue through dedicated compute services and external GPU rentals via CUDO Compute's marketplace, with a projected IRR of 59.7% and 5x equity multiple over five years. AlphaTON successfully launched a Cocoon AI pilot on November 25, 2025, and expects hardware delivery and soft launch in Q1 2026, with full deployment and potential cluster expansion in Q2 2026.CudocomputeEconomics of renting cloud GPUsThe article analyzes the cost-effectiveness of renting cloud GPUs versus on-premise infrastructure, highlighting that cloud providers like CUDO Compute offer significantly lower hourly rates for high-end NVIDIA H100 GPUs compared to competitors AWS and Azure. It details pricing structures including on-demand, reserved, and bare metal options, demonstrating substantial savings for AI model training workloads when utilizing specific geographic locations or spot instances.CudocomputeTop 10 cloud GPU platforms for deep learning in 2024The article ranks the top ten cloud GPU platforms for deep learning in 2024, evaluating providers such as CUDO Compute, AWS, Google Cloud Platform, and Microsoft Azure based on criteria including hardware availability, pricing structures, and ease of use. The analysis highlights CUDO Compute as a cost-effective option for budget-conscious users while identifying major hyperscalers like AWS and Azure as suitable for large-scale enterprise workloads due to their extensive infrastructure and support ecosystems.TecheratiCato Digital and Cudo Compute partner for sustainable, high-performance cloud solutionsCato Digital and Cudo Compute announced a strategic alliance to offer sustainable, on-demand cloud infrastructure. Cato Digital repurposes hardware and runs energy-efficient data centres, while Cudo Compute's marketplace makes this infrastructure accessible. The partnership is expected to attract video rendering and AI inference communities.PressatCato Digital and Cudo Compute Announce Partnership for High-Performance, Low-Cost Cloud SolutionsCato Digital and Cudo Compute announced a partnership to offer sustainable, low-cost cloud infrastructure using repurposed hardware. The collaboration combines Cato Digital's circular economy data centers with Cudo Compute's marketplace, targeting video rendering and AI inference communities. The partnership aims to provide a cost-effective alternative to traditional cloud services.CudocomputeBest hardware specifications for animation.An article by Emmanuel Ohiri outlines the hardware requirements for animation, covering CPU, GPU, RAM and storage, recommending at least a quad-core processor, 4GB of VRAM, 16GB of RAM and 1TB of SSD storage. It then promotes CUDO Compute, a cloud platform offering remote access to high-end GPUs, scalable resources, collaboration, and secure storage.