Private AI Cloud: The Infrastructure You Need for Enterprise-Scale AI

Most businesses begin their AI journey on shared or public cloud platforms. They’re flexible, easy to access and require no upfront investment. However, as workloads become more advanced, sensitive and compute-intensive, you start seeing the cracks in shared models.

If you’re fine-tuning a large language model on proprietary data or developing an AI application that could define your next decade, is a public cloud (where resources are shared and unpredictable) good enough?

For enterprise-grade AI workloads, the answer is often no.

Private AI Cloud offers a secure platform where you can run sensitive and performance-hungry workloads without compromise. If your AI workload is too sensitive or IP-intensive to run in a shared space, it’s time to consider a Private AI Cloud.

Who Needs Private AI Infrastructure for Enterprise-Scale Workloads?

What kind of workloads demand a private AI infrastructure? Typically, they’re high-value, high-risk or performance-critical projects. You can say the ones where latency, data control and security are non-negotiable. When data privacy, compliance, IP protection and latency cannot be compromised, public cloud AI often falls short. That's where Private AI Cloud steps in.

Here are four common enterprise use cases that benefit most from Private AI Cloud deployments:

1. Processing Regulated Financial Data for Risk & Compliance

Large banks and financial institutions regularly run high-performance computing (HPC) simulations to perform risk modelling, credit stress testing and capital adequacy forecasting under regulations like FCA/PRA rules or other specific to each region/country. These simulations process trading books, exposure data and customer financial records, all of which are subject to strict compliance and data sovereignty rules.

2. Fraud Detection and AML on Customer Transactions

Financial fraud detection and anti-money laundering (AML) systems increasingly rely on AI to scan billions of transactions for anomalies in real time. These workloads involve sensitive personal and financial information (PII) such as account activity, payment histories and customer behaviour.

3. AI-Powered Customer Service on Confidential Interactions

GenAI-driven assistants are being used in customer service in finance, healthcare and telecoms. Whether summarising chat logs, personalising financial advice or triaging healthcare queries, these LLMs often rely on real-time access to customer data.

Enterprises are increasingly fine-tuning LLMs on internal datasets that contain sensitive communications and behavioural insights. Hosting these workloads in a Private AI Cloud ensures they remain protected from third-party APIs or data-sharing risks, while enabling fast, secure inference and customisation.

4. Training AI Models on Healthcare and Genomics Data

In healthcare, AI is used for everything from analysing radiology images to personalising treatment based on genomic sequences. These use cases demand massive compute but they also deal with some of the most tightly regulated data such as patient records and clinical notes.

For instance, NHS guidelines in the UK require health data to be stored and processed within the UK or trusted environments. A Private AI Cloud enables research institutions, hospitals and AI medtech firms to comply with these mandates while training and deploying models on high-performance GPU infrastructure.

Why Choose a Private AI Cloud Over Public Infrastructure?

Private AI Cloud is a dedicated, high-performance GPU environment built for privacy, full isolation and compute-heavy AI workloads.

Let’s break down why private infrastructure is often a viable option for enterprise-grade AI workloads.

1. Privacy First

Your training datasets, inference models and application logic are imperative to your competitive edge. A shared infrastructure (even with encryption) could carry risk because full isolation is never guaranteed.

A Private AI Cloud ensures your data never crosses into shared spaces. From the GPUs to the tenants, everything is dedicated to you. That means no chance of accidental access, no side-channel vulnerabilities and full control over audit trails.

2. Performance Matters

AI training and inference not only rely on GPU power but also on network bandwidth, low-latency communication and high-throughput storage. On public clouds, you may face resource contention, scheduling delays or not-too-great performance due to shared workloads (the infamous “noisy neighbour” problem).

Private infrastructure eliminates these bottlenecks. You get exclusive access to your GPU Clusters for AI, guaranteed throughput and consistent I/O performance, so your workloads run as fast and predictably as possible.

3. Custom Configuration

You know this: AI is not a one-size-fits-all. Whether you're building a multi-node training pipeline, deploying an inference API or integrating model feedback loops into your app, your stack will look different.

Public cloud might force you into templated environments. Private AI Cloud gives you full control. You can define:

• Which GPU types to use (NVIDIA HGX H100, NVIDIA HGX H200 or other)
• Your preferred storage system (e.g., Object Storage, High-performance parallel file system)
• The exact networking you need (NVIDIA Quantum InfiniBand, Ethernet, etc.)
• Your container orchestration or MLOps tools

4. Regulatory Ease

Whether you're working under GDPR, HIPAA, ISO/IEC 27001 or other compliance frameworks, data residency and control are imperative. A Private AI Cloud hosted in compliant jurisdictions simplifies regulatory alignment. No shared tenancy, no cross-border data transfers, no vendor lock-in, just infrastructure you can audit, control and certify as needed.

What is NexGen Cloud’s Private AI Cloud?

NexGen Cloud’s Private AI Cloud is a fully dedicated, high-performance environment designed to meet the most stringent AI requirements for enterprises. It offers guaranteed hardware isolation, customisable infrastructure and sovereign-grade security, hosted entirely in Tier 3 data centres across Europe.

Here’s what you get with our Private AI Cloud deployment:

1. Enterprise-Grade GPU Clusters for AI

NexGen Cloud provides access to the most powerful GPUs for AI including NVIDIA HGX H100 and NVIDIA HGX H200. These clusters are designed specifically for deep learning, foundation model training and high-throughput inference at scale. If you're training a transformer model or deploying a retrieval-augmented generation pipeline, the compute power is there and fully yours.

2. Ultra-Fast Networking with NVIDIA Quantum InfiniBand

Networking is often a bottleneck in distributed training and inference. NexGen Cloud eliminates that with NVIDIA Quantum InfiniBand, delivering up to 400Gb/s speeds with extremely low latency across GPU nodes.

This ensures your model’s parallel training or inference workloads aren’t slowed down by data transfer delays. It’s ideal for multi-node LLM training and large-scale simulations.

3. High-Speed Data Storage 

Traditional storage systems struggle with AI’s need for constant, parallel data access. NexGen Cloud integrates high-speed data storage with GPUDirect Storage support. 

With GPUDirect support, data flows directly between storage and GPU memory, eliminating CPU bottlenecks and cutting latency. This makes it perfect for workloads like reinforcement learning, multimodal model training and fast inference pipelines.

4. Complete Isolation

Your infrastructure is completely separate from other tenants. That means no noisy neighbours, no metadata leakage and no risk of performance variation due to other workloads. It is your private GPU-powered environment.

5. Full Customisation

Need a specific GPU? Want to pre-install your MLOps stack or connect to an on-prem cluster? NexGen Cloud allows full control over your compute, network and storage configurations.

6. Secure Infrastructure

Our infrastructure meets the needs of organisations with strict data control requirements:

• Intrusion detection systems and firewalls to prevent unauthorised access
• Single-tenant deployment options for isolation and full control over your environment
• End-to-end encryption and role-based access controls
• Detailed audit logs and configurable access policies to support compliance with industry standards

Conclusion

AI at scale demands more than just compute power. It demands an environment that aligns with your privacy, performance and compliance needs. Shared cloud infrastructure can be a good start but it quickly falls short for workloads that are sensitive, high-value or mission-critical.

A Private AI Cloud bridges this gap, offering the security of on-prem with the scalability and performance of the cloud. And when it's time to deploy at scale, with total control and peace of mind, NexGen Cloud makes it not only possible but seamless. With fully isolated, GPU-accelerated infrastructure hosted in sovereign-grade European data centres, NexGen Cloud delivers everything you need to run enterprise AI workloads with confidence.

Build the Future of AI, Securely

Deploy sovereign-grade AI infrastructure with guaranteed hardware isolation, GPU-accelerated performance, and full compliance control tailored to your enterprise needs with NexGen Cloud’s Private AI Cloud.

FAQs

What is a Private AI Cloud?

Private AI Cloud is a dedicated, high-performance GPU environment built for privacy, full isolation and compute-heavy AI workloads.

Why choose a Private AI Cloud over a public cloud?

A Private AI Cloud offers exclusive GPU access, stronger data control, consistent performance, and compliance advantages for enterprise-grade AI deployments.

Who should use a Private AI Cloud?

Organisations fine-tuning models, hosting internal GenAI tools or running confidential IP-rich workloads can use the private AI Cloud.

What GPUs are available with NexGen’s Private AI Cloud?

NexGen Cloud offers NVIDIA HGX H100, NVIDIA HGX H200 and the upcoming NVIDIA Blackwell GB200 NVL72/36 clusters tailored for enterprise AI workloads.

How does NexGen ensure performance isolation?

Via our Private AI Cloud deployment, we ensure there is no shared tenancy and every resource, from GPUs to storage is dedicated to your workloads for consistent performance.

Does NexGen Cloud support high-speed networking?

Yes, NexGen Cloud offers GPU Clusters for AI that are optimised with advanced networking such as NVIDIA Quantum InfiniBand for ultra-low-latency, high-throughput communication across GPU nodes and storage systems.