Airon is built specifically for AI workloads that need dedicated capacity, further control, and predictable costs.

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Compared with hyperscalers:

• Dedicated, not shared: Airon provides compute capacity reserved for your organization, instead of shared infrastructure.
• More predictable performance: dedicated resources reduce slowdowns and variability for demanding AI workloads.
• More predictable costs: simple, linear pricing helps avoid complex billing and surprise charges.
• Built for AI: Airon’s data centers and infrastructure are purpose-built for AI workloads, not general-purpose computing

Compared with building and operating it yourself:

• No facilities or operations burden: you don’t need to buy equipment, house it, or run it yourself.
• Faster access to capacity: you avoid long lead times for purchasing, installation, and scaling.

Airon is used for running AI and data workloads that need high performance, strong security, and predictable costs.

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Common use cases include:

• Training AI models: building and improving models using large datasets.
• Running AI services (inference): using AI in day-to-day operations, such as automation and decision support.
• Data analysis and machine learning: analyzing large datasets to find patterns and improve decisions.
• Large-scale simulations: running compute-heavy simulations for planning, forecasting, or research.

Airon is a good fit when:

• AI workloads are too slow or too expensive in shared cloud environments.
• You need guaranteed capacity for critical projects.
• You require strong control, isolation, and oversight for sensitive work.

Airon solves the problem of running AI at scale when traditional cloud services become too unpredictable, too costly, or too hard to control for demanding workloads.

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Organizations often run into challenges such as:

• Unpredictable costs: complex cloud pricing and usage-based billing can make costs hard to forecast.
• Unstable performance: shared environments can create variability and slowdowns.
• Limited control: it can be difficult to guarantee capacity, oversight, and clear governance.
• Scaling barriers: moving from pilot to production can cause delays,procurement friction, or budget surprises.
• High security and compliance requirements: sensitive workloads require strong access control, auditing, and clear data handling.

Airon addresses these challenges by enabling:

• Guaranteed access to capacity when you need it.
• Predictable cost structure: simpler pricing that is easier to plan for.
• Stronger control and oversight: clear access control and auditability.
• Reliable performance and scalability: built for demanding AI workloads.

Yes. Airon only operates AI factories in the Nordics, allowing customers to keep workloads and data within the EU. Infrastructure is physically located in the region and designed to support European data sovereignty and regulatory requirements.

Airon manages the physical infrastructure, including data centers, GPUs, networking and hardware operations.

You manage your AI workloads, models and data. This gives you full control over how your AI is built, trained and deployed, while we ensure the infrastructure runs securely and reliably.

Airon provides dedicated GPU compute for AI. You get dedicated computing capacity for AI, hosted and operated by Airon, without needing to buy servers or run facilities yourself.

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Airon’s offer includes:

• Dedicated GPU capacity reserved for your organization.
• AI-purpose-built data centers in the Nordics (Sweden), operated by Airon.
• An user friendly platform for visibility and control, to manage access, usage, and resources.

Traditional cloud AI services are typically built on shared, multi-tenant infrastructure. Your workloads run alongside others, with resources dynamically allocated across customers. This can offer flexibility, but it may also lead to performance variability, less predictable costs and limited control over the underlying infrastructure.

Airon operates tailored AI factories. Your environment is physically and logically isolated, not shared with other tenants, while still giving you the operational flexibility to scale capacity as needs change. The result is predictable performance, clear cost structures and full control over how your AI is trained, deployed and run over time.

Fully dedicated means that the computing capacity you buy from Airon is reserved for your organization only. Your workloads do not compete with other customers for the same resources.

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Bare-metal means you run on the physical servers directly.

How this helps you:

• Predictable performance: no competition for capacity means no unexpected slowdowns due to other customers’ usage and no sudden performance fluctuations.
• Stronger isolation: dedicated hardware reduces cross-customer risk and supports sensitive workloads.
• Further control: you define access, usage rules, and governance for your environment.
• Clear accountability: it's easier to understand what is reserved for you and what you are paying for.