AI only delivers its full value when organisations can trust it with their most sensitive data. Yet regulatory requirements and high security standards often restrict the use of mainstream AI services. Banning AI does not help: employees may turn to private services instead (shadow AI). A sovereign AI infrastructure resolves this dilemma and opens up new opportunities, with predictable costs and the control you need over data, models and operations:
- Unlock sensitive data for AI: use AI in business-critical areas that were previously off-limits for data protection or security reasons.
- Avoid shadow AI and data silos: create a secure alternative to unauthorised AI services that brings together knowledge from different systems and makes modern AI part of employees’ everyday work.
- Stay strategically independent: reduce dependence on individual technology vendors and respond flexibly to changing conditions.
The building blocks of a sovereign AI infrastructure
What we offer: from architecture to concrete use cases
Architecture and model selection
We evaluate use cases, AI models, data sources, hardware and deployment options and develop an architecture that balances quality, performance, cost and sovereignty.
AI platform and infrastructure
Using proven blueprints, we build your sovereign AI platform to your requirements and integrate it into your existing data sources, systems and business processes.
AI applications
We develop applications your teams can use straight away, from secure chat and document search to copilots and agents, integrated into your systems and access permissions.
Optimisation and model training
We test and optimise AI models with your data and use fine-tuning to adapt them to your domain and business context.
Security and control
We manage access and data flows and provide transparency over models, usage and costs, aligned with your data protection, security and regulatory requirements.
Operations and monitoring
We take care of monitoring, support and updates and continuously evaluate new models, so your platform stays secure, high-performing and up to date.Digital sovereignty has many facets
Sovereignty is not a yes-or-no question. Depending on your data, use cases and regulatory requirements, the right solution can range from a controlled cloud environment to fully local operation. Together, we determine where you need which level of sovereignty.
Your benefits with sovereign AI from Ergon
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The right AI architecture for your needs: we develop an AI architecture that matches your protection requirements, your existing systems and your commercial requirements.
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Flexible choice of models and technology: with open models and standards and interchangeable components, we reduce your dependence on individual vendors.
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AI expertise meets data engineering: we integrate AI applications seamlessly into your existing systems and business processes, from intelligent document search to AI agents.
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Secure by design: we place great emphasis on security and data protection compliance in line with the GDPR, the Swiss FADP and industry standards.
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One partner from start to finish: with over 40 years’ experience in software development and data projects, Ergon brings together business analysis, architecture, software engineering and operations.
Is secure AI right for you? Talk to our experts and find out which level of sovereignty suits your organisation.
FAQ
A sovereign AI infrastructure makes artificial intelligence usable even where data is particularly sensitive. These FAQs explain what digital sovereignty involves, which building blocks make up a local AI platform and what matters most for security, model choice and operations.
Why is a sovereign AI infrastructure important for organisations with sensitive data?
Organisations that upload sensitive data to public AI services can increase their data protection and compliance risks. Organisations that ban AI risk employees working with private accounts and falling behind. Providers can switch off models, change their terms or limit capacity, and foreign authorities may, under certain conditions, demand access to data. A sovereign AI infrastructure makes AI usable for your most sensitive data and keeps you able to act.
Will my data or inputs be used to train the models?
No. Ergon does not use your data or inputs to train or further develop models unless you explicitly request and approve this. With self-hosted models, architecture, processes and access rights ensure this both technically and organisationally. Where third-party cloud models are integrated, we only use services whose contractual terms rule out the use of your data for training.
Which AI models are suitable for sovereign AI?
Which models are powerful and suitable enough depends on the use case. For tasks such as document analysis, summaries, translations or internal assistants, open models are often sufficient and can be run on your own infrastructure. For specialised requirements, cloud models can also be integrated via controlled interfaces. Besides model quality, the key factors are hardware requirements, speed, licence terms and the ability to replace models later.
On-premises or Swiss cloud: which deployment model is right?
The right deployment model depends on protection requirements, regulatory obligations, existing infrastructure and the level of control you need. Particularly sensitive data or specific compliance requirements can make a case for running on your own infrastructure. A Swiss cloud offers more flexibility and reduces the effort for hardware and operations. Hybrid models are also possible. We choose the right option together with you, based on your requirements for data protection, security, availability and cost.
What does it cost to run your own AI infrastructure?
Running your own AI infrastructure involves one-off hardware costs followed by predictable operating costs. The effort depends on the use cases, the number of users, the model size and the availability requirements. For text, summaries or transcription, a single GPU server is often enough. This makes getting started realistic for smaller organisations too. Operation, monitoring and updates are largely automated and can be handed over to Ergon.
How do we avoid creating a new vendor lock-in?
A sovereign AI infrastructure should reduce dependencies, not create new ones. That is why we rely on interchangeable models, standardised interfaces and an architecture in which applications remain as independent as possible of any particular model or vendor. This allows you to switch models, hardware or operating environments when needed, without rebuilding the entire solution.
We look forward to hearing from you
We are pleased that you are interested in our services. Do you have any questions or a specific project idea? Tell us about it – with no commitment on your part. Our experts will contact you as soon as possible.
Glossary
Digital sovereignty is not a yes-or-no question but a balance between protection requirements, cost and the ability to act. This glossary explains the terms that make the difference when building and running your own AI infrastructure.
Digital sovereignty
Digital sovereignty is an organisation’s ability to decide for itself about its data, its technologies and how they are operated. In the context of AI, it covers data, models, operations and jurisdiction, and shows in how well an organisation can still act when things change.
Swiss cloud
The term Swiss cloud refers to cloud services with data centres in Switzerland. What also matters for sovereignty is which law the provider is subject to: even data held in Swiss data centres can fall under foreign laws if the provider is headquartered abroad.
On-premises
On-premises means that a solution runs on your own or contractually controlled infrastructure rather than in a public cloud. This can be decisive for data protection, control over data flows and regulatory requirements.
Open models
Open models are freely available AI models that can be run on your own or freely chosen infrastructure. They offer more control over operations and data flows and reduce dependence on individual vendors.
GPU server
A GPU server is a computer equipped with graphics processing units designed for the parallel computations that AI models require. The number and performance of the GPUs determine which model sizes can be run and how many users can work at the same time.
Model independence
Model independence means that applications are not tied to a specific AI model or vendor. The AI infrastructure acts as an adapter between applications and models and supports widely used interfaces such as the OpenAI and Anthropic APIs. This allows models to be connected or replaced regardless of vendor or hosting location.
Shadow AI
Shadow AI refers to employees using AI tools that have not been approved, often via private accounts. It usually emerges when no approved alternative is available and increases data protection and compliance risks.
