Sovereignty through Local GenAI: Independence in the Age of AI

Maximum security for your processes

Are global Gen AI solutions really the right place for your highly confidential data?

Are global GenAI solutions really the right place for your highly confidential data?

Many companies today face a risky dilemma: they want to leverage the enormous efficiency of artificial intelligence, but fear the creeping loss of control over their most sensitive information. Dependence on international tech giants and concerns about feeding valuable corporate know-how directly into a digital "black box" often act as a massive brake on innovation.

Are you also facing these challenges?

Selecting an open-weight LLM

How do you choose the optimal open-weight model based on performance, inference costs, and security features?

On-premise LLM hosting

How can the GPU infrastructure be properly sized for the selected LLM model and the expected workload?

Selecting a GPU hosting provider

How do you identify the best regional partners for GPU hosting—while strictly considering performance and data protection compliance?

Cybersecurity protection for private LLMs

How do you implement the key protection mechanisms to protect private LLMs against current attack vectors?

Sovereign AI in Sales

The pressure is mounting: volatile prices, tight margins, changing customers. That's why many companies use ChatGPT & Co. for emails, quotes, or analyses. The results are impressive, but where does the data end up? This article shows why standard AI has technical limitations and also poses a data risk – and how sovereign, proprietary AI can become a secure sales copilot.

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Future-ready solutions and concepts

Implementing private LLMs

Private LLMs for data-sensitive GenAI applications

We support you from feasibility analysis and technical design to the implementation of private LLMs.

Designing hybrid private-public strategies

The right mix of private and public LLMs

Not all data has the highest confidentiality level. Much of the data can still be processed by public LLMs.

Fine-tuning private LLMs

Train LLMs on your terminology

Fine-tuning optimizes models for specialized tasks, increases precision, and ensures full control over your knowledge while maintaining high cost efficiency.

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