Souverana.

Insights

AI, explained soberly.

Swiss-specific guides to sovereign AI, data protection and architecture, written for decision-makers.

Provider Data-Protection Check

5 parts

  1. Part 01 Analysis

    Is ChatGPT GDPR-compliant? What OpenAI's contracts cover

    A Zurich law firm reviewed OpenAI's contracts: none of them holds up for professional-secrecy work. What that means for business use, and three routes around it the review does not name.

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  2. Part 02 Analysis

    Anthropic Claude and Swiss data protection: what to check

    Claude works for business data, not for professional secrecy, according to VISCHER. And a promise many organisations rely on has not held for two models since June.

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  3. Part 03 Analysis

    Google Gemini & data protection: what SMEs need to know

    Google leads technically as the only provider, yet stalls on bureaucracy, and a signed addendum does not close the gap while the standard web search stays active.

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  4. Part 04 Analysis

    Using Microsoft Copilot safely: what data protection allows

    Microsoft closes almost every contractual gap, except for web search. What Swiss companies need to check on Copilot and Azure OpenAI.

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  5. Part 05 Analysis

    Proton Lumo: what privacy-friendly AI looks like

    Open models, its own servers, encrypted chats: Lumo 2.0 shows what confidential AI looks like. Two catches remain.

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Law & Regulation

5 parts

  1. Part 01 Guide

    AI regulation in Switzerland: what already applies

    Waiting for a Swiss AI law is not worth it. Almost every AI project is already measured against law that has been in force for years.

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  2. Part 02 Guide

    revFADP and AI: what the law actually requires

    The fine falls not on the company but on the person who approved the tool, up to CHF 250’000. That makes the approval a matter for management.

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  3. Part 03 Guide

    Professional secrecy and AI: what may go to the cloud

    'That does not work for us' is the standard answer to AI in law firms and medical practices. Art. 321 of the Swiss Criminal Code says something narrower, and most of daily work falls outside it entirely.

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  4. Part 04 Template

    AI governance: one page is enough to start

    A policy that takes three months to finish protects no one today. Shadow AI grows for exactly as long as the document keeps maturing.

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  5. Part 05 Guide

    EU AI Act Switzerland: role first, then duties

    Most Swiss companies owe the EU AI Act almost nothing. One single point gets expensive, and whoever slips into it usually notices too late.

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Sovereign AI

5 parts

  1. Part 01 Guide

    What sovereign AI actually means for Swiss companies

    If you sell discretion, you have a problem the moment a client asks where the data goes. Sovereignty is the answer, and it is not a product but a dial.

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  2. Part 02 Strategy

    AI strategy for SMEs: the questions to answer first

    Most AI strategies are tool lists. Nine questions that determine the sovereign path for Swiss SMEs, without a ready-made framework.

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  3. Part 03 Guide

    Sovereign AI infrastructure: why the model is the easy part

    The language model is the most replaceable part of your AI. Why embeddings and OCR decide your lock-in, and which Swiss hosters offer every component.

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  4. Part 04 Platform

    Sovereign AI platform: why it binds more than the model

    The model is easy to swap. The platform holds your chats, files and knowledge, and that is what binds you longest. How to choose platform, host and operations separately, and sovereignly.

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  5. Part 05 Integration

    Sovereign AI integration: when AI starts to act

    The moment an agent acts instead of merely reading, a mistake becomes an incident. Integration is where your IP is built and where you have to keep control. How that works.

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Local Inference

5 parts

  1. Part 01 Analysis

    Self-hosting an LLM: GPT-5 performance for CHF 8’500

    Two RTX 4090s, CHF 8’450, three weeks of measurements. Which tasks a machine of your own can carry, which it cannot, and where the real limit sits.

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  2. Part 02 Technical

    VRAM for LLMs: how to size it correctly before you buy

    How to calculate how much graphics memory you need from parameter count, quantisation, context length and concurrent requests. With a calculator and the measurements from two RTX 4090s.

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  3. Part 03 Technique

    LLM quantisation: how it works and how to use it well

    Quantisation is the lever that fits a large model onto affordable cards and makes it answer faster. How it works, how to quantise a model yourself, and how to find the level at which quality still holds.

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  4. Part 04 Technical

    Ollama, llama.cpp or vLLM: choosing the right engine

    Whether Ollama, llama.cpp or vLLM: the choice comes down to two questions. How many people work on the model at the same time, and how much graphics memory do you have relative to the model you want? Three tools, measured on the same hardware.

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  5. Part 05 Analysis

    Self-hosting an LLM: the real cost and the break-even

    Whether a machine of your own pays off against Swiss token prices comes down to one figure: utilisation. The full calculation to check for yourself, from the parts list to the break-even, with measured power instead of estimates.

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More articles

1 part

  1. Analysis

    What LLMs really cost: the price per token is misleading

    Comparing price lists is time wasted: token consumption, cache hit rate and quantisation decide what you actually pay.

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Start the AI Sovereignty Check