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AI Solutions

AI that runs on your infrastructure, on your data.

Overview

Open-source models deployed locally or in a private Swiss cloud. Your data never leaves your infrastructure.

Local AI is an artificial-intelligence model that runs on your own servers or in a private Swiss cloud instead of OpenAI's or Google's infrastructure. Your data never leaves your network — the answer to the confidentiality requirements of legal, medical, financial and industrial work. Today's open-source models make it a realistic option for SMEs.

Target

For Swiss SMEs and organizations handling sensitive data — law firms, medical practices, fiduciaries, banks, manufacturers — that want the benefits of AI without routing their documents through American servers.

Details

ChatGPT and Claude are remarkable, but they run on servers you don't control. For many Swiss organizations that is a legitimate blocker: professional secrecy, patient data, client files, trade secrets. Local AI removes it.

We select an open-source model suited to your need, deploy it on your infrastructure — a dedicated server, a powerful workstation or a Swiss-hosted private cloud — and connect it to your documents and tools. You get an assistant that knows your context, with one simple guarantee: nothing leaves.

Why local AI changes everything for sensitive data

Every time an employee pastes a document into ChatGPT, that document travels to servers abroad. Enterprise plans restrict what is done with it, but the data still travels. For a lawyer, a doctor, a fiduciary or a manufacturer, that transit alone can be unacceptable — contractually or legally.

Local AI reverses the relationship: the model comes to you, not the other way round. Your documents stay on your server, your queries never leave your network, and you can audit exactly what gets logged. nLPD compliance stops being a grey area.

Our approach: the right model in the right place

The all-local reflex is expensive; the all-cloud reflex exposes you needlessly. Our work starts with a mapping: which tasks touch sensitive data, which never do, and what volume that represents.

Then we size the solution: a compact model is often enough to classify, extract and summarize; a larger one is warranted for demanding writing. Today's open-source models — Llama, Mistral, Qwen, DeepSeek — offer excellent quality for the cost, and deployed locally their weights run on your hardware: no data ever reaches their publishers.

What we actually build

A local AI deployment is not a server blinking in a corner. It is a working tool wired into your daily operations.

  • An internal assistant that answers from your documents (local RAG), citing its sources
  • Automated processing: mail classification, PDF data extraction, draft replies
  • A simple interface for your teams, in the browser or inside your existing tools
  • The right infrastructure: a GPU server on premises or a Swiss-hosted private cloud
  • The logging and access controls your sector requires

Cloud, local or hybrid: how to choose

The right architecture is often hybrid: local AI handles what is confidential; a cloud model handles the rest when top writing quality matters. We define the boundary with you, per data type and per use case, and enforce it technically — not just in a policy document.

What it includes
  • Open-source model deployment (Llama, Mistral, Qwen…)
  • Local RAG on your internal documents
  • Swiss hosting or your own server
  • Business assistants connected to your tools
  • nLPD compliance and professional secrecy
  • Hardware sizing and cost optimization
Deliverables
  • A working AI assistant on your documents, hosted on premises or in Switzerland
  • A clear map: what stays local, what may go to the cloud
  • Infrastructure sized and documented, with no needless spend
  • Your teams trained on the tool, with written usage rules
  • A direct contact for maintenance and evolutions
Comparison

Cloud AI vs local AI

Cloud AI (ChatGPT, Claude, Gemini)Local AI (on your infrastructure)
Your dataTravels through external serversNever leaves your infrastructure
CostPer-user subscription, grows with the teamUpfront investment, low marginal cost
Writing qualityBest models on the marketVery good, improving fast
Compliance (nLPD, professional secrecy)Contract-by-contract reviewGuaranteed by construction
Connection to internal documentsLimited or via third partiesNative (local RAG)
Takeaways
  • Local AI runs on your servers: your data never leaves.

  • Today's open-source models make it realistic for SMEs.

  • Essential for legal, medical, financial and industrial work.

  • Hybrid architectures combine local confidentiality with cloud power.

  • We size, deploy and train — in French-speaking Switzerland, directly.

You might also need

Enterprise RAG

RAG on your knowledge base so AI answers with your context, not in general.

AI agent / assistant

AI agents that act inside your tools, not just chatbots that answer questions.

AI automation

Business and AI automation that frees your team from repetitive work.

Frequent questions

What exactly is local AI?

It is an AI model — often open source, such as Llama or Mistral — installed on your own server or in a private Swiss cloud. It works like ChatGPT, but everything happens on your side: questions, documents and answers never leave your infrastructure.

How is it different from ChatGPT Enterprise?

ChatGPT Enterprise contractually restricts how your data is used, but it still travels through OpenAI's servers. With local AI the question disappears: the data does not leave. For professional secrecy or patient data, that is a difference in kind, not in degree.

How much does local AI cost for an SME?

Expect an upfront investment for infrastructure and setup — from a few thousand francs for a simple document assistant to more for a full platform — then low running costs with no per-user subscription. Initial scoping prices your case precisely before any commitment.

Which open-source models do you use?

We select per task and hardware: Llama (Meta) and Mistral for versatility, Qwen for multilingual work, DeepSeek for cost-effectiveness. Deployed locally, these models run entirely on your hardware — no data reaches their publishers, whatever their origin.

Does our data really stay in Switzerland?

Yes. Either the model runs on your own hardware, or in a Swiss data centre you choose. In both cases we document the full data flow and configure logging so you can prove it — to a client, a regulator or an auditor.

Can we combine local AI with cloud tools like ChatGPT?

That is often the best architecture. Local AI handles confidential documents; ChatGPT, Claude or Gemini take the rest when writing quality matters most. We define the boundary per data type and enforce it technically, not just in a policy.
Next steps

Your data deserves AI that stays home.