AI implementation for companies in Geneva & French-speaking Switzerland

Data security is our priority. We work with strict confidentiality agreements and configure the OpenAI/Anthropic APIs in "no training" mode so your data is never used to train the models. For highly sensitive data, we offer an integration with locally hosted models (self-hosted Mistral, LLaMA via Ollama) that never leave your infrastructure.

The choice of LLM depends on your use case: GPT-6 Astra excels at tasks that drive tools and a browser, multilingual and vision-based work. Claude is optimal for long documents, analysis and code. Mistral is the best choice if European GDPR compliance and self-hosting are strong constraints. We always run a comparative benchmark on your real data before validating the final choice.

Yes. For cases requiring maximum confidentiality or independence from cloud providers, we deploy open-source models (Mistral, LLaMA) on your infrastructure via Ollama or vLLM. Performance is lower than frontier proprietary models, but more than enough for most business cases.

It is a real risk that we anticipate. Our orchestration layer is built with an abstraction that lets you switch LLM provider without changing your application code. We use libraries such as LangChain or LiteLLM that handle this portability. In practice, switching from GPT-6 Astra to Claude only takes a few hours of configuration.

Costs vary depending on volume and model. As a guide, in October 2026: GPT-5.6 Terra costs around 2 USD per million input tokens, Claude Sonnet 5.5 2 USD, GPT-6 Astra 10 USD and Claude Opus 5.5 4 USD. For an internal assistant handling 500 requests per day, a Terra- or Sonnet-class model costs 30 to 80 USD per month, a flagship model several times more. We set up cost monitoring and optimisations (caching, prompt compression) to keep the production bill under control.