AI development and automation for Swiss businesses

Where AI pays off for Swiss companies

Swiss firms often run lean teams serving demanding customers in several languages. That makes repetitive work expensive: answering the same questions in three languages, re-typing data between a CRM and an accounting tool, sorting inbound documents. These are the jobs AI handles well when it is scoped tightly and supervised.

Privacy and the Swiss legal frame

The revised Federal Act on Data Protection has applied since 1 September 2023 and covers AI that processes personal data. The FDPIC is the regulator. In practice this shapes the design from day one. Not legal advice; your lawyer should confirm the details.

• Collect only what the task needs, and tell people when they are talking to an AI assistant.
• Decide what may be sent to an AI provider. Names, health data and financial details need a deliberate decision, not a default.
• Sending personal data to a provider or team abroad is a disclosure abroad, so safeguards are set in writing first.
• Switzerland is not in the EU, but the EU AI Act and GDPR can still reach you if you place AI systems on the EU market or serve EU users.
• Keep a human in the loop for decisions that affect a person, and log what the system did.

Our AI readiness checklist and AI use policy template help you get these decisions on paper.

Language: standard German, French, Italian and dialect

Written Swiss communication uses standard German with Swiss spelling, not dialect, so a chatbot answers in written standard German and uses ss instead of ß. Visitors may type dialect words, which current models mostly understand, but we test on real examples from your customers before launch. French and Italian get their own test sets rather than being treated as translations of the German.

How a project runs

1. Scope callWe pick one process with clear volume and a measurable result, and agree what the AI may and may not do.
2. Prototype on your dataA working version on a small set of real cases, reviewed with you in the first weeks.
3. Test and tuneWe run it against your edge cases in all needed languages and add guardrails and handover rules.
4. Launch and monitorGo live with logging, a review routine and documentation your team can read.

We work remotely from India. Switzerland is 3.5 to 4.5 hours behind, so a morning review in Zurich is an afternoon in Pune, which leaves most of a shared day for questions.

Tools and models we use

We pick the tool for the job instead of one stack for everything. For model calls we use the OpenAI and Anthropic (Claude) APIs. For connecting systems we use n8n, Make or Zapier when a visual workflow is enough, and custom code when volume, speed or control call for it. Our comparison of n8n and Make explains how we choose.

Swiss companies often run a mix of local and international software: Abacus or Bexio for accounting, Microsoft 365 or Google Workspace for mail, and a CRM such as HubSpot or Salesforce. We connect to whatever API your tools offer and tell you early if one is missing. Where a vendor offers hosting in Switzerland or the EU, we can design to it. Ask us about this during the scoping call, because it changes the architecture.

We also say no to some ideas. If a rule-based form does the job, we will tell you, and if your data is too thin for a useful assistant, we will say so before you spend money.

Pricing

Projects start at $1,500 and the rate is $30 an hour. You get a fixed quote within one working day of a short call. Running costs for model usage are separate and paid to the provider on your account. See the AI chatbot cost guide and the AI automation cost guide for what moves the price.