Buyer's Guide

AI Consulting in Switzerland: What SMEs Should Actually Look For

Every provider claims to be the right fit. Here's the actual checklist — including where Quantix Systems fits, and where it honestly doesn't.

How to evaluate

Four questions that matter more than the pitch deck

1

Data-first or framework-first?

Does the provider start by analyzing your actual data, processes and organizational structure — or by presenting a generic AI framework? If nobody has looked at your data yet, any strategy is a guess.

2

A working system, or a slide deck?

Is the deliverable something that actually runs, or a roadmap and a set of recommendations? Slides don't automate anything.

3

Where does your data run?

On your own infrastructure, or inside a system you don't control? For Swiss SMEs and financial institutions, this decides nDSG and FINMA compliance from day one — not as an afterthought.

4

Advisory on request, or mandatory retainer?

Is ongoing strategy advice something you can opt into when you actually need it, or a subscription you're locked into regardless?

The market

The four provider types you'll run into

Not a ranking — just what each model is actually optimized for.

Large consultancies

Broad reach and staffing capacity, higher day rates, often junior consultants doing the actual work under a senior name.

Boutique AI agencies

Fast and trend-aware, but often tool-first — they sell you a chatbot or an automation before analyzing whether it's the right problem to solve.

Independent consultants

Flexible and direct, but capacity-limited — rarely covers both custom software development and ongoing advisory.

Platform vendors

Sell you their SaaS or cloud AI product — the "advisory" is usually a sales function pointed at their own platform.

Honest fit check

Where Quantix Systems fits — and where it doesn't

Probably not a fit

  • You want a multi-week workshop series for a large team
  • You need staff augmentation or a large delivery team
  • You've already picked a specific AI tool and just need it installed

Likely a good fit

  • You want your data and processes analyzed honestly before anything is built
  • You need custom software or an ARCOS deployment, not just a recommendation
  • You want on-premise systems aligned with nDSG and FINMA
  • You want advisory available on request, not sold as a retainer
Take this to your next call

Six questions to ask any AI consulting provider

  1. Can you show me you've looked at my actual data before recommending anything?

  2. What's the deliverable — a working system, or a report?

  3. Where will my data physically run?

  4. What happens after the project — a mandatory retainer, or advisory on request?

  5. Who's actually doing the work — the person I'm talking to, or a team I've never met?

  6. What happens if the honest answer is "you don't need AI"?

Questions

Frequently asked

Is a boutique provider better than a large consultancy for a Swiss SME?

It depends on what you need. A large consultancy brings breadth and staffing capacity, often at a higher day rate and with junior staff doing the actual work. A boutique or independent provider usually means direct access to the person actually doing the analysis, faster decisions, and a narrower but deeper focus. For a single diagnostic engagement or a specific software build, that focus is usually the better fit.

How much does AI consulting cost in Switzerland?

There's no honest single number — it depends entirely on scope: a diagnostic analysis, a custom software build, and an ongoing advisory role are priced very differently. Any provider quoting a fixed price before looking at your data or process is guessing. The only reliable way to get a real number is a scoping conversation.

Do I need a data strategy before I start with AI consulting?

You need clean, accessible data and a clear picture of your processes more than you need a formal "data strategy" document. Many SMEs solve their actual problem with better data and a working analytics platform, before AI becomes relevant at all.

Is on-premise AI still realistic for a small Swiss company?

Yes. On-premise deployment is more about architecture discipline than company size — the same principles that apply to a bank apply to a 20-person SME. It means your data stays inside your own infrastructure, in line with the Swiss Data Protection Act (nDSG), without dependency on external cloud providers.

Want the honest read on your specific situation?

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