Why n8n and not simply Zapier?

Zapier and Make are ideal for quick, manageable processes, and we use them for exactly that. n8n plays to its strengths with more complex workflows, AI steps and large volumes of data. It can also be run on your own servers. We recommend the tool that suits your process.

Where do the automations run, and what happens to our data?

Depending on your requirements, in the vendor's cloud or on a server of your choice, for example in a data centre in Germany or on your own infrastructure. Which data goes where is agreed with you before we build anything, and documented.

What does a project cost?

That depends on the scope. After the process audit you receive a quote at a fixed price for the implementation, together with an estimate of how much time the automation will save. That way you can see up front whether the investment pays off.

How long does it take until the first workflow runs?

A single, clearly defined workflow is often live in 2 to 4 weeks. Larger projects are split into stages so that you see a benefit early on.

What happens if something does not work?

Every workflow reports errors to us immediately. Many issues, such as an interface being briefly unavailable, are handled by the workflow itself with a retry. Everything else we fix as part of our support.

Does our team need technical knowledge?

No. Your team keeps working in the tools it knows. Anyone who wants to adjust the workflows themselves gets a training session and documentation in plain language.

Can you take over existing workflows?

Yes. We first review what is already running, document it and propose what can stay and what we would improve.

Do we have to buy licences for n8n, Make or Zapier ourselves?

The accounts are usually held by your company so that you keep full control. We advise you on the right plan and set everything up.

What happens if we end the collaboration?

All workflows and accounts belong to you. With the documentation, your team or another provider can continue seamlessly.

Which AI models do you use?

That depends on the task. Among others we work with models from OpenAI and Anthropic and choose according to the requirements for quality, cost and data protection.

What happens to our data?

Which data goes to which model is agreed with you before we build anything, and documented. Where necessary, we reduce the data beforehand to what the task actually requires.

What if the AI gets it wrong?

That is what approvals and logs are for. In uncertain cases the agent asks instead of guessing, and every step can be traced afterwards.

How much time do we need to invest ourselves?

Most of it in the first week, when we go through the process together. After that, short check-ins and a test with your data are enough.

Yes, that is what we recommend. A single workflow quickly shows whether and how much time can be saved.

What if our process changes during the project?

Small changes we absorb. Larger ones we discuss and then adjust scope and price transparently.

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Which process costs you the most time today?

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