Process analysis and automation.
First I look at how the work actually gets done — with the people who do it every day. Then the work that comes back daily and moves nobody forward disappears: copying data, producing documents, triaging requests.
Why analysis comes before tooling
Automation built on a poorly understood process makes the poor process faster. That is not an improvement, it is entrenchment — afterwards the detour is cast in software and harder to change than it was before.
So this does not start with picking a tool. It starts with an afternoon next to the people doing the work. Not in a meeting room with the leadership team, but at the desk: which file gets copied where? Where does someone wait for someone else? Which step exists only because something went wrong once, three years ago?
The result is a sober list: where the time goes, which steps are worth automating, and which are better simply abolished. Sometimes the best automation is deleting a step entirely.
What usually turns out to be automatable
The worthwhile candidates look much the same everywhere: tasks that happen often, follow clear rules, and demand nothing from anyone professionally.
- Map the workflow, name the bottlenecks, put numbers on effort and return
- Automate recurring work, from quote to invoice
- Connect the systems you already run: CRM, ERP, e-mail, file storage
- Extend your existing software with AI instead of replacing it
Connect systems instead of replacing them
In most companies the real problem is not one bad system but the gap between several good ones. The CRM knows something the ERP needs. File storage holds the document that should end up in the quote. Today that gap is bridged by people who retype and forward.
Those gaps can nearly always be closed without touching any of the systems involved, using the interfaces they already ship with. It is unspectacular, considerably cheaper than a replacement, and it leaves the tools your people already know alone.
Where AI helps, it joins in: sorting free text, pulling the relevant details out of an e-mail, preparing a draft that a human approves. Where conventional rules are enough, conventional rules are what you get — they are predictable and cheaper to run.
The person stays, the typing goes
AI does not replace people, it amplifies them. Whoever did the work before still does it afterwards and still makes the same decisions. What changes is what fills the day: what disappears is the retyping, the forwarding and the checking up.
That is not a reassurance formula, it is a condition for the thing working at all. Automation that arrives looking like redundancies gets quietly undermined by exactly the people whose cooperation it needs. That is why the analysis phase involves talking with the team, not only about them.
Questions about this
How long does an analysis take?
For a bounded area, usually one to two days on site plus write-up. What you get at the end is a list with effort and expected return per candidate — including when the conclusion is that automating it is not worth it.
Do we have to change our systems?
As a rule, no. The normal case is connecting the systems you already have through their interfaces. Changing systems is a separate, far bigger project and should never be a side effect of an automation exercise.
What happens to our data if AI is involved?
We settle that before anything is built: which data may leave the building and which may not. If data cannot leave, that is a requirement like any other — not a reason to bury the project.
The other areas
Most projects touch more than one of these.
- Custom software development from HamburgCustom web applications, APIs and legacy modernisation from a freelance software engineer in Hamburg — including advice that sometimes argues against a rewrite.
- AI training for business teams and managersHands-on AI training for business teams and managers, using your real tasks and your real documents. Explicitly not for developers. Hamburg and remote.
- Claude Skills and MCP server developmentDevelopment of Claude Skills and MCP servers: hand recurring tasks and formats to an AI permanently, and make internal systems safely reachable for it.
Sound like your problem?
A 30-minute call, no obligation. By the end you know whether it is worth doing — including when the answer is "probably not".