Automate the manual routine that eats your team's day

1. Map the process

We walk through the routine together: every manual step, every copy-paste, every place time leaks. I write down exactly what triggers it and what 'done' looks like — so there's no guessing later.

2. Build the workflow

I write a script or workflow that links 2–3 of your systems — spreadsheet, CRM, mail, an API — and does the steps your team was doing by hand, the same way every single time.

3. Make it run itself

Triggers and a schedule so it fires on the right event or at the right time. No one has to remember to run it; it just happens in the background.

4. Watch it, report it, fail loudly

You get notifications and a result report, and errors surface immediately instead of failing silently — so you can trust the output without checking it by hand.

The best fit when someone on your team does the same operation by hand every day — moving data, generating the same quote or report, syncing two tools — and the rules are consistent enough to write down.

If your automation is a standard hop between popular apps — 'new form entry → row in a sheet → Slack ping' — Zapier, Make or n8n will do it in an afternoon for a monthly fee, and you shouldn't pay for custom. Custom earns its keep when the logic is unusual, a system has no ready connector, the data is sensitive, or per-run no-code fees get expensive at volume. And if the process still changes every week, stabilise it first — automate later.

The daily routine that eats your time, turned into a background process.

• ✓Process mapping: where it's manual, where time leaks
• ✓A script or workflow linking 2–3 of your systems
• ✓Triggers and scheduling: it runs itself
• ✓Notifications and reports on the outcome
• ✓Error handling — it fails loudly, not silently

How is this different from Zapier or Make?

Zapier and Make are great when your automation is a standard chain between apps that already have connectors. I build custom automation when the logic is unusual, a system has no ready integration, the data is sensitive, or per-task no-code fees get costly at volume. Often I'll even recommend a no-code tool if it genuinely fits — the honest answer saves you money.

What does 'fails loudly' mean?

It means that when something breaks — an API is down, a file is malformed, a value is missing — the automation stops and tells you, with a clear message about what and where. The opposite is silent failure, where a broken process keeps running and quietly produces wrong results for weeks. Loud failure is a deliberate design choice, not an afterthought.

Will it break when one of my tools changes?

Any integration depends on the tools it connects, so a major change on their side can require an update. I handle that two ways: error handling that surfaces the break immediately instead of producing bad data, and an optional support plan for updates and monitoring. Most months nothing changes; when it does, you hear about it fast.

What are the ongoing costs after it's built?

The build is one-time. After that you may pay for the services the automation uses — API calls, a cloud runner, a queue or scheduler — typically around €200–600 a month depending on volume, paid to those providers, not to me. Some automations run on near-free tiers. Optional support with me runs €50–750 a month if you want monitoring and updates.

How do I know my process is ready to automate?

A process is ready when the steps are consistent, the rules can be written down, and it's done often enough that the time adds up. If it changes every week or depends on human judgement each time, automate later. I'll tell you honestly on the first call rather than build something that fights a moving target.