AI automation
AI automation for the work that repeats every single week
AI automation removes the routine work where someone moves and corrects data by hand many times a week. I have been building automations since 2010 and make sure the solution runs in the systems you already use.
- I usually reply the same day
- Written estimate before work starts
AI automation
What I most often automate
- Document handling: extraction from invoices, order confirmations, datasheets and contracts arriving as PDFs.
- Customer service: categorising and routing incoming enquiries so they land with the right person immediately.
- Product data: descriptions, specifications and translations across many SKUs.
- Internal tools: reports currently assembled by hand from three systems every Monday.
- Integration with existing systems: moving data between webshop, accounting and inventory without manual go-betweens.
When it pays off
The arithmetic is simple: how many times a week does the task happen, how long does each one take, and what does it cost to build. If payback arrives within a reasonable horizon, it is usually worth doing.
Beware the trap of tasks that feel annoying but only happen twice a month. They loom large in the mind and are rarely worth automating, however much everyone agrees they are stupid.
Errors and control
Automation with AI is not deterministic, so there has to be a plan for the cases where the system is unsure or wrong.
My standard setup is a threshold: if the system is confident enough, the case goes through, and otherwise it lands in a queue a person looks at. The queue also shows how well it is really doing.
What you get
Concrete deliverables, not a report of recommendations someone else has to find time for.
- An automated workflow
A solution running in the systems people already use, not in a new tab someone has to remember to open.
- A threshold and a queue
A setup where confident cases go through and doubtful ones land with a person straight away.
- Before and after numbers
An account of how long the task took before, how long it takes now, and how many cases still need a hand.
- An off switch
A way to switch everything off without calling me. It sounds trivial and is what people most often ask for afterwards.
How it works
Four steps. You know what happens when, and you can stop after any of them.
- 01
Pick the process
Together we find the piece of work that repeats often enough for automation to pay off. The more contained the task, the faster the first version reaches production.
- 02
Set a baseline
We record how long the task takes today, how often it occurs, and how many errors slip through. Without those numbers, nobody can tell afterwards whether the solution was worth the effort.
- 03
Build against a test set
I collect real examples from your day-to-day and test every prompt and model change against them. That keeps quality stable when the solution is tuned later on.
- 04
Production with logs and a kill switch
The solution is wired into your existing systems with full logging and a switch that can turn it off. I document the setup and train someone on your side to maintain it.
Brands I've worked with
Frequently asked questions
- How does AI automation differ from ordinary automation?
- Classic automation follows fixed rules and requires structured data. AI automation can also handle text and documents that never look alike, such as emails and PDFs in every possible format. That opens up tasks that previously needed a person to read and judge.
- What does AI automation cost?
- The price follows the complexity. The number of workflows, the access to your systems and the volume of documents going through are what typically move it most. Describe the workflow in an email and you will get a reply the same day, and a fixed quote once a few details are in place.
- Do you use tools like Zapier or Make?
- For simple chains, yes, it is faster and cheaper. As soon as errors need proper handling or volume gets large, writing it as code becomes cheaper.
- How are personal data and GDPR handled?
- The first step is deciding whether personal data needs to pass through the model at all, because masking can often avoid it. Where it cannot, we choose hosting and data processing agreements that match your requirements, and everything is documented so you can answer if anyone asks.
- Do you automate for companies outside Copenhagen?
- Easily. The solution runs in your systems, so it makes no difference whether you are in Aarhus, Odense, Aalborg or outside the country. Most of it is handled over video, and I am based in Herlev if you want to meet.
- Does this mean someone loses their job?
- In the projects I have done, the answer is usually no. What disappears is the part of the day nobody liked. The decision is yours, though, and I believe it should be taken openly rather than sprung on people.
- How quickly does an effect show?
- On a bounded workflow there is usually something running within a month. The effect can be assessed from day one, provided the baseline was measured beforehand.
- Can we adjust it ourselves afterwards?
- The parts about rules and phrasing, yes. I put those somewhere they can be changed without touching the code, while the integrations themselves need a developer.