Business process automation and AI integrations
Most companies lose hours every week copying data between systems, retyping documents and chasing the same status by email. I find the step that costs the most, automate that one first and measure whether it worked.
01
What you get
- Integrations between the systems you already run — ERP, CRM, accounting, e-shop, spreadsheets
- Document and data processing: invoices, orders, reports, exports
- AI workflows with a person approving what matters
- Small internal tools where no off-the-shelf product fits
- Monitoring, so a broken integration is noticed before a customer notices it
02
Typical projects
- Orders arriving by email that someone retypes into another system
- Weekly reports assembled by hand from three different exports
- Documents that have to be read, sorted and filed
- A manual approval chain that lives in chat messages
03
How it goes
- 01
First conversation
You describe the problem in a sentence or two. I reply with questions — or with a straight answer that it is not work I should take.
- 02
Scope in writing
What gets built, what counts as done and roughly when, agreed before any code is written.
- 03
Build in reviewable steps
You see working software early and often, not a stack of screenshots at the end.
- 04
Launch and handover
Deployed, documented and handed over — with ongoing maintenance if you want it.
04
Questions
- Do we have to replace our current systems?
- No. Automation usually connects what you already have. Replacing a system is a separate decision, and rarely the first one.
- Is AI always part of it?
- Only where it helps. A lot of automation is plain, reliable integration work — AI comes in for reading unstructured text, documents or email.
- What about manufacturing?
- Automation on the production floor — predictive maintenance, vision-based quality control — runs through STKY, the company I lead.
Tell me what you need built.
Start with one sentence