Automate the process, not the job
Most teams lose time on work between systems: copying data, checking orders, writing the same answer again, compiling a weekly report. That is where automation pays off first. We start with one process, measure what it saves and extend from there.
When AI automation fits
WHEN IT FITS
It fits when a task comes back every day or week, follows rules a colleague can explain, and runs through systems with an API or an export. It does not fit when the process itself is unclear. Then we fix the process first.
Workflows
Fixed steps with a language model where judgement is needed: reading an email, classifying a ticket, drafting a reply. The route is defined, so the outcome is predictable.
AI agents
Agents choose their own steps within limits you set. We use them where a fixed route does not work, such as research, monitoring and multi-step tasks across tools.
We run our own agent stack, Commerce365, with live connections to Shopify, Meta Ads and Klaviyo. What we advise comes from systems we operate ourselves.
Connected to your systems
An automation is only useful when it reads and writes where the work happens: your ERP, CRM, webshop, inbox or spreadsheets. We build the connections and the scripts between them.
People stay in control
For every step we decide together whether it runs on its own, needs approval, or only prepares a proposal. Actions are logged, so you can see afterwards what happened and why.
How a project runs
Mapping. We go through the process with the people who carry it out and pick the first task to automate.
Prototype. A working version on your own data, so you can judge the output before anything goes live.
Build. We connect the systems, set the approval steps and test the exceptions.
Handover. Your team learns to adjust the automation, and we stay available for maintenance.
AI in practice
Which task would you automate first?
Tell us which process costs your team the most time and which systems are involved. We reply with a first approach.
