AI that your team approves

AI is good at reading documents, sorting requests and writing drafts. We build it into your workflow so that it prepares this work and a person on your team makes the decision. Your data stays in your system.

Discuss your project Start the process check

Does this sound familiar?

Invoices and delivery notes are typed in field by field.
Someone sorts the shared inbox by hand every morning.
Staff paste customer data into their private ChatGPT accounts.
The same replies are written from scratch every day.

What you get

Reading documents
The system reads invoices, delivery notes and reports and fills in the fields. Your team checks and confirms.
Sorting requests
Incoming emails and forms are sorted by topic and urgency and assigned to the right person.
Draft replies
For recurring questions the AI writes a draft. It only goes out once someone on your team has approved it.
Traceable
You see what the AI suggested and what your team made of it. That way you notice early where it gets things wrong.

How it works

Typical duration, depending on scope.

1 to 2 weeksWe look at which documents and requests reach you and how they are handled today.
A few daysWe try real examples from your business to see how reliable the recognition is. Then we decide together.
6 to 12 weeksWe build the workflow with a review step and connect it to your systems.
OngoingWe watch where your team corrects suggestions and improve the system step by step.

Questions about this

Where is our data processed?

We decide that together. Options are a language model accessed through an interface under a data processing agreement, or a model that runs on a server of its own. Your data does not end up in private accounts.

What if the AI makes a mistake?

That is exactly why a person always approves. The system flags uncertain results, and every correction is visible. Nothing goes to clients or into the books without approval.

Do we need a lot of our own data for this?

Usually not. For invoices, delivery notes and typical requests, today's models do well with good instructions. We still need a few real examples from your business to test it.