AI agents that handle routine back-office work for you

An order arrives by email. Someone reads it, finds the client in the ERP, checks stock, creates the order, and sends a confirmation. That is five actions across four screens, dozens of times a day. Each step is simple. Together they take up most of one employee's morning. An AI agent does exactly this kind of work. It receives a task, looks into your systems, carries out the steps, and comes back to you when it is unsure.

What an AI agent does differently from a chatbot

A chatbot answers a question and waits for the next one. An agent receives an assignment and finishes it. It reads the email, opens the client record, compares the ordered quantities with stock, creates the order, and reports what it did. Nobody has to type a prompt. The agent runs in the background and picks up whatever arrives, whether that is a mailbox, a folder of PDFs, or a new row in your CRM.

The difference is in the doing. Chatbots & voice agents hold the conversation with your client. A back-office agent does the work that follows. The two often work together: the chatbot takes the request, the agent carries it out in your systems, and the chatbot tells the client it is done.

Which back-office work an agent takes over

The best candidates are tasks that happen often, span several systems, and follow a fixed route. Order entry from email and PDF. Matching purchase invoices to the right purchase order and preparing them for approval. Requesting missing documents from the clients of an accounting firm and tracking what has not arrived. Adding Chamber of Commerce data and open items from your accounting system to a CRM request. Telling a carrier the new delivery time when an order is ready later.

None of these tasks is hard. There are just so many of them that someone is busy with them every day. We start with the task that costs the most hours. It is almost always something your team has done for years without thinking about it. If you do not know which task that is, the AI process scan counts it up before we build anything.

Limits, permissions, and a person watching

An agent that may write in your ERP gets no more permissions than the employee who does that work today. Usually it gets fewer. It may create a draft order, but not send an invoice. It may ask a client for a document, but not promise a discount. Every action is logged with the reason, so you can see afterward exactly what happened and why. Above a limit that you set, such as an order amount or a client who is not yet in your system, the agent prepares the task and waits for a person to approve it. If it is unsure about an address or a quantity, it asks instead of guessing.

The model runs on an isolated server in the EU, and your data is not used to train anyone else's models. Personal data goes to the model only when the task truly needs it. We record what the EU AI Act and the GDPR require of you in the documentation you receive. That way, an audit or a question from a client holds no surprises.

An agent that does one task in 10 business days

We do not build an agent that can do everything. We build one that does a single task well. You point out the process. Within 10 business days, we build a prototype that runs on real emails and real orders, first with a person approving every action. You see in practice how often it gets things right and where it gets stuck. If the error rate is too high for your work, we tell you right away and stop there. You are then a few weeks further along, not months.

If it works, we relax the approvals step by step and connect the agent permanently to your software, whether that is Exact, AFAS, Odoo, or a system of your own. What you get is yours: the code, the instructions the agent follows, and the logs. There is no subscription per task and no vendor you cannot replace. A second task comes only after the first has run smoothly for a few weeks.