Most of what companies call AI today waits until you ask it something. You type a question, you get an answer, and you still end up doing the work yourself. This employee gets access to the systems you choose, runs around the clock and keeps track of what needs to be done. In the morning, a report is on your desk: what it did and what it needs you to decide.
Two one-hour workshops, and within 48 hours you know what is worth automating in your company, what it brings and whether an AI employee pays off at all. If it turns out it doesn't, I'll say so and we stop there.
If the plan shows it pays off, I follow up right away: I build the employee, connect it to your systems and hand it over in operation. How fast I can deliver a finished thing is shown by a real case: 20 days from order to live operation, five people work with it today.
With a chat, you have to come to it, phrase a question and then do something with the result. This employee knows what to do today because it knows your rules and sees what is happening in the company. You talk to it only when you want to.
It writes, creates, fills in and records things where they belong. It has access to your systems, so the work really gets done and off the table. By it, not by you.
It knows your customers, your prices and what you criticized last week. The longer it runs, the less you have to explain.
This is what a day looked like at a model trading company of twenty people. The numbers are an illustration, not a promise. At your company it will do what you decide.
It went through 214 companies in the CRM and for 63 of them filled in the missing company ID, address or line of business from public registers. For 9 it found the company had changed its managing director and flagged them for review. It merged 4 duplicate records of the same company.
It pulled 6 new inquiries from the mailbox, read the attachments, filled in the form and created them in the system. It recognized 2 as existing customers and attached them to their history. It marked one as spam.
It found 11 quotes the customer had not responded to for a week and prepared a reminder for each one, in the style of the salesperson who sent it. They wait for his approval.
It compared the prices in the quotes against the current price list. In 3 it found a mismatch: twice an old price, once a discount beyond the rules. It flagged them and wrote down what it noticed.
Every salesperson has today's tasks sorted by what is urgent and where the money is. The manager can see who has how much work in progress.
One page: what happened yesterday, what it handled, where it got stuck, and three things it needs you to decide. Nothing more.
An inquiry that arrived at 13:12 is in the system at 13:13. At 14:40 it found that an e-mail to a customer bounced and told the salesperson who sent it.
It updated what changed during the day, prepared materials for tomorrow and listed what stayed open. Tomorrow at two in the morning it starts again.
| Today | With an AI employee |
|---|---|
| You retype orders from e-mail into the system by hand | Data flows in on its own; you just check it in the morning |
| You build the management overview on Sunday evening | The report is waiting, finished, every morning |
| You write answers to the same questions again and again | Drafts are prepared; you only send them |
| You keep reminders and deadlines in your head | The agent watches them and speaks up in time |
The price covers the initial survey, configuration, connection to your systems and training your people. No further invoice for the setup will ever come.
Server operation and my ongoing care. The company changes, the assignment changes and it changes with them. The price also covers adding whatever you come up with along the way.
It doesn't get sick, doesn't leave for a competitor and doesn't forget what it learned. If we part ways, you get its configuration and memory to keep. In the variant on your own server it keeps running even without me.
On your own server at your company. With a local AI model, company data never leaves the building. For companies that care about their data, or whose industry rules require it.
On a server I manage. A cheaper variant, faster deployment, no hardware on your side. Access stays separated from everything else.
Before I deploy anything, we go through where you lose time today. If AI doesn't make sense for a given task, I'll say so.
It starts by only preparing everything and waiting for your click. Only when you see it does the job well do you let it go further on specific tasks. You decide, not it.
It doesn't get the keys to the company. It gets access only where it should have it, and you can change that anytime.
Every step can be traced. It is not a black box that decisions fall out of.
The monthly fee includes changes to the assignment. The company evolves, and it evolves with it.
Tell me what people at your company do over and over. We will look at what it can take over, and what is better left to people. If none of it makes sense, you find out right away and it cost you nothing.