Most of what fills a support inbox is the same twenty questions in different words. An agent can close those and leave the ones that need judgement on a colleague's desk, already drafted.
Who is an AI agent for?
- Support teams whose queue is longer at the end of the day than at the start
- Back offices where the same request gets typed out again every week
- Anyone whose senior people are the bottleneck for routine answers
What does an AI agent actually do?
- 01
It reads the whole request, not the subject line
The ticket, the thread it belongs to, the order behind it and the customer's history. The same context a colleague would open before replying.
- 02
It answers from your material
Your help pages, policies, price list and order data — not from what a model happens to remember. When the answer is not in there, it is built to say so and pass the question on, instead of making one up.
- 03
It knows which ones are not its to close
Refunds over an amount you set, anything about a complaint, anything it is not confident on: those go to a person with a draft attached, so the handover costs a read rather than a restart.
- 04
It leaves a trail
Every action it took and the source it used, in a log you can read. When something goes wrong you can see exactly where, which is the difference between fixing it and guessing.
What may an AI agent never do alone?
- Which systems it may read, and which it may only write to
- What it may send without a human, down to the amount and the topic
- The tone it replies in, and the answers it is never allowed to give
- The off switch, in your hands, with no call to us required
What happens after go-live, and what does it cost?
We start on one real queue with your own data, so you can see whether it holds up before you commit to more. From there it runs on managed hosting from €39 a month, and the rules stay yours to change.