AI agents
A generic agent answers the way the internet answers. Your agent answers the way your company answers: with your documents, your rules and your limits. The difference is not the model, it is everything around it.
Free reviewWhen you need this
- Your team answers the same questions every week from the same information.
- There are tasks someone does by hand following always the same steps.
- You tried a generic assistant and it made things up or knew nothing about your work.
- You want to use AI but need to know exactly what it can and cannot touch.
What it includes
- Your business context inside it: documents, rules and your own vocabulary.
- Explicit limits on what it may do and what stays out of reach.
- A connection to your systems, to query and to act.
- A record of every decision, so it can be reviewed afterwards.
- Integration where you already work: your site, your chat or your internal dashboard.
How we do it
Before building anything we check whether an agent is the answer. Sometimes it is, and sometimes the right solution is a well-written query against your database, which costs less and fails less. That comes out in the audit, before anything is signed.
Five phases, each with its own acceptance criteriaQuestions about this service
How do you stop it making things up?
By bounding where it can take an answer from. The agent works over your documents and your systems, cites where what it says came from, and when it does not have the information it says so instead of filling the gap.
Can it do things, or only answer?
It can act, and that is exactly where limits matter. Which actions it is allowed to take, which need someone to confirm, and which it will never be able to do, all go in writing.
Which model do you work with?
Whichever suits the case, decided during architecture. What matters to you is that the choice does not lock you in: the logic, the data and the context are yours and do not live inside the model.