Integrating artificial intelligence into a company isn’t about giving the whole team access to a chat window. It means capabilities such as interpreting a request or finding a document become part of processes that already exist. The model is only one piece: it must also reach the right data, integrate with your systems and provide traceability of what it does.
I start with the user’s goal
The first step is defining what the person using it must achieve. Consulting an internal procedure is not the same as preparing a change in a management system. The first needs reliable sources and access control. The second also requires validating data and having write permissions in another system.
That difference determines the whole architecture. Starting with the technology leads to building components the first version didn’t need.
The usual architecture
There is normally an entry point where the person makes their request, an in-house service that applies the business rules, the integrations with your applications and the model provider. If the system has to consult documentation, it must be processed and indexed for search.
In an internal knowledge assistant, for example, the flow is: receive the question, check what that user can access, retrieve the relevant documents and answer citing the source of each fact. Each step has its own failure modes, and it is worth defining who is responsible for each one.
Where data is processed and who maintains it
You need to decide where information is processed and stored, who manages access and what conditions each provider offers. I compare the options against the company’s real needs and their maintenance cost, not against the trend of the moment.
Updates, backups where relevant, alerts and the incident procedure also need planning. Something working in a demo doesn’t mean this is solved, and it is precisely what tends to be left out.
A first version that can be verified
Before building, I gather a set of real cases from daily operations and we agree on the expected answer for each one. I deliberately include incomplete requests and situations where an external service doesn’t respond.
That test set shows whether the first version meets its goal and can be rerun whenever the model or the instructions change.
If you are considering bringing AI into an area of your company, here is how I work, or book a meeting and we’ll look at your case.