Artificial intelligence that does the work, with a person who confirms.

An AI agent does tasks, not just answers. A chatbot replies with a well-written text; an agent reads an order, looks up the customer and the items in your system, applies your rules and leaves the work ready for a person to confirm. Answering is the easy part; resolving is what counts.

That is why nothing goes out on its own: a person confirms before anything is recorded, and when the agent is not sure it asks instead of choosing. At a distributor, if “fernet” could be two items, it offers both options and remembers the answer. We also measure how many times a person corrected what it proposed.

It sees only what we give it for that task, and the data stays your company’s. When the system is in production, access is read-only: it reads without writing or changing anything. In projects with several companies, each one sees only its own, and that is put in writing before we start.

Maybe not, and we will tell you. If what enters the process already comes structured, like a statement or a work order, rules are enough, and they are cheaper and more predictable. AI is justified when a person writes the data: a voice note, a pasted list, a sentence.

A first version to try can be ready in weeks; getting it to work in production takes longer. At a beverage distributor, nine months passed between the start and the panel in production; the second one, building on what was learned, took four. We always start with a narrow process so we can measure early.