At an importer in Guayaquil, the head of purchasing spent Monday mornings with twenty tabs open. Supplier price lists as PDFs, each with its own date, each in its own currency, three of them revised by hand in a later email nobody filed. Her Monday question was always the same: what is the current price for this item from this supplier, and since when.
That is exactly the question an agent answers in about twenty seconds: it reads the same PDFs she was reading and returns the answer with the file name and the page each figure came from. The head of purchasing still checks what comes back. That is part of it working, too.
This article is about what that thing actually is, what it does well, what it does not do, and what it costs.
An agent is not an AI chat
The distinction looks like vocabulary and it is not. It decides what the thing can do for you.
An AI chat takes text and returns text. Everything it knows about your company is what you pasted into the message. If you ask about a supplier contract, you have to paste the contract. It is useful for drafting, summarizing and translating. It knows nothing about your company between one conversation and the next.
An agent takes a task and has tools. It can search your documents, open the ones it needs, read them, write a new file, leave a task noted. It works in several steps: it searches, reads, decides something is missing, searches again, and only then answers. That is why it takes longer than a chat, and why it answers things a chat cannot.
The practical consequence is that an agent is for questions whose answer you do not know the location of. A chat is for working with material you already have in front of you.
The four things an agent does well today
After sitting through several rollouts, these are the four that hold up in daily use. They are not the most impressive in a demo. They are the ones people are still using in month three.
Answering with the source. “What did we agree with this supplier about delivery times?” The agent searches, finds the contract and the later email where it was amended, and answers citing both. The value is not the summary, it is the citation: you can verify it in ten seconds.
Consolidating what is scattered. “List every confidentiality clause we drafted in the last two years and group them by equivalent wording.” Over a hundred and sixty contracts, that is one agent turn and three days of a trainee. It is the kind of work that sits on a firm’s to-do list for eighteen months because nobody has the free week.
Keeping a document alive. A process manual that gets updated when something changes, with the change noted and linked to the minutes where it was decided. This sounds minor and it is what stops documentation from dying, which is the cause of death of ninety percent of knowledge bases.
Preparing the boring draft. The meeting minutes from the notes, the follow-up email, the new supplier record with the details already in the file. Nobody is going to send it unread, but starting from a draft with the right facts saves half the time.
The three things it does not do
This is where expectations are better lowered by you than by reality.
It does not replace judgment. The agent will tell you something correct and something badly inferred from an out-of-date document with exactly the same confidence. Any answer going to a client or a regulator gets reviewed by a person. If your plan depends on nobody reviewing, the plan is something else.
It does not understand what was never written. If the reason that client has a twelve percent discount lives in the commercial manager’s head and in no set of minutes, the agent will not find it. It will find the discount, not the why.
It does not fix your permissions. And here it is worth being very concrete, because this is where people get nervous. When you put an agent over your documentation, information that was hidden in a subfolder becomes searchable. That is what you wanted. It also means the salary table, if it was in there, now surfaces. Before switching anything on, somebody has to review who sees what. It is half a day of work and it avoids a very uncomfortable conversation.
What an agent needs in order to be worth anything
Three things, and only the first is technical.
A place where the documents are. It can be messy. It cannot be spread across four personal mailboxes, because the agent cannot reach those and, more to the point, neither can whoever replaces that person.
A clear boundary of what it can touch. In Ofivia the agent works confined to the file subtree of the department where you opened the conversation. Sibling departments are not mounted into its working environment: the agent knows they exist because we pass it a summary, but it cannot open their files. That is the real boundary, and we say it that way rather than promising a per-file permission we do not enforce on writes today.
Somebody who corrects things. When the agent answers badly because the document was wrong, the work is not tuning the agent: it is fixing the document. The companies where this works are the ones that understood every bad answer is a finding about their documentation.
What they cost
Two costs, and they behave differently.
The software runs between fifty and a hundred and fifty dollars a month for a whole company, when billing is per company. When billing is per seat, between ten and thirty dollars per person per month, which for forty people turns into a considerably larger figure.
The model usage is what you pay for the agent’s real work. Over 119 measured turns on the installation we write from, the average came out at 0.19 dollars per complete turn. A team of forty where five use the agent daily runs between 1,500 and 3,500 turns a month, so between 285 and 665 dollars.
Two questions worth asking any vendor before signing. First: which operations consume nothing. Indexing documents and searching them should cost nothing, because they do not call a paid model. If you are charged to index, you will end up deciding what to upload based on price. Second: what exactly happens when the month’s credit runs out. In Ofivia usage is recorded and shown by day, by process and by person, and you see exactly what was spent. What we do not do today is cut off on our own at the ceiling: you see it in the dashboard, we tell you, and an owner can request more credit from that same screen.
How to evaluate it in two weeks without committing
The mistake is evaluating with demo questions. Do it like this.
Week one. Pick one department and upload what it has, without cleaning it. Write ten real questions somebody had to answer last month, with the correct answer noted separately. Have them asked by someone who was not involved in the upload.
Week two. Compare. Count how many it got right, how many wrong, and how many it said it did not know. The third category is the good sign: an agent that says it cannot find something is more useful than one that invents.
Seven right, two do-not-knows and one wrong is a good rollout. If it comes out four right and six wrong, look at those six source documents before blaming the software. In the evaluations we have sat through, between half and two thirds of the failures came from documentation that said something different from what the company believed it had written down.
That alone justifies the two weeks.
If you want to see how that working boundary is built, which tools the agent has and what gets recorded about everything it runs, it is explained in detail on the agent page.