Every business has a person who "just checks something quickly" and loses an afternoon. A sales manager wants to know what a supplier's terms actually say. An accountant needs to compare how three official documents describe the same rule. An agency owner has to prepare a briefing on a market they have never worked in. The task is simple to state and slow to do: find sources, read them, compare them, write it up.
This is where a research agent is genuinely useful. Not as a chatbot that answers from memory, but as a workflow that does the legwork and shows its work.
What the agent actually does, step by step
- **Takes a precise question.** The agent starts from a written question, not a vague topic. "What do these three supplier contracts say about delivery delays?" is workable. "Tell me about suppliers" is not. Part of the setup is agreeing on what a good question looks like for your process.
- **Gathers sources from defined places.** The agent searches only where you allow it: a folder of your own documents, a knowledge base, a list of approved websites, an official register. The boundary matters. An agent that can read anything will sooner or later cite something you would never trust.
- **Extracts the relevant passages.** Instead of summarizing whole documents, it pulls the specific passages that bear on the question and keeps a link between each passage and its origin.
- **Compares.** Here the capability shines. A language model can read several sources written in different styles and lay out where they agree, where they differ, and where one source is silent. For a human this is the tedious part. For the agent it is the natural one.
- **Drafts an answer with evidence attached.** Each claim in the answer points to the passage it came from. If the sources conflict, the answer says so rather than quietly picking a side. If the sources do not answer the question, it says that too.
- **Hands over to a person.** The output is a draft with citations, ready for someone to verify the points that matter.
Source checking is the real product
Anyone can generate fluent text. The value of a research agent is in how it handles trust. A well-built one separates three things: what a source states, what the agent infers from it, and what remains unknown. It records where each source came from and when it was retrieved, and it flags material that cannot be traced back to anything.
Fresh news deserves special care. A model's built-in knowledge is not a news feed, and an agent should never present recent events as fact from memory. For anything time-sensitive, the workflow should require a verified primary source, such as an official publication, a regulator's page, or the company's own announcement, supplied or approved by you. No primary source, no claim. We deliberately do not use this article to report any current news for exactly that reason.
An illustrative example
Imagine a small logistics company that needs to compare the terms of several carrier agreements before renewal. The agent reads the contracts from the company's own document store, extracts the clauses on liability, delays and notice periods, and builds a side-by-side table with a reference to the exact clause behind each cell. It marks the places where wording is ambiguous. A manager then reviews the table, checks the flagged clauses, and decides.
The agent did not decide anything. It removed hours of searching and copying, and it made the checking faster because every statement comes with its location.
Where people still matter
Human checks are part of the design, not a patch. Someone should confirm the conclusions that carry risk, and the workflow should define who and when. Questions involving personal or confidential data also need an early decision about where the processing happens and which tools are allowed to touch it.
Note: this example is illustrative and not a client result. The data, tools and human checks are defined for each specific process.
Want to see what this could look like for your business?
Pragma AI builds and operates AI automation systems for Bulgarian small businesses, connecting real tools to your real data. If you have a recurring research or reporting task that eats your team's time, write to us. We will go through the sources, the checks and the workflow together and tell you honestly whether it makes sense to automate.