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AI agents for business

We build AI agents that each do one job for a team from start to finish inside the tools your business has approved. A person checks the work and the team owns the agent after we leave.

What an AI agent is

An agent is an AI model set up to do one job from start to finish without a person typing prompts. It might prepare the weekly numbers or check what AI models say about your company or read a new brief against the brand's rules. It runs on a schedule and uses only the information it has been allowed and it leaves its work for a person to check. We build most of our agents on Claude because it follows written instructions closely and explains what it did. We work with whichever model your business has approved.

From strategy to a working agent

  1. We agree the job in one sentence and what information the agent may use and who checks its work.
  2. We write the instructions in plain English because the instructions are the agent and your team can read them and change them.
  3. We build it inside the tools your business has approved and run it beside the person who does the job today for two weeks.
  4. We hand it over with the instructions and a one-page guide and the count of hours it gives back.

What you get from an agent project

An agent that runs every week without anyone prompting it. The written instructions that your team owns and can change. A measure of the hours returned to the team counted in the second month when the novelty has worn off. The difference from most agent work is the hand-over. We leave nothing that only we can run.

What we count

The chart shows the measure we report for an agent. It is the hours a week returned to the team counted in the second month.

What the Monday numbers agent looks like
The three screens the team sees. Illustrative and kept deliberately simple.
1 · Upload this week's files
sales_week41.csv✓
orders_and_tickets.xlsx✓
marketing_export.csv✓
Drop a file here or connect a folder
Run the Monday numbers
2 · The agent runs Claude
07:00 Collected three files07:01 Matched 2,412 customers across sales and tickets07:02 Checked totals against last week07:02 Flagged: returns up 31% in one region07:03 Wrote the sheet and the note
Instructions: monday-numbers.md at 42 lines. Allowed data: the three files only. Checked by: the marketing manager before 9am.
3 · The dashboard
£412kSales up 4% on last week
31%Returns up in the North region
2,412Customers matched
3Lines to check
What moved this week: returns in the North region doubled after the Thursday promotion. The agent cannot say why. It has listed the 40 orders.
monday_numbers_w41.xlsxOpen

Three agents we have built

The Monday numbers

It pulls sales and customer and marketing data from the systems that hold them and then matches the records and checks the totals before leaving one Excel sheet with a note on what moved. It gives the team back six hours a week and it stays in use because the manager still checks it and the trust is hers rather than the machine's.

The AI answer monitor

Asks the main AI models a fixed list of questions about the company on a schedule the team sets. It flags any answer that changed and files the full set with its date. It gives the communications team a dated record nobody else holds and that is the point of difference. A change you can date is a change you can act on.

The brief checker

Reads a new brief against the brand's rules and last year's briefs and returns the questions a planner would ask before anyone books a meeting. It saves a round of meetings on every brief and because the questions are the team's own and written down the agent sounds like the team.

Each agent is described without naming the client.

Questions people ask us

Which AI model does Model Research build agents on?

We usually build on Claude because it follows written instructions closely and explains its steps. If your business has approved a different model we build on that. The agent is its written instructions so it is AI and platform agnostic and moves between models with small changes. The counting and the checks inside it are done outside the AI wherever possible.

Is our data safe with an AI agent?

The agent runs inside the tools your business has approved and uses only the data it has been allowed. That is written into its instructions. Nothing leaves the systems you already trust. We review this with your IT or security lead before anything runs.

What happens when an AI agent gets something wrong?

A person checks its work before anyone acts on it and the agent flags what it is unsure about rather than guessing. When it is wrong we change the instructions and that is a ten-minute edit rather than a rebuild.

Can our team change an AI agent after Model Research leaves?

Yes and that is the point. The instructions are plain English in a file your team owns. Changing what the agent does is editing that file.

Our details are on the contact page if you have a job in mind for an agent.