A workforce for the work that keeps landing on you.
AI agents for business, staffed the way a well-run firm staffs a desk. Each one is named and given one job, a boundary and someone who checks its work. We install them inside your business, trained on how you already run it, and every morning they report to you.
What AI agents for business are actually for.
Most owners reading about AI agents already know the problem: the calls returned at nine at night, the quotes that wait for Sunday, the invoices nobody chases. None of it needs your judgement. All of it waits for you anyway. The work is staffed; you just happen to be the staff.
An AI workforce takes that work off your desk, one job at a time: a small team of AI workers, installed, briefed and checked, doing the routine so you can do the parts that need the owner.
What an AI agent is, in our model.
Every system we install has two layers. The AI brain watches the business and decides what matters. The AI workforce acts on those decisions. An agent is one member of that workforce, and before it does any work it has three things.
One thing, done well
It answers the phone, or drafts the proposal, or chases the invoice. One job, with a clear finish line. An agent that does everything is an agent nobody can check.
What it never does
The receptionist books appointments and never quotes a price. The invoice chaser sends reminders and never writes off a debt. The boundary is set with you during the build, and it lives in the system rather than in a hope.
Someone who checks
Every agent answers to a rule or a person. Routine work runs on the rule. Anything outside it comes to you, or to whoever you name, before it goes anywhere.
What one does depends on the business. In a plumbing firm, the receptionist takes the burst-pipe call at seven in the evening, books the job and texts the plumber on call. In a law practice, it takes the enquiry and puts the details in front of a lawyer for a conflicts check. In a marketing agency, the proposal drafter turns a discovery call into a first draft, and the account lead signs it off.
The AI workforce a Foundation ships with.
Every Foundation starts with a first AI workforce, built around the bottlenecks the Intensive found. Most draw on these five roles, and the right mix gets scoped during the AI Strategy Intensive.
The receptionist on the line
Answers every call you miss, day and night. Qualifies the caller, books the job and puts the urgent ones through to a person.
The lead responder
Replies to every new enquiry inside sixty seconds, on the channel it arrived on. Qualifies first, then books the conversations worth your time.
The proposal drafter
Reads the contact history and the call notes, pulls the right pricing and drafts the proposal in your format. A person reads it before it leaves.
The invoice chaser
Polite, escalating and on schedule. Reminders go out on the rules you set, and anything disputed comes straight to you.
The daily brief
The brain's report on the whole workforce. Sales, cash, the overnight work and the decisions that need you, on your phone at seven.
Every role has its own page under solutions by outcome, with the detail of what it does and what it hands back.
AI agent examples from real service businesses.
Ian · AVIT Properties · London
Ian used to spend 80 working hours each reporting cycle pulling data from email, utility accounts and Google Drive by hand. Now the workforce drafts the full report and flags what needs a human eye. He spends two hours checking it instead of building it.
Ray White Milldale · Real estate
The office runs Speed to Lead. New enquiries get a reply from the lead responder within the first minute, day or night, and the conversations worth having land in the salespeople's calendars.
Brass Butler · Auckland
We run our own firm on the same model, on Claude, every day: enquiries, proposals, client onboarding and the morning brief. Titus reviews; the workforce does the rest.
Agent, chatbot or automation: what you actually need.
Owners use the three words interchangeably. They are not the same thing, and the difference decides what you should pay for.
A fixed rule
When this happens, do that: send the reminder on day seven. Cheap, reliable and exactly as clever as the rule. Most of a good install is still this.
A window that waits
Sits on a website and answers questions when someone types. It cannot do the work, only talk about it, and it has no idea what happened in your business yesterday.
A worker with a job
Reads the situation, decides within its boundary and acts: books the job, drafts the reply, chases the payment. It uses judgement, so it needs a reviewer.
Most businesses need all three in the right places, and fewer agents than the market suggests. If you're brassed off with a chatbot that answered questions nobody asked, that's why: it was a talker doing a worker's job. The Intensive sorts which work needs which.
Nothing goes out without a rule or a person.
This is the part most AI agent pitches skip. An agent that can send, book or charge on its own is a liability, so every workforce we install runs behind a review layer.
Nothing is sent, booked or paid without a rule that allows it or a person who approved it. Routine work inside the rules runs on its own. Anything outside them lands as an approval, a short card with the draft and the reason, and waits for a yes. You choose what needs you, and you can tighten it whenever you like.
Then the morning brief. Every day at seven, the brain reports what the workforce did overnight, what it booked, what it sent and what is waiting on a decision. The top brass, briefed, and nothing done behind your back.
Agentic AI, in plain English.
Agentic AI is the industry's name for AI that takes actions rather than only answering questions. Give a language model tools, such as your calendar, your CRM or your inbox, plus a goal and some rules, and it can work through a task in steps: read, decide, act, check. That is all the word means.
The hype says agentic AI will run your company. It won't, and you wouldn't want it to. It does bounded work with a clear finish line well, which describes most of the routine in a services business. In our installs, it simply means the workforce.
Software workers that do a defined piece of a business's work: answering calls, replying to leads, drafting documents, chasing payments. In our model each has one job, a boundary and a reviewer. An agent acts, where a chatbot only talks.
Fewer than you'd think. Most Foundations start with two or three, aimed at the work that costs the owner the most hours or revenue. More follow once the first have earned their place. The AI Strategy Intensive tells you which ones, and in what order.
That isn't what they're for. They take the repetitive layer underneath your people's work, not the judgement. In most installs the team keeps its roles and stops doing the chasing, the re-keying and the after-hours phone.
The review layer catches it before it reaches anyone, or it happened inside a rule you set and the fix is changing the rule. Every action is logged, and we tune the agents after go-live on exactly what they get wrong.
You do. Every Foundation is yours from handover: the code, the IP, the documentation and the accounts it runs on. From there, most owners keep us on and the workforce is kept polished, with new agents added as new bottlenecks show up. More on life after handover.
With a 30-minute discovery call. If there's a fit, the next step is the AI Strategy Intensive: two hours one-to-one with Titus, a written audit and a prioritised plan, $797, money-back, and credited in full to the build. For the wider picture, read how our AI consulting works, or how we work.
Hire the first one on purpose.
Most owners don't need a fleet of agents. They need the right first one, on the work that costs them the most, with someone checking it. The discovery call is where we work out which one that is.
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