AI Agents
Intelligent systems that work autonomously to handle complex business tasks, freeing your team to focus on strategic initiatives and customer relationships.
What Building an AI Agent Actually Involves
Most AI agent projects fail for unglamorous reasons. Nobody wrote down what the process really was, nobody agreed what the software was allowed to decide on its own, and it went straight to live customers without ever being run alongside a human. Here is the sequence we work through instead, and roughly where each part sits in a typical build.
Process mapping
Week 1We sit with the people who actually do the work and write down what happens today, click by click. Which inbox the request lands in, who reads it, what they check before they act, where they go looking when something is unclear, and what they do when it does not fit the usual pattern. Most of the value of an agent build comes out of this step, because it is where the undocumented rules that live in one person's head finally get written down.
Rules, exceptions and escalation
Week 1 to 2An agent is only safe when you have decided in advance what it must never do on its own. We agree the decision boundary with you: which cases it handles end to end, which cases it prepares and a human approves, and which cases it hands straight to a person without touching. We also set what happens when a system it depends on is down, so the fallback is a queued task rather than a silent failure.
Connecting your systems
Week 2 to 3The agent reads from and writes to the tools you already pay for. That usually means your email, your calendar, your accounting package, your CRM or job management system, and whatever spreadsheet is quietly holding the business together. We connect with scoped credentials limited to the exact permissions the job needs, never a shared login, and we document every field that moves in either direction.
Build and test in a sandbox
Week 2 to 4We build against copied data and test accounts, never your live records. That lets us run the awkward cases deliberately: the duplicate customer, the invoice with no purchase order, the email that is three requests in one message. You see the agent handle them before it is anywhere near a real customer.
Parallel run
1 to 2 weeksThe agent runs beside your existing process rather than replacing it. Your team keeps working as normal, and each day you compare what the agent produced against what a person produced. This is where trust is earned or the rules get corrected, and it is the step most rushed AI projects skip.
Go live, then watch it
OngoingWe cut over, then monitor closely through the first weeks. Every action the agent takes is logged with the reasoning behind it, so when someone asks why a particular request was handled a particular way, there is an answer. As your business changes, the rules change with it.
Problems AI Agents Solve for Australian Businesses
The best candidates for an agent are the jobs your team already finds tedious: high volume, rule driven, and dependent on information that already exists somewhere in your systems. These are the patterns we are asked about most often by Australian small and medium businesses.
A trades business drowning in after-hours enquiries
How it works today
Enquiries arrive by email overnight and sit unread until someone opens the inbox at 7am. Half of them are quoting requests that go cold before anyone replies.
With an AI agent
An agent reads each message as it arrives, works out whether it is a new job, an existing customer or a supplier, pulls the job history if there is one, drafts a reply and books the site visit into the calendar. The owner approves the drafts over coffee instead of writing them from scratch.
An allied health clinic re-keying referrals
How it works today
Referrals arrive as PDFs and faxes. Reception types the patient details into the practice system by hand, and any typo becomes a billing problem weeks later.
With an AI agent
The agent extracts the details, checks them against the existing patient list, flags anything ambiguous for a human, and creates the record. Reception reviews rather than retypes.
A wholesaler chasing overdue invoices
How it works today
Someone runs an aged receivables report when they remember to, then writes the same four chase emails over and over, and the awkward calls get put off.
With an AI agent
The agent watches the ledger daily, sends the polite reminder on day one overdue and the firmer one later, escalates genuinely difficult accounts to a person with the full payment history attached, and stops chasing the moment a payment lands.
A services firm reporting to a board every month
How it works today
Two days at the end of every month are lost to pulling numbers out of four systems into a spreadsheet, and the pack is always slightly out of date by the time it is read.
With an AI agent
The agent assembles the same pack on a schedule, pulling live figures and flagging anything that moved more than expected, so the finance lead edits the commentary instead of rebuilding the numbers.
A retailer answering the same questions all day
How it works today
Staff answer the same twenty questions about stock, delivery times and returns across email, the website form and social messages, and answers differ depending on who replies.
With an AI agent
The agent answers from your actual policies with one consistent voice, and passes anything about a complaint, a refund dispute or a vulnerable customer straight to a person.
What It Costs
Agent builds are scoped and quoted at a fixed price after discovery. We do not publish a price per agent, because two businesses asking for the same thing on paper can be a fortnight apart in effort depending on the state of their data and how many systems have to be touched.
The consulting and scoping work that sets that scope is priced clearly. A focused engagement is $1,000, a standard engagement is $3,000, and a broader strategic engagement is $10,000. You come out of it with a written scope and a fixed build price, and you are free to take that scope elsewhere if you would rather.
Initial consultations are free for businesses with 20 or more full-time staff (smaller teams pay $200 including GST). If part of your solution is a voice agent answering the phone, those run on a published subscription: Starter at $299 per month plus $499 setup, and Pro at $599 per month plus $999 setup.
How Long It Takes
A single agent handling one clearly defined process typically goes live in four to eight weeks, and that figure includes the parallel run rather than stopping at the day the code is finished. Simple builds against systems with good APIs can land sooner.
Builds that span several systems, or that need real data clean-up before anything can be automated reliably, run longer. We would rather tell you that at the start than discover it in week six.
Where a programme covers multiple processes, we sequence them. The first agent goes live and proves itself before the second is started, so you are never carrying a large unfinished build on faith.
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