AI Agents
Intelligent systems that work autonomously to handle complex business tasks, freeing your team to focus on strategic initiatives and customer relationships.
What Can AI Agents Do?
Our AI Agents are like having highly skilled digital employees that never sleep, never make mistakes, and continuously learn from your business processes.
Email Processing
Automatically sort, categorize, and respond to emails based on content and priority
Customer Support
Handle customer inquiries with intelligent responses and escalation protocols
Scheduling & Coordination
Manage appointments, meetings, and resource allocation automatically
Report Generation
Create detailed reports from data analysis and business metrics
Key Benefits
How AI Agents Work
1. Analyze
AI agents continuously monitor your systems and incoming tasks
2. Process
Intelligent decision-making based on your business rules and data
3. Execute
Complete tasks and update systems with full audit trails
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.
When an Agent Is the Wrong Answer
Plenty of work is a poor fit, and saying so early saves everybody money. We would rather turn down a build than deliver something that quietly damages your reputation with your own customers.
Judgement calls that carry real consequence
Hiring decisions, dismissals, credit refusals, clinical judgements and anything touching a vulnerable person belong with a human being who is accountable for the outcome. Software can gather the information and prepare the file. It should not make the call.
Processes nobody has agreed on
If three people do the same job three different ways and each is convinced theirs is correct, automation will simply pick one and make the disagreement permanent. Settle the process first. That conversation is often worth more than the automation was going to be.
Volumes too low to justify the build
A task that happens twice a month and takes ten minutes is not worth a project, however irritating it is. We will tell you when the arithmetic does not work, and occasionally the right recommendation is a better template or a tidier checklist.
Data that is not ready
Where records are duplicated, incomplete or contradictory, an agent will act confidently on bad information and spread the error faster than a person would. Cleaning that up first is unglamorous and it is usually the highest value week of the whole engagement.
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.
Work We Have Published
We would rather point at named work than quote invented numbers. Three published examples of the kind of automation described on this page:
Reignite Health
An AI receptionist handling inbound calls for a healthcare practice, including bookings and enquiries, with escalation to human staff where it matters.
Firebox Australia
A customer rewards integration wired into an existing ecommerce platform, so the programme runs without manual administration behind it.
Nutrition Science Group
Automation work delivered for an Australian business, connecting the systems the team already used rather than replacing them.
Frequently Asked Questions
What is the difference between an AI agent and a chatbot?
A chatbot talks. An agent acts. A chatbot can tell a customer your returns policy, but an agent can read the order, check whether it is inside the returns window, create the return in your system and email the label. The distinction that matters commercially is whether the software finishes the job or just hands it back to a human.
Will an AI agent make decisions we cannot see?
No. Every action is logged with the inputs it used and the rule it applied, and you decide in advance which categories of work it may complete on its own versus prepare for a human to approve. If you want every outbound email approved by a person for the first month, that is a configuration choice, not a rebuild.
Do we need to replace our existing software?
Almost never. The agent works on top of what you already run. If your systems have an API we connect to it directly. If they do not, there is usually still a workable path through scheduled file exchange, email parsing or database access. We work that out during discovery, before you commit to anything.
What happens when the agent gets something wrong?
It gets caught in the parallel run, or it gets escalated. Agents are built to recognise their own uncertainty and hand off rather than guess, and the escalation path is agreed with you up front. When a mistake does slip through, the log shows exactly which rule produced it, so the fix is a specific correction rather than a mystery.
How much does an AI agent cost?
Agent builds are scoped and fixed-priced after a discovery session, because the honest answer depends on how many systems are involved and how messy the data is. Consulting and scoping engagements run at $1,000 for a focused piece of work, $3,000 for a standard engagement and $10,000 for a broader strategic one. Initial consultations are free for businesses with 20 or more full-time staff (smaller teams pay $200 including GST).
How long before we see anything working?
A single well-defined agent handling one process usually goes live within four to eight weeks, including the parallel run. Broader programmes covering several processes take longer, and we would rather sequence them one at a time so you get value from the first before committing to the next.
Who owns the agent once it is built?
You do. The build, the configuration and the documentation are yours. We are not interested in holding a client hostage through a system nobody else can understand, so everything is written up in plain English as part of the delivery.
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