AI agents that lives in your stack, not on a vendor's roadmap. Shipped from Australian Capital Territory.

Our goal is to give Canberra businesses a three-day weekend, so people can spend more time with their families and the people they love :)

Canberra sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers - none of those are details our default AI agents template would catch.

What AI agents actually does

Autonomous AI agents that don't just answer - they get things done. They check inventory, draft proposals, file paperwork, and chase quotes while your team focuses on the human work.

  • 01 Goal-driven agents that complete multi-step tasks
  • 02 Connect to your tools - Xero, HubSpot, Gmail, Slack, your CRM
  • 03 Human-in-the-loop checkpoints for anything risky
  • 04 Full audit log of every action the agent takes

Built on: Claude Agent SDK OpenAI Agents LangGraph n8n MCP

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How AI agents compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKoala Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

Our field notes from Canberra builds.

  • Canberra runs on government, policy and the contractors that service them - AI here has to handle process and compliance as carefully as it handles speed.
  • Federal departments and the consultancies orbiting them generate huge volumes of documents, submissions and reporting. Canberra teams want AI that speeds up drafting and research without ever guessing on something that needs a citation.

We work with teams across Canberra: Civic · Belconnen · Woden · Gungahlin · Tuggeranong · Barton.

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How we build AI agents for a Canberra team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Canberra business, so value lands before the build is finished. AI agents that do work.

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How the work runs

The outcome for Canberra teams

The shape of the result for Canberra teams: Replaces 15+ hours of weekly back-office work per agent deployed. Built on Claude Agent SDK, hardened with the rest of the stack as it scales.

Not your typical AI agency.

Honest about what AI can and cannot do

Ships the one workflow that pays for itself

Hours given back, never the size of the invoice

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Koala Dynamics, that drops to about 52.

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*Based on 9 hours a week of admin at Koala Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

FAQ

How fast could we have AI agents in production?

Eight to ten weeks for most Canberra businesses. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.

What's the smallest engagement you'd take on?

A two-week paid discovery for Canberra businesses that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.

Can you walk us through a comparable build?

Yes - on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Replaces 15+ hours of weekly back-office work per agent deployed.

What if our Canberra doesn't have any data ready?

Most don't. Getting the data into shape - ingestion, cleaning, the lightweight contracts you need before any model is useful - is part of the engagement. For AI agents specifically, we typically run that work on Claude Agent SDK, OpenAI Agents, LangGraph, n8n, MCP and assume messy starting conditions from day one.

One short call.

Tell us what you're trying to fix. We'll come back inside a working day.

Talk to us about this

Tell us what you're trying to do and we'll reply with how we'd build it - no obligation.