Automation projects fail when they start with the technology. Ours start with a timesheet. We look for the tasks that happen often, follow rules, and involve moving information from one place to another. Those are the tasks where a language model plus a bit of engineering pays for itself in weeks.
The result is usually invisible to your customers and obvious to your staff. Quotes that draft themselves from a photo and a form. Documents read and filed without a human opening them. Records matched, flagged and escalated only when they genuinely need judgement.
We are deliberately conservative about where AI belongs. Anything that must be exactly right gets deterministic code and validation. The model handles the parts that need language and judgement, and everything it produces is checkable.
We are based in Canberra and most of the businesses we automate for are too: trades and suppliers in Fyshwick and Mitchell, offices in Civic and Barton, and family businesses from Belconnen to Queanbeyan. The question we start every job with is a simple one: can it be done with AI, before you pay a large firm tens of thousands of dollars to do it the old way? Usually it can, and when it cannot, we will say so.
What is included
Workflow audit
A short, honest list of the tasks worth automating, ranked by hours saved against build cost, including the ones we recommend leaving alone.
Custom pipelines
Purpose-built automation for your process: intake, extraction, classification, generation and routing, with human review where it matters.
Integrations
Connections into the tools you already use, including email, CRMs, job management, accounting, storage and internal databases.
Guardrails and fallbacks
Validation, rate limiting, cost controls and a defined behaviour for when the model or an API is unavailable, so the process degrades rather than breaks.
Monitoring
Logging and alerting so you can see what ran, what it cost, and what it got wrong, rather than trusting a black box.
How we work
- 01
Find the hours
We interview the people doing the work and quantify the current cost of the task in real minutes per week.
- 02
Prototype fast
A rough version running on your real inputs within days, so you can judge accuracy on your own data before committing to a full build.
- 03
Harden it
Validation, edge cases, retries and the boring reliability work that separates a demo from something you can leave running.
- 04
Deploy and measure
We ship it, watch it for a few weeks, and report the actual time saved against the estimate.
Automation we have built
- A quoting estimator that reads customer-submitted photos and produces a priced estimate for a removals business
- A product description engine that writes consistent, accurate listings for a high-volume auction house
- A sourcing engine that matches auction results against supplier catalogues and ranks them by margin
- Bank statement reconciliation that matches payments to expected charges and flags only the exceptions
- Automated marketing videos: the business sends in raw footage once, and finished, captioned posts go out to every platform each week
What we will tell you not to automate
If a task happens twice a month, or the rules change every time, automation usually costs more than it returns. We would rather say so in the first meeting than sell you a build.
The same goes for anything where an error is expensive and hard to detect. In those cases we automate the preparation and leave the decision with a person.
Frequently asked questions
Which AI models do you use?
Whichever fits the job. We regularly build on Claude and OpenAI models, and use smaller or self-hosted models where cost, latency or data sensitivity calls for it. The choice is an engineering decision, not a loyalty one.
Is our data used to train models?
No. We use API tiers that exclude your data from training, and for sensitive work we can keep processing local. We will tell you exactly where your data goes before anything is built.
What does AI automation cost to run?
Model usage is billed per request, so cost tracks volume rather than a flat licence. We measure the real running cost during the prototype and give you the figure before you commit to a full build.
What happens when the model gets it wrong?
It will, occasionally. Every build has validation, a confidence threshold and a human review path for anything the system is not sure about. Errors surface rather than silently propagate.
Can you automate something in a tool we already pay for?
Often, yes. If your existing software has an API we will use it. Rebuilding a tool you already own is usually the wrong answer.
How much does it cost?
Work is charged from $120 per hour. For a defined project we estimate the hours after a free discovery call and give you a fixed quote, so you know the total before anything starts.
Related work
Auction House
Every small business owner has heard that they need to post consistently. Very few do, because filming is the easy part. Editing, captioning, resizing for each app and remembering to publish is the part that never happens. We built a system that takes that part away entirely: the owner emails their raw footage to one dedicated address, and the system designs the content and distributes it to the platforms they have chosen, on schedule.
Read the case study →AI SolutionsPrivate Client
A bespoke AI feature built into a removals company’s quote form: the customer uploads a few photos of their rooms, and a vision-capable AI model estimates the total moving volume in cubic metres, itemises the goods it can see, and instantly sizes the right truck, replacing manual inventory counts and in-home surveys with a quote that takes seconds.
Read the case study →AI SolutionsAuction House
A bespoke AI-assisted description generator for a busy auction house, staff upload item photos, a vision-language model drafts a professional listing in seconds, and experienced staff review before publication, combining AI speed with human quality control.
Read the case study →AI SolutionsPrivate Client
A bespoke AI system for a second-hand goods retailer that learns from their own sales history, automatically categorises every product line, and continuously surfaces the highest-ROI restocking opportunities from global wholesale marketplaces, replacing hours of manual research with a ranked, ready-to-act shortlist.
Read the case study →PerspectiveMedia Canberra
I spent the best part of a decade and a half at The Auction Barn, and one of the biggest things I took away was just how many hats you end up wearing when you’re running or managing a business. When you’re busy, the day-to-day stuff has a habit of taking over.
Read the case study →Next projectYours
We are taking on new AI Automation work now. Tell us what you are trying to fix and we will tell you honestly whether we are the right people for it.
Start the conversation →Want to try this yourself first?
Map your customer journey, automate the boring touchpoints and keep a human at the moments that matter, in your own voice.
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