Canberra · Australia
Architect, former real estate advisor, now building the systems businesses run on.
Story
Spain, Nepal, California, Australia. Open any year.
Turning what I built inside the clinic group into modular automation other multi-site operators can deploy — dental, physio, psychology, GP, allied health.
An item-code optimiser that recovers $5–15K a month in missed billing. A content engine that runs unattended. Reporting that builds itself.
We moved to Canberra when my partner took a clinical management role here, and I joined the same group on the operations side.
Twenty-plus staff and every process held together by spreadsheets and memory. I started automating pieces of it to survive my own workload, and ended up designing and building the entire operations and AI stack — on my own, while running the day-to-day.
I'm not there any more, and all of it is still running.
My partner suggested Australia — we had to enter before turning thirty to qualify, so we went. A year in Sydney: sales director at a carbon consultancy, then sales and marketing for an events business.
It taught me to explain a technical idea to someone with no interest in the technology and every interest in the result. That turns out to be most of the job when you're the person introducing AI into a business.
My partner and I started a small botanical care business in Valencia and ran it for a year.
Alongside it I took on the family property portfolio — and later built its software myself: a bilingual owner portal where owners see their properties and financials directly, plus an intake agent that reads documents and books maintenance jobs and owners' meetings. Still running today.
COVID made me want a change, and an American developer took me on. On site I supervised and coordinated the renovation works. Off site I coordinated the team still working from Valencia — marketing, the rentals side, the designer — across a nine-hour time difference.
It's where I learned to run a project without being in the room with the people doing it.
It ended over visas. Continuing would have meant staying on the wrong side of the rules, and I wasn't willing to do that, so I came home.
Comparative market analyses. Winning and maintaining listings. Qualifying buyers against real financial capacity. Contracts and paperwork. Campaigns.
Three years of doing, by hand, almost every task an agency later asks someone to automate. I learned the part of real estate no drawing teaches you: it's a business of a hundred small, repetitive, deadline-driven jobs, and the people doing them are almost always underwater.
I did my final university project in Gahare, Nepal — not on paper. Five months coordinating phase two of a primary school rebuilt after the earthquake: two classroom buildings on split levels, retaining walls, landscaping, leading volunteers from six countries. Traditional bioconstruction combined with seismic-resistant methods.
No budget padding, no consultants, no safety net. It's still the most complete design-to-build project I've been part of, and it's where I learned what a system costs when it fails.
Back home I co-founded a small practice — a town hall building, a penthouse renovation, a residential development. Concept to site.
How to hold an entire system in your head, and how a change in one place moves through everything else. Structure, sequence, constraint, tolerance, dependency.
The vocabulary is identical when you're designing an automation layer instead of a building.
Work
Designed, deployed and handed over by me. Open any entry.
Three people used to sort a shared inbox every morning. The agent classifies each message by location and intent, routes it, and drafts a reply where one is needed.
It never sends on its own. A person approves — and the system records whether they agreed or overruled it, so it improves and accountability stays human.
n8n · Gemini · Gmail API · structured output parsing · approval step
The platform at the centre of the business had no usable API — by design, because the vendor sells the lock-in. I didn't fight it and I didn't replace it. I built around it: scheduled structured exports, a small extraction service, a normalisation layer.
It ran every day for two years, and every dashboard and agent was fed by it.
Headless extraction · scheduled exports · ETL service · Docker
Timesheet ingestion, healthcare award interpretation, exception flagging, payroll-ready output across six locations.
The forty-five minutes left are deliberate: a person reviews the exceptions with everything already assembled. Automating that last mile would be reckless, not clever.
n8n · MYOB integration · award rule engine · exception queue
Built for the portfolio I still look after. It takes documents in by email or chat, reads multi-page files, works out what they are and files them — and where the content implies an action, it creates the calendar entry.
Nothing is committed without a person confirming. Absorb the routine volume, surface the decision, keep someone accountable for the call.
n8n · multi-page document reading · chat + email intake · calendar actions
Owners log in and see their properties, documents and financial position directly, instead of waiting for someone to assemble a monthly report. Data model, authentication, interface and hosting, all mine.
Small on purpose. The point is that owner reporting stops being a recurring manual task and becomes a live surface.
Custom web app · authentication · bilingual ES/EN · Docker · self-hosted
Reads completed treatment records against the item code schedule and flags what was delivered but never billed, or billed under the wrong code.
No new sales, no price increase. Recovered margin on work already done.
Structured extraction · rules + LLM validation · exception reporting
Chair utilisation, recall rate, revenue per patient, treatment acceptance, new patient count — per site and consolidated. Nobody compiling spreadsheets on a Friday.
Leadership stopped asking for reports and started asking better questions. That was the actual return.
ETL pipeline · Supabase · dashboard layer · automated distribution
Supplier invoices arrive, get matched against expected purchases, checked for duplicates and approved automatically below a set threshold. Anything unusual goes to a person with the reason attached.
Document parsing · supplier matching · duplicate detection · approval routing
Ideas generated from a configurable brief, drafted in a defined voice, pushed to a phone for a yes or no, then scheduled and published.
The pattern generalises straight to property copy, suburb market updates and campaign variants.
n8n · LLM generation · Telegram Bot API · Sheets config · scheduler
Containerised services behind a reverse proxy with automatic TLS, on a server I administer. No per-seat tax on the automation layer, no vendor holding the data.
Maintained like production, because it is: every workflow backed up to version control nightly, and a daily report listing any failure with a direct link. Automation nobody is watching is just technical debt with better marketing.
Docker · Traefik · Linux · self-hosted n8n · Supabase · nightly Git backups
Method
Six habits that decide whether an automation is still running a year later. None of them are about the technology.
A week sitting beside the people doing the work, timing the process as it actually happens — not a workshop. What people describe and what they do are never quite the same thing, and the gap between them is where the automation goes.
Small on purpose, and visible to the people who feel the pain. Nobody should have to take automation on faith for a quarter. The first win buys the trust that pays for the harder work behind it.
Highest volume, clearest rules, fewest people to convince. That's the fastest, lowest-risk win — and it produces the clean data the next system will need anyway.
Most software a real business runs on was never built to be integrated. So the question is never whether a platform has an API. It's what a human can do inside it, and how a human gets data out of it today. Whatever that answer is — a report, an export, a screen — that's the door.
Handle the repetitive band completely, then put a person on the edge cases with the context already assembled for them. Speed everywhere it's safe, judgement everywhere it isn't.
Infrastructure, data, IP and credentials belong to the business — not to me, not to a vendor. Backed up nightly, failures reported daily, one page a week in plain English. Automation nobody is watching is just technical debt with better marketing.
Toolkit
Contact
The most useful first conversation is you describing the process that hurts most, and me telling you honestly whether it's a two-week build or a two-quarter one.