Great Truck Repairs: a website and a COF queue system for a diesel truck workshop in West Auckland
A 24/7 diesel truck repair workshop in Te Atatū, Auckland. We built a website that turns calls into ready-to-quote jobs, and a simple system that runs the COF queue.
The problem
Heavy trucks in New Zealand need a Certificate of Fitness every six months, so a truck workshop always has a queue. Calls come in while the mechanic is under a truck, and every driver wants a price before they commit. On top of that, someone has to remember which truck is due for its COF and which one is still waiting for parts.
The website
We built it for drivers on the road. One tap calls the workshop, and a ready-made text books a pre-COF check. A short form takes the plate number and a description of the problem, so the owner can text back a ballpark price. Clear pricing and the list of West Auckland suburbs it covers help nearby fleet owners find the workshop on Google and call with confidence.
The COF queue
An AI bot and a shared spreadsheet now run the queue of trucks being prepared for their COF. Every truck sits in one list with its due date and status, so the owner and the team see the same picture.
What changed
Enquiries arrive with the plate number and the problem already written down, so a quote can go out by text within minutes. The COF queue has one home: a shared list everyone can check.
Sound familiar?
If your workshop runs on phone calls and memory, we can build the same setup for you. It suits any business with a queue of jobs: truck and car mechanics, auto electricians, panel beaters and fleet maintenance teams.
Aiona: Medical English, an AI-powered iPhone and Android app for doctors and nurses
Aiona teaches medical English to doctors and nurses who learned English as a second language. We co-founded it and designed the product. It is live on the App Store and Google Play, and people pay for it.
The problem
A doctor who moves to another country has to work in English from the first shift. They need to take a patient history and explain a diagnosis, often in a hurry. Many are preparing for the OET exam or already work in an English-speaking hospital. General language apps teach you to order coffee, and medical English courses rarely fit around night shifts.
The business had its own problem. The first version of the app taught general English and competed with every big language app. It needed a clear audience and a reason to pay.
The app
In September 2025 we rebuilt Aiona around one audience: people who work in healthcare. New users pick their specialty, level, native language and app language, and get a personal learning map. Lessons mix vocabulary cards, reading, quizzes and an AI chat that plays a patient, so a nurse can practise a real conversation before it happens on the ward.
Fixing the drop-offs
The analytics showed that many new users left during a sample exercise at the very start. We removed it and sent people straight to their learning map, and retention went up. A hard paywall caused the same problem: it asked for money before people saw what the app could do. We replaced it with a reverse trial and a free daily limit, so new users start with the full app and pay once they see the value.
What changed
Aiona now has a clear audience and paying users on both stores. Every product decision starts from the analytics and from journey maps for four types of users, from a nurse planning to move abroad to a doctor who already works in English.
Sound familiar?
If you have an app idea for a specific audience, or an app where people sign up and then disappear, we can help. We work on the parts that decide whether an app earns money: the audience, the onboarding, the pricing model and the analytics behind it. It suits edtech and training apps, and any app that runs on subscriptions.