AI integration in Melbourne
Melbourne's SaaS companies are under pressure from their own customers to add AI features, and the customers asking loudest are also the most careful. They want to know that one customer's data never turns up in another customer's answer, that the feature is right often enough to trust, and that someone can see what the model was shown. A feature built in a hackathon rarely has good answers to any of that.
We build AI features into SaaS products with those answers designed in: retrieval scoped strictly to the tenant, evaluation sets drawn from the questions your users really ask, and logs that show what the model saw and said. We measure whether the feature actually saves users time before it ships widely. On FM360 we run a weekly summary written by Claude, and the lesson we kept is that trust comes from every figure being checkable.
Melbourne's software market is built on products rather than projects. SEEK, REA Group and MYOB run from the city, Culture Amp started here, and a generation of engineers learned their trade inside marketplaces and SaaS businesses that sell well beyond Australia. The SaaS companies we hear from have usually found their market and are now paying for early decisions: a data model that assumed one customer type, permissions that started as a role column, and infrastructure in a single region when their newest customers are in the US or Europe.
Health and education are the other two pillars. The Melbourne Biomedical Precinct around Parkville brings together hospitals, research institutes, biotech firms and universities, and they need registries, trial platforms, patient apps and operational tools that handle sensitive records carefully and still suit a busy clinician between patients. The universities (Melbourne, Monash, RMIT and the rest) run student systems, learning platforms and research data at a scale that rarely fits off-the-shelf software, and their students judge every portal against the apps on their phones. And the Port of Melbourne keeps a large freight and logistics industry busy, much of it still run on email and spreadsheets.
Hiring costs a little less than in Sydney. Indeed puts the average base salary for a software engineer in Melbourne at A$109,570, from 329 reported salaries, and the engineers who have already scaled a product are the ones every scale-up wants at the same time. A platform problem can sit on the roadmap for quarters while that hire is found. That is where we fit: senior engineers on a defined piece of work within days, with the code in your repositories from the first commit.
Our four hours of daily overlap land in your afternoon, and we move them to suit your team. Your morning stays with your own people, and the afternoon is when you talk to the engineer writing your code, in stand-ups, reviews and design decisions. Runbooks and architecture notes are written as we go, so the work stays readable long after the engagement ends.
We are the right fit for a platform problem your product team has no time for, a defined piece of work with a clear end, or the months before your own hires start. Senior engineers arrive within days, the first piece is a fixed-price two weeks, and agencies can put the work under their own name.
Four ways this arrives.
A prompt that behaved on twenty hand-picked inputs meets ten thousand real ones. We build the evaluation set from your actual traffic first, so a change can be judged rather than argued about.
Usually a large context sent on every call, or a big model doing a job a small one can do. We measure where the tokens go before recommending anything.
Logging that captures the prompt, the retrieved context, the model version and the output, so a support question has an answer that is not a guess.
A fallback path, a timeout that is shorter than your user’s patience, and a degraded mode that is honest about being degraded.
A weekly maintenance pulse where Claude writes only the prose, checked against a JSON schema and a whitelist of numbers, with a template that takes over when the model fails.
Read the write-up →Asked by Melbourne teams.
How do you work with teams in Melbourne?+
We are in Bengaluru, and four hours of every working day overlap with your afternoon, moved to suit your team. Stand-ups, code reviews and design calls happen live in that window, so your mornings stay with your own people. We work in your tools, whether that is Slack, GitHub or Linear, and the person on every call is the engineer who writes the code.
Do you build for Melbourne SaaS and marketplace companies?+
Yes, and it is the work Melbourne asks for most. We untangle data models that assumed one customer type, turn a role column into proper permissions, add single sign-on and a second region for the first large overseas customer, and tune search and messaging for marketplaces that have outgrown their first version. We work inside your codebase, alongside your product engineers, starting with whatever is slowing them down most.
How does your rate compare to hiring in Melbourne?+
Indeed puts the average base salary for a software engineer in Melbourne at around A$110,000. Our published rate is $35/hour with a $5,000 minimum, or $5,400 a month for one embedded engineer. There is no recruiting time and no employment overhead, and work can start within days of the call. The first piece is a fixed-price two-week engagement at $2,800, so you can judge us on what ships.
Can you work white-label for a Melbourne agency?+
Yes. If your agency wins more build work than your developers can carry, we work under your name. Your client sees your team and your process, we join calls as your engineers, and the code goes into your client's repositories from the first commit. You keep the client relationship. An NDA is signed before you share anything specific, and the runbooks and architecture notes are written as we go.
Will you tell us if we do not need a model?+
Yes, and it happens often. Several requests we have taken turned out to be a search problem, a rules engine, or a form with better defaults. We would rather say that in week one than bill for a year of prompt tuning.
Whose API keys?+
Yours, in your accounts, with the spend visible to you. We never proxy your traffic through infrastructure we control.
What about our data going to a provider?+
We map exactly what leaves your systems and where it lands before anything is wired up. Where that is not acceptable, self-hosted open-weight models on your own hardware are a real option and we will price both.
Do you fine-tune?+
Rarely, and not as a first move. Retrieval and prompt structure fix most of what people bring to us as a fine-tuning problem, at a fraction of the cost and with none of the retraining treadmill.