AI integration in Sydney
Complaints and claims are where a Sydney bank or insurer's customer promises are tested. The volume is high, the letters are long, and each case arrives with call notes, emails and documents that someone has to read before anything can be decided. A lot of skilled time goes on reading and drafting rather than on deciding what is fair, and the customer waits while it happens.
We build AI features that do the reading: summarising the case from notes, calls and documents, pointing to the relevant policy or product terms, and drafting a response that a case handler edits and signs. A person approves every reply before it reaches a customer. Every draft keeps a link to the source material it came from, so the handler can check any statement in one click, and we measure whether the feature shortens the time to a response before it is rolled out widely.
Sydney is where Australian money keeps its head office. Commonwealth Bank, Westpac and Macquarie run their groups from the city, the large insurers are here, and around them sits a dense fintech sector in payments, lending and wealth. The software these firms need is rarely a brand-new product. It is the work around the core: payment flows that settle in seconds, onboarding and lending journeys customers actually finish, reports that agree with each other, and the internal tools that keep claims and complaints moving.
Real-time payments have raised the bar. On the New Payments Platform money moves in seconds, and PayTo lets a business take agreed payments straight from a customer's account, so a lender or fintech built around overnight batch files now needs instant confirmations and a ledger that never records the same payment twice. Sydney is also where Atlassian and Canva started, so its buyers have been trained by good software built down the road. A clunky internal tool or a slow sign-up flow is noticed here in a way it might not be elsewhere. Beyond finance, the city has a large property and strata sector, online retailers shipping across a very big country, and a startup scene around Tech Central.
Hiring reflects all of that. Indeed puts the average base salary for a software engineer in Sydney at A$119,602, from 526 reported salaries, and experienced engineers are contested by the banks, the big product companies and every well-funded startup at once. A team that needs a payments engineer or an extra pair of senior hands for a quarter can wait a long time for the right hire. That is where we are useful: a defined piece of work, started 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; 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 whoever joins your team next inherits work they can read.
We are the right fit when you have a defined piece of work and want senior engineers on it within days, or when the Sydney hire you need is months away and the roadmap keeps moving. Start with a fixed-price two-week piece and judge us on the output. 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 Sydney teams.
How do you work with teams in Sydney?+
We are in Bengaluru and share four hours of live overlap with you every day, in your afternoon, moved to suit your team. That is when we join stand-ups, review pull requests and take design calls. 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. Between calls, progress is in your tracker and your repositories.
Do you build for Sydney banks, insurers and fintechs?+
Yes, and that is most of what Sydney asks us for. We build payment backends that handle NPP and PayTo without recording a payment twice, sign-up and lending journeys customers finish on their phone, complaint and claims tools that take the reading off skilled staff, and data pipelines that make finance and risk reports agree. We work inside your codebase and your cloud, starting with the one flow that matters most.
How does your rate compare to hiring in Sydney?+
Indeed puts the average base salary for a software engineer in Sydney at around A$120,000. 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 starts within days of the call. The first piece is a fixed-price two-week engagement at $2,800, so you judge us on what ships.
Can you take over an app another team built?+
Yes. It is a common starting point for Sydney products whose agency or founding engineers have moved on. We read the code, run it, and write down how it fits together and where the risks sit. The first fixed-price two-week piece is usually one real fix or feature, so you see the handover working while the architecture notes build up. The code stays in your repositories throughout, as it always would.
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.