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AI development

AI Development Company in Australia

Most of what gets sold here as AI development is a team of five with one person who has shipped, and a bill that reflects the other four. This is the opposite arrangement: the engineer who scopes it is the engineer who builds it, the price is fixed before anything starts, and you pay nothing until a checkpoint is delivered and you accept it.

Australia has the rare combination of high willingness to pay and a thin local pool of engineers who have run production AI infrastructure. Most teams are choosing between an expensive local consultancy and an offshore arrangement in a timezone that makes daily contact impossible. India is the exception: the working day overlaps almost entirely, so this behaves like a local engagement rather than an overnight handoff.

What you get

  • One senior engineer end to end: the person on your first call architects it, writes it and hands it over
  • LLM features, retrieval over your own documents, agents that call real tools, and voice where it earns its place
  • Deployed in your own cloud account in a regional data centre, or on your own hardware where residency demands it
  • Fixed price and fixed scope agreed in writing before work starts, invoiced per accepted checkpoint
  • Code and infrastructure in your repository and your accounts, written to make us replaceable on purpose
Working builds from $1,000. Full production systems from $12,000.

Nothing payable upfront. You hold every dollar until a checkpoint is delivered and accepted, and thirty days of defect correction is included. Final scope and price are settled on a call before any work begins.

Invoiced in USD or AUD, payable by Wise or bank transfer.

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You speak to the engineer who does the work. No sales rep, no deck.

No spam and no sales team. You talk directly to Neeraj.

Architecture diagram of orchestrated AI agents with an MCP harness: a product on web, mobile or Slack sends a request to a central orchestrator that runs the flow step by step, consults a model router across Claude, GPT, Gemini and open-weights models, and hands work to a research agent, an action agent and a review agent. Every tool call passes through one MCP harness that enforces permissions, retries and logs before reaching the CRM, the database, email and calendar, or your internal API. Evals, tracing and replay, and cost per request run alongside.
One orchestrator runs the flow, and every tool call goes through the same MCP harness, so permissions, retries and logs live in one place.
How you pay

Get it built at $0.

That is not a discount. It is when you pay. The work is split into checkpoints with acceptance criteria written down before anything starts, and each checkpoint is invoiced only after you have seen it and accepted it. No deposit.

$0 to start
You hold every dollar until a checkpoint is delivered and you accept it. No approval, no invoice.
Fixed cost, unlimited features
Or hire the team outright: one fixed monthly cost, unlimited feature development, any stack.
The engineer takes your call
The person on your first call is the one who architects and writes it. No account managers, no bench time.

A US agency quotes $50,000 to $150,000 for the same build and asks for 40 to 50% of it before a line is written. Account managers, project managers, sales commission and bench time. None of it appears in your product.

How it works

Three stages, nothing hidden.

01

Twenty-minute call

You talk to the engineer who will build it. We scope the problem, and if this is the wrong fit for you, you get told so on that call rather than three weeks into a proposal.

02

Fixed proposal in 48 hours

Fixed price, fixed timeline, defined deliverables, in writing. No hourly billing, no open-ended scope, and no change-request business model.

03

Checkpoints until it ships

Working software at each checkpoint, with acceptance criteria agreed before that checkpoint starts and an invoice only after you accept it. Direct access throughout, not a ticket queue.

Working in Australia

What actually applies here.

Regulation and data

Government and health-sector buyers in Australia commonly require that data stays onshore, and that requirement is passed down to whoever supplies them. Once it appears in a tender or a customer contract, a hosted model API is off the table and the only workable answer is inference running on infrastructure inside the country.

Contracting and payment

You contract with an individual consultant based in India. Invoices in AUD or USD, paid by Wise or bank transfer. Your accountant handles an overseas supplier in the usual way, and any documentation they need is provided up front.

Working hours

Full working-day overlap with AEST, which India covers naturally. Calls at a civilised hour on both sides.

Is the timezone actually workable?

Better than most offshore arrangements. AEST and IST overlap for nearly the whole working day, so you get real-time conversation rather than a 24-hour round trip on every question.

Can everything stay onshore?

Yes. On your own hardware, or in an Australian region of your own cloud account, so data does not leave the country at any point in the request path.

Who does the work, and what happens afterwards?

One named engineer throughout. At handover you get infrastructure as code in your own repository, a runbook covering start, stop, upgrade, key rotation and recovery, and all our access removed with written confirmation.

Why would we use an overseas engineer rather than a local integrator?

Often you should use both. An integrator holding the prime contract and the local relationship, with a specialist doing the AI and data layer underneath, is a common and sensible structure here. What you should not do is pay integrator rates for engineering that one person is actually doing.

Can the system run entirely inside our own infrastructure?

Yes, and in this region that is frequently the requirement rather than the preference. Model serving on your own hardware or in your own cloud account in a regional data centre, with no outbound calls, up to fully air-gapped.

Who owns the code?

You do, entirely. It ships into your repository on your own cloud accounts, documented so your team or your next hire can carry it without us, and all our access is removed at handover with written confirmation.

Full detail

AI Product Development

LLM apps, agents, RAG and MCP tooling, architected by the builder of AccioMatrix.