AI consulting for Australian businesses that want a return, not a pilot. We find the use cases that pay, our own engineers build them, and the governance goes in before anything reaches a customer.
The Aussie automation partner rated
Most AI spend never reaches production
Rarely because the technology failed. Usually because nobody scoped the use case against a number, and nobody owned it after the demo. Unlike most AI consulting firms, we do not hand back a strategy deck: our own engineers build what we recommend and stay on it once it is live.
A working model is the halfway mark. These are the four places an AI project has to land before we call it delivered.
Enquiries answered, quotes issued, and bookings taken at 11pm on a Sunday, when the alternative was a form sitting in an inbox.
The re-keying, the chasing, the reading of documents so someone can type the same thing into another system. Handed over, not outsourced.
Checks and approvals that used to wait on one person’s inbox clear immediately, with the genuine exceptions still escalated to a human.
Every AI-assisted decision logged, explainable, and reviewable, so your board and your clients get an answer rather than a shrug.
Every system we recommend, we have already built and run somewhere. Here is what our AI consulting services have produced for businesses across Australia.
The chatbot they already owned was written off as a cost line. We rebuilt it as an AI consultant for a major Australian flooring retailer, and it now turns after-hours visitors into booked quotes.
Every Amex payment Pay processes needs a verified business address, or it stops. The decision itself is now made automatically, in seconds, across two markets, with no one reading a document to do it.
The assessment found a revenue opportunity, not just a technology problem. We built TOIPA from scratch: a paid program that runs itself and sustains Link Foundation’s free core services.
The data had to be in one place before anything clever could run on it. Standard Access moved beyond servicing into full toolkit asset management, on a platform their operations now run from.
Where AI belongs in your business and, just as usefully, where it does not. AI strategy consulting that ranks the candidates by payback, names an owner for each one, and comes back with a costed sequence rather than a wish list.
A short, fixed-scope engagement that scores your processes, data, and systems against what AI can actually do today. You leave with a shortlist, a baseline to measure against, and a recommendation — whether or not we are the ones who build it.
Generative AI consulting that ends in something running: retrieval over your own documents, drafting and summarising inside the systems your team already uses, and an evaluation harness that proves the answers hold up. Model chosen after the requirement, not before.
Agents that do the work rather than describe it — reading the email, updating the record, escalating what they should not decide alone. Built on the same rails as our process automation work, so the handover between rules and judgement is deliberate.
Assistants that qualify, quote, and book around the clock. This is the work behind our AI customer service page, where rebuilding one retailer’s chat assistant produced nearly $1M in attributable revenue.
The policy, the controls, and the AI register your board can sign off, mapped to Australia’s Voluntary AI Safety Standard and its ten guardrails, with a path to ISO/IEC 42001 where a client or tender demands one. Includes the awkward part: what your staff are already using, and what to do about it.
Most stalled AI projects are data projects wearing a costume. We connect the systems, reconcile the identifiers, and get the records into a state a model can be trusted on — scoped before anyone trains anything.
Deployment, human-in-the-loop review, drift monitoring, retraining, and your team trained to run it without us. Our engineers build what we recommend, which is the main thing keeping the recommendation honest.
Tell us the process that hurts. We will tell you whether AI is the right answer, roughly what it would return, and when it is not worth doing.
Tell us what’s not workingWe deliver AI consulting to organisations right across Australia. These are the moments that start the conversation.
Reading the spec, pricing it, writing it up. Common across retail and e-commerce and construction, and usually the first place AI pays for itself.
Invoices, applications, contracts, remittances — re-typed into a system that could have read them. Standard work for professional services firms and finance teams.
Banking and finance and government clients cannot deploy a model nobody can explain. Governance gets designed in at the first workshop, not bolted on for the audit.
Buying decisions increasingly start at night. An assistant that qualifies, answers, and books is the difference between a lead and a form sitting in an inbox until Monday.
Often the fastest engagement we run: find what is in use, work out what data has left the building, and replace it with something sanctioned that is genuinely faster.
You need something defensible: use cases ranked by payback, an owner against each one, and a number attached. Costed and sequenced, not a list of technologies.
Sits in the first workshop and stays accountable for the use case long after the model is live.
Pressure-tests every AI recommendation against what it costs to run, monitor, and retrain in production.
Your single point of contact once a use case becomes a build. Owns scope, timelines, and comms.
Runs the readiness assessment, mapping processes and data to find what is worth automating before anything gets built.
We’ll be in touch within 30 mins to:
Since going live we’ve cut admin time by over 60%, reduced stock issues, sped up reporting, and improved guest response times. It paid for itself quicker than expected.
Their ability to translate complex AI concepts into clear, actionable strategies tailored to each client’s needs is exceptional. Their consulting approach is both strategic and hands-on.
They took the time to understand how we operate, pinpointed areas that needed tightening up, and implemented practical solutions that have genuinely improved our turnaround times and overall clarity.
Automation Consulting has been excellent to work with. Their team demonstrates strong expertise, clear communication, and a commitment to delivering value. Highly recommended!
An AI consultant works out where artificial intelligence is worth applying in a business and what it will return: assessing your processes and data, ranking use cases by payback, choosing the models and tools, then building, governing, and measuring what goes live. The ones worth hiring are still involved after the pilot.
At a minimum: a readiness assessment, a use-case shortlist with a business case against each one, and an AI strategy and roadmap. Ours also include the build — generative AI, agents, and customer-facing assistants delivered by our own engineers — plus the governance, monitoring, and handover that keep it working after we step back.
Ask who builds it. Many AI consulting firms sell the strategy and hand delivery to someone else; others resell the platform they are certified in, which settles the recommendation before the assessment even starts. Three questions separate them quickly: do you build what you recommend, what happens if the payback does not appear, and can you point to a system you built that is still in production a year later.
The part of AI consulting concerned with models that produce language, code, or images rather than a score or a forecast. In practice: retrieval over your own documents, drafting and summarising inside the systems your team already uses, and agents that take actions — each with an evaluation harness proving the output is accurate enough to rely on. Generative AI consulting without that measurement is a demo.
Start with Australia’s Voluntary AI Safety Standard: ten guardrails covering accountability, risk management, data governance, transparency, and human oversight, aligned to ISO/IEC 42001 and deliberately workable for smaller organisations. It creates no new legal obligations on its own, but your existing privacy and record-keeping duties still apply to whatever a model touches. We build to those guardrails and hand over the policy, the AI register, and the controls as part of the engagement, not as an extra.
No, but you need to know what state it is in. The readiness assessment tells you which use cases your data already supports and which need work first. A good deal of the early value sits in cases that need no data project at all: reading documents, answering enquiries, drafting the first version of something.