Your expertise is the edge. AI is how it scales.

Usually, if your edge is expertise. A system that puts your specialists' knowledge in the whole team's hands grows capacity without growing headcount: one psychology client now serves 25% more clients per psychologist, with clinical reports down from around 4 hours to 20 minutes.

The first step is a two-week discovery sprint that finds where the hours actually go.

Their knowledge can be captured into a system the rest of the team uses every day, so the business stops depending on who is in the room. How to spot it and reduce it is covered in our guide on key person risk.

Test demand before building anything. Handover+ validated the idea in two weeks and launched in five months; another venture, WellUnited, signed $1.2M in client contracts before development began.

A first stage can also end with a clear answer not to build, which is a cheap answer to get.

You are the majority: 56% of CEOs say their company has seen neither higher revenues nor lower costs from AI. The fix is to agree which number should move first, time, capacity, quality or revenue, and measure where it stands before building anything.

As a business decision, not a technology one. Decide which number AI should move, time, capacity, quality or revenue, measure where it stands today, and only build what moves it. Tools chosen before the number is chosen are how companies end up in the 56%.

It is worth having, and it is not the same thing. A subscription makes individuals faster one chat at a time; it does not capture your process, keep your data governed, or produce the same quality every time, for everyone. That takes a system built around how your team actually works, measured against the number you chose to move.

Follow the hours and the bottlenecks: where specialist knowledge limits growth, where work waits on one person, where the same judgement is made over and over. Our guide on where AI is worth using walks through the method we use in the discovery sprint.

Readiness is a score, not a feeling. Take the six processes that matter most to margin or liability and score each from 1 to 3 on two things: the cost of a mistake, and how clearly the standard for doing the work well is defined. Multiply. The highest score is where AI is worth testing first; a low-scoring list means the groundwork comes before the technology.

The readiness score above is the short version; the guide on where AI is worth using has the full method.

Buy when an off-the-shelf tool fits a job you do the same way as everyone else. Build when the advantage is your own way of doing things, because that is what generic tools cannot capture and competitors cannot copy.

A good first stage can end with "buy" or "do not build", and that answer is worth having before a major investment.

Start from the number that should move and its baseline, then cost the smallest system that moves it. The two-week discovery sprint produces exactly this: the opportunity, its value, and a go or no-go you own.

Eight questions, from "who owns the IP" to "what happens if AI is not the right answer", are in our guide to choosing an AI consultant, along with the difference between a consultant, an agency and a venture studio.

Then that should be found out before a major investment is made, not after. We work in stages, and a useful first stage can end with a clear, evidenced decision not to build.

Most AI consulting in Australia is priced by the day or hidden behind a proposal. We price per sprint, in the open, and every sprint is two weeks.

Every engagement starts with a discovery sprint at A$20,000: two weeks with the people who do the work, ending in a ranked list of opportunities, a commercial case for the first one and a decision that is yours, including the decision not to build.

Build work after that runs in two-week build sprints at A$30,000 each. A prototype is one sprint; larger design and build work typically runs across 5 to 12 sprints, and each one ends with something you can see and test.

The investment grows with the evidence, and you own what is built.

Two weeks for the discovery sprint. A working prototype in the first build sprint, then typically 5 to 12 two-week sprints to build and launch. Handover+ went from a validated idea to a live product in five months.

You do: the code, the IP and a transferable stack any team can run. If what we build could become a product for a wider market, we can test that demand too.

No. Each sprint ends with a decision that is yours. If the numbers do not stack up, you stop and keep everything produced up to that point.

No. Your team brings the business and industry knowledge; we bring strategy, design and engineering, working alongside the people who will use what is built.

A conversation. You do not need an AI brief or a finished idea: write to hello@mayflyventures.com or book a free 30 minute call.