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Intelligence for the industries that grow, produce and supply the world.
intelliwAIve builds industry-specific AI platforms for the businesses that grow, produce and supply the world. By connecting fragmented data and predicting what comes next, we give teams the intelligence to act earlier, transform performance and drive stronger margins.
Operational, production and financial data in one model
Forward outcomes during the period, not a report after it
Interventions ranked by what they are worth
vinwAIve is our first platform, in market now
Somewhere in your business today, a decision is being made on a number that was already out of date when the spreadsheet opened. That is not a data problem. It is margin leaving the building in places nobody can point to, because nobody can see them all at once.
intelliwAIve builds industry-specific AI platforms. Each one connects the fragmented operational and financial data of a single industry into one live economic model, then uses AI to show what is happening, predict what comes next and identify where margin is being made or lost.
The first platform is vinwAIve, built for the wine industry and live across Australia and New Zealand.
AI platforms, built one industry at a time.
Every business that grows, produces or supplies something runs two separate realities. One lives in production systems, field notes and machinery. The other lives in the ledger, weeks later, at a level of summary that cannot tell you which block, line, batch or account is carrying the business and which is quietly eating it.
intelliwAIve builds the AI platform that joins them. We do not replace the systems you run. We model the economics they were never designed to answer, put AI on top of that model rather than beside it, and keep the whole thing live so the answer arrives while it is still worth having. We are based in Australia and New Zealand, and vinwAIve, our platform for the wine industry, is live in both.
How we choose what to build next →Everything that happened, in exhaustive detail.
- What you produced, from which block, line or batch
- What went into it, and who did the work
- What condition it is in, right now, today
- What the weather did to it last Tuesday
It cannot tell you what any of it earned.
Everything you earned, six weeks after the fact.
- What the business made last period, in total
- What it spent, allocated across broad categories
- A gross margin your auditor will sign off
- A standard cost nobody has revisited in years
It has no idea which unit made it or lost it.
Swap the industry and the story barely changes.
We looked hard at a lot of sectors before choosing where to build. The equipment changes. These three do not, and none of them appear as a line item, which is exactly why they never get fixed on their own.
The picture is assembled by hand, every time
Production in one system, financials in another, what actually happened written on a phone. Every decision gets built from fragments, stitched together under time pressure, by whoever happens to be free.
The answer arrives after the decision
The report lands weeks after the period closes. By then the fruit is picked, the run is finished, the contract is signed. The number was correct and useless.
Averages hide the bleeding
A respectable headline figure can mask a wide spread between the best and worst unit, whether that unit is a vineyard block, a production line, a site or an account. Most businesses cannot tell you which is which without weeks of manual work.
AI is only as good as the model you point it at.
This is the part that gets skipped. Before anything can be visualised, someone has to decide how a shared cost allocates, how one unit of measure converts into another, how an operational event becomes a financial consequence, and which of those relationships hold when the season turns.
That work is specific to an industry and it does not generalise, which is why the same tool transforms one company and becomes wallpaper in the next. It is also why AI underperforms in most operating businesses. Given no model, a very capable system will reason fluently over the wrong structure and answer with total confidence.
We build the model first, then build the AI platform on top of it. That order is the whole difference.
Five questions, answered in order.
This part does not change from industry to industry. What changes is the data underneath it, the workflows it has to respect and the decisions it exists to inform.
Connect
Pull operational, production, financial and field data out of spreadsheets and disconnected systems into one structured model, without asking anyone to abandon the systems they already trust.
Understand
Show real performance at the level the money is made, not the average that hides where the problem sits. If a unit is losing money, it should be impossible to miss.
Predict
Model forward outcomes while the period is still open, so a shortfall is a decision to be made rather than a result to be explained.
Recommend
Surface the specific interventions worth making, ranked by the financial impact of making them, so attention goes where it earns the most.
Act
Turn the intelligence into a decision a team can make today, with the reasoning attached and the numbers behind it to defend it in the room.
vinwAIve is live in wine.
Wine came first because the problem was sharpest there. A wine business grows fruit, makes a product, packages it and sells it across several channels, and until now it could not tell you, on demand and with evidence, what a single wine cost or what margin it carried.
vinwAIve was built AI-first and AI-native rather than retrofitted: a cost of production assembled from the vineyard block forward, per nine litre equivalent, per wine product, with a full margin ladder over it and an analyst that reasons across the whole model. That chain is the proof the architecture works, and the template for everything that follows.
Four decisions we made early and have not moved on.
Connect, do not replace
We sit above the systems you already run. Nobody should have to remove a system they have just finished implementing to answer a question about margin.
AI-native, per industry
Not a generic platform with a logo swapped out. Each one is built AI-first around how a single industry actually makes money and where its decisions get made.
Say what is not built
Our product pages carry a live status list, including the parts still in build. A buyer who finds a gap in month three trusts you less than one told in week one.
Tied to commercial value
If we cannot explain what a capability is worth in margin, yield, time or risk, it does not get built and it does not go on the screen.
Built inside the operation, not handed to it.
Every intelliwAIve platform is built alongside people who have actually run the industry, because a model that does not survive contact with the operation is not worth running.
What people ask about intelliwAIve before they talk to us.
What is intelliwAIve?
intelliwAIve builds industry-specific AI platforms for businesses that grow, produce and supply physical goods. Each platform connects fragmented operational and financial data into one live economic model of that industry, then uses AI to show what is happening, predict what comes next and identify where margin is being made or lost. vinwAIve, built for the wine industry, is the first platform and is live across Australia and New Zealand.
What is an industry-specific AI platform?
An industry-specific AI platform is software built around how one industry actually makes money, rather than a general tool configured after the fact. It carries that industry's real units of measure, cost structures and decision points natively. In wine that means hectares, tonnes, litres and nine litre equivalents flowing through a cost model that reflects how a winery genuinely operates, instead of generic rows and columns a customer has to interpret.
How is intelliwAIve different from a BI tool or a general AI assistant?
A business intelligence tool visualises a model that already exists, and a general AI assistant reasons over whatever data it is given. Neither builds the model. The difficult, industry-specific work is deciding how a shared cost allocates, how one unit of measure converts into another, and how an operational event becomes a financial consequence. intelliwAIve does that work first, then applies AI to the finished model, which is why the answers can be traced back to the screen and the formula that produced them.
Does intelliwAIve replace our existing systems?
No. intelliwAIve sits above the systems you already run. Your production system remains the record of what happened on the floor or in the cellar, and your accounting software remains the ledger. We connect to both and answer the question neither was designed for, which is what each individual unit of your operation costs and earns.
Which industries does intelliwAIve build for?
Wine is live today through vinwAIve. Beyond that, an industry has to pass four tests before we build for it: operational and financial data fragmented across disconnected systems, a measurable financial cost when problems surface too late, genuine variance between units that averages conceal, and a buyer organised enough to act on the answer. Industries that grow, produce or supply physical goods tend to fit this pattern.
How does an engagement start?
It starts on your own data, not a demonstration data set. We model a recent completed period, show you the unit economics that fall out of it, and give you an honest assessment of what is connected and what is missing. You keep the findings and the model whether or not you go further.
How is our data handled and secured?
Your data remains yours and is never shared, sold or pooled across customers. Hosting, security and data governance are handled at the intelliwAIve platform level, and we will walk your technology lead or your auditor through the architecture on request. Data handling terms are agreed in writing before you share anything.
See what your business could know earlier.
Bring a question your current systems cannot answer. We will show you where the answer lives and what it would take to keep it live.
vinwAIve, live in wine
The cost and margin engine that proved the architecture, block to bottle to ledger.
Explore vinwAIve → The roadmapIndustries we build for
The four tests an industry has to pass, what is live, and how to put yours forward.
See the criteria → The peopleAn operator and a winemaker
Why the pairing is the point, and how it shapes everything we build.
Meet the founders →