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About | intelliwAIve
Vineyard rows at sunrise
About

An operator and a winemaker, building the thing neither trade had.

intelliwAIve was founded by Troy Vertigan and John Belsham. One has spent his career deploying technology and AI inside operating businesses. The other has spent his making wine, designing wineries and advising the companies that make and sell it.

Two disciplines

Applied AI and technical winemaking

Two markets

Australia and New Zealand, from the start

One model

Argued out against a real operation, not a whiteboard

One platform live

vinwAIve, in market now

The hardest part of building an AI platform for an industry is not the AI. It is knowing which number actually matters, where it comes from, and who gets blamed if it is wrong. That knowledge is not researchable. You have to have lived it.

Why we built it

A wine business can tell you almost everything, except what it earns on a bottle.

Between us we kept meeting the same conversation. An owner who knew their volumes, their scores, their allocations and their brand position, and could not tell you which of their wines actually made money, or which blocks were carrying the ones that did not.

From the technology side

The tools existed. The model did not.

Every business we worked with had bought software, and increasingly had bought AI. What almost none of them had was a model that carried a cost from where it was incurred to the product that had to earn it back. Without that, an AI has nothing worth reasoning over, and it will still answer confidently.

From the wine side

The knowledge existed. It was not written down.

Winemakers and viticulturists carry an extraordinary amount in their heads. Which block runs hot, what a barrel programme really costs, which calls get made on feel. It works until the person leaves, the market turns, or a board asks for the number in writing.

So we built the missing middle, AI-first rather than AI-added. vinwAIve carries a cost from a named section of vineyard through to a margin ladder on a named wine, live, auditable, and open to anyone in the business at whatever depth their job requires. It is the first platform under intelliwAIve, and the architecture behind it is built for the industries that follow.

The founders

Two careers that had to meet for this to work.

Troy Vertigan
Co-founder

Troy Vertigan

Founder and CEO, AI Surge

Troy is a technology leader and entrepreneur who has scaled businesses across Australia, the United States and Europe, with commercial expertise across software, SaaS and AI.

He is the founder and CEO of AI Surge, an Australian AI consulting company that takes organisations from experimentation to deployed, governed AI inside their own workflows. That work spans manufacturing, industrial, mining, construction, agriculture, professional services and financial advisory, and it surfaces the same underlying problem every time: businesses with plenty of data and no model connecting operational activity to a commercial outcome.

His consistent position is that AI is only worth deploying where it changes a decision that shows up in the P&L. That is why intelliwAIve platforms start with unit economics rather than with an interface.

Applied AI and deploymentSaaS and softwareCommercial and go to marketOperating model and transformationGovernance and responsible AI

If a number does not change a decision, it does not belong on the screen.

John Belsham
Co-founder

John Belsham

Founder, Foxes Island Wines and Wine Focus

John began his winemaking career in Bordeaux and is among New Zealand's most influential winemakers. In 1992 he founded Foxes Island Wines, one of the first New Zealand producers of single vineyard, cellar aged Chardonnay and Pinot Noir.

He leads Wine Focus, a consultancy covering business strategy, technical winemaking, sensory evaluation, mergers and acquisitions advisory and due diligence, and his work includes winery design, operational systems and water flow engineering across France, Australia and New Zealand. He is also the founder of Marlborough Oak Imports, the exclusive New Zealand representative for Tonnellerie Dargaud et Jaeglé.

John led the New Zealand Screw Cap Initiative, which moved 95 per cent of the country's wine industry from cork to screw cap within eighteen months, a change still studied internationally. He served as Air New Zealand's wine consultant for twenty years and as lead wine critic for Cuisine Magazine for sixteen, and is one of Australasia's most experienced wine judges. He is fluent in French and English and a regular commentator across international media and keynote events.

Inside vinwAIve, John owns the model itself. The costing logic, the recovery assumptions, the allocation of winemaking and packaging services and the definitions behind every parameter are his, which is why the platform behaves like a winery rather than like a spreadsheet with a wine label on it.

Technical winemakingWinery design and operationsCost and margin modellingMergers, acquisitions and due diligenceSensory evaluation and judging

The quality of the wine is decided in the vineyard. So is most of the margin.

Why the pairing matters

Industry software fails at the join, not at the code.

A technologist alone builds something elegant that a winemaker will not use, because it asks for data nobody has and reports a number nobody trusts. A winemaker alone builds a very good spreadsheet.

What makes vinwAIve work is that every modelling decision was argued out between someone who knows what the system can do and someone who knows what actually happens in a cellar in March. Where those two disagreed, the operation won.

That is also the template. Each intelliwAIve platform is built by pairing the architecture with somebody who has actually run the industry it is being built for.

The barrel hall
Every modelling decision was argued out against what actually happens on the floor.
How we work

Six things we decided early and have not moved on.

We connect, we do not replace

Your production system, your accounting software and your compliance tools keep doing their jobs. We sit above them. Nobody should have to rip out a system they have just finished implementing to answer a question about margin.

We build the model before the interface

Anyone can draw a chart. The work is deciding how a cost allocates, how tonnes become litres become nine litre equivalents, and how an operational event turns into a financial consequence. That comes first, every time.

We tell you what is not built yet

Our product pages carry a live status list, including the parts still in build. A buyer who discovers a gap in month three trusts you less than one who was told about it in week one.

We claim nothing we cannot show

No invented statistics, no borrowed case studies, no integrations described as working when they are linked portals. If we say a number, we will open the screen it came from.

We build it to be opened every day

A model nobody opens is a model nobody trusts. One navigation pattern the whole way down, so a grower, a winemaker and a chief executive use the same platform at their own depth, and nothing important hides behind training.

We start where the money is

Every capability has to trace back to a decision worth making. If we cannot explain what it is worth in margin, yield, time or risk, we do not build it.

Talk to us

Three conversations we always make time for.

Wine businesses

Show us your last vintage

Bring the numbers you already have and we will model them through to margin per nine litre equivalent, per wine product. You keep the findings either way.

Accountants and advisors

Test the framework on us

If the cost per bottle question is one your clients cannot answer, we want your professional judgement on the costing framework and the margin ladder before we put it in front of more boards.

Other industries

Tell us where your data breaks

If your industry runs on fragmented operational and financial data, and the decisions that move your margin are made on partial information, that is the exact problem we exist to solve.

Aerial view across a wine estate
Connect. Predict. Act.

Come and argue with the model.

The fastest way to understand what we have built is to put your own operation against it. Bring a question your current systems cannot answer and we will show you where the answer lives.