You don't give a frac how it's built. But you do care that it keeps delivering results.
We find the AI work worth doing, and build it in a way that keeps delivering results.
Fail fast. A diagnostic, then an honest go or no-go you can walk away from.
A capped budget you can plan against, and scope that can flex inside it.
Monthly. We keep it delivering as everything underneath it changes.
You're worried you're missing out on AI. That worry is someone else's business model.
Watching the AI conversation right now is a bit like watching American politics. Two camps, both extremely loud and little middle ground.
Your feed is wall to wall tokenmaxxers and people trading skill files for a follow. In between, a steady drip of stories about AI projects that failed. Meanwhile the chat you had with GPT this morning hallucinated three times and you corrected it twice before it gave you what you wanted.
Both camps miss the same thing. It is genuinely easy to make AI show value quickly: a demo, a prototype, a workflow that impresses a room. It is still genuinely hard to build something that matters and keeps mattering. Those two cost different amounts and need different engineering. Telling them apart is where we start.
Three stages, and a real exit halfway through the first one.
Every price is on this page, including the one we make nothing on.
The audit
Fail fast, deliberately.
The diagnostic
A structured look across your leadership, your people, your data and your systems. Days rather than weeks.
Stopping here is a normal Tuesday.
We stop and sit down with you, and you get an honest go or no-go. Sometimes the right answer is using an existing product or a simple skill file. You keep everything we found, we shake hands, and you have spent a small amount to avoid spending a large one.
Plenty of firms will tell you they would walk away from bad work. Almost nobody has built a way to mean it. We price the diagnostic at cost and we lock this meeting in before anything starts.
The deep dive
Only the work that cleared the bar, taken to implementation detail: real ROI, architecture, sequencing, risks, and anticipated costs to keep running. A plan any competent team could execute, including one that is not ours.
The build
A ceiling you can plan against and scope that can flex inside it, so we change direction when we learn something instead of raising a change request. Scoped to the shortest piece that stands on its own. Ships with the tests, the decision log and the written instructions for whoever runs it.
Keeping it sharp
We watch for drift, maintain your tests as your rules change, ship patches, and migrate you as model providers move. Each month you get a report of what changed and what we caught.
All prices AUD, ex GST.
What we look at
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Your people and process
Who we talk to, what we listen for, how the work actually gets done versus how it is documented.
Your data
What we assess. Quality, coverage, structure, access.
Your systems
What we review technically.
What you get
The named artifacts that arrive. [to be named]
Results on launch day. And every day after it.
A production system has to work every day, on inputs nobody thought of, while the model and context it operates under may be changing underneath.
It has to be yours, not a template.
A whole category of firm is building roughly the same agent for everyone and calling it bespoke. Nothing wrong with that if it gets you the outcome you are after.
Where we excel is the part of your business nobody else can copy: the pricing judgement your best operator makes, or the experience your customers get because of how your CS team works.
What does good look like? Constantly evaluated.
AI solutions are not deterministic, so we agree a set of test cases and acceptable boundaries with your team and evaluate them continually.
Good is not just day one. It is day one thousand, as models drift and your data changes.
Reliable AI needs reliable data.
Data is the foundation of every AI system. Bad data in, bad data out.
We do the cleanup, the pipelines and the integration work, and we sit down with your stakeholders to understand how your data is actually used so it is modelled for context and retrieval accuracy.
A record of why, not just what.
Every decision that matters gets logged with its reasoning. Why this model, why this threshold, why we rejected the obvious approach.
When someone new picks it up, whether that is your team or ours, they inherit the thinking and not just the code.
01It has to be yours, not a template.
A whole category of firm is building roughly the same agent for everyone and calling it bespoke. Nothing wrong with that if it gets you the outcome you are after.
Where we excel is the part of your business nobody else can copy: the pricing judgement your best operator makes, or the experience your customers get because of how your CS team works.
02What does good look like? Constantly evaluated.
AI solutions are not deterministic, so we agree a set of test cases and acceptable boundaries with your team and evaluate them continually.
Good is not just day one. It is day one thousand, as models drift and your data changes.
03Reliable AI needs reliable data.
Data is the foundation of every AI system. Bad data in, bad data out.
We do the cleanup, the pipelines and the integration work, and we sit down with your stakeholders to understand how your data is actually used so it is modelled for context and retrieval accuracy.
04A record of why, not just what.
Every decision that matters gets logged with its reasoning. Why this model, why this threshold, why we rejected the obvious approach.
When someone new picks it up, whether that is your team or ours, they inherit the thinking and not just the code.
What we will not do
We are not vibe coders, and we do not sell vibe-coded solutions.
No multi-year transformation programmes. No RFPs. No bums on seats.
We do not compete on price, we believe that you get what you pay for.
Workshops that make everyone feel good, but don't actually deliver meaningful change.
frac this:
frac legacy.
The legacy problem in this market is not your old system. It is the firms selling to you. Same delivery model they have run for fifteen years, same process, same shape of team, now with AI in the deck. They will charge you handsomely to transform while transforming nothing about themselves. If a firm has not changed how it works, be careful about what it can teach you about changing how you work.
And no, we will not tell you to replace something because it is old. If a system has been quietly doing its job for twelve years, it has earned some respect. Upgrading for the sake of upgrading is the same sales trick wearing a different costume.
frac one size fits all.
The market makes you pick one. Firms with real engineering depth turn up with a single playbook and learn your industry on your dime. Firms who genuinely know your industry hand you engineering that results in flaky and clunky systems. You are paying for one and you need both.
At Frac Consulting, we not only have a network of seriously impressive software and data engineers. Where a build needs domain depth we do not have, we bring in an AI-pilled fractional executive who has actually run that function, working alongside the engineer. CXOs who understand your industry, your problem, and your domain, able to get up to speed and start adding value immediately.
frac big projects that turn into black holes.
You know how this one goes, because you have watched it. The pitch was $500,000. Three years later it was $4.5 million, the partners who pitched never came back, the contractors who did the work left nothing written down, and you were arguing with an account manager about a change request for a system that no longer fit your business.
We scope to the shortest piece of work worth having on its own, we agree a ceiling before it starts, and then we look at the next one. Nobody should be waiting a year to find out whether this was a good idea, least of all you.
Questions people actually ask
What do we get for $3,000?
A structured diagnostic across your people, your data and your systems, and a written go or no-go you could hand to your board. You keep everything we found regardless of what you decide next.
Can we just start with the $500 Pulse session?
Yes, and plenty of people do. Two hours, one on one, live. Bring the thing you are stuck on and you will leave with next steps, and usually something working that you can keep using.
Be clear about what it is, though. Two hours on one part of your business will not tell you where AI pays across the company, what it is worth, or what it costs to run. That is the audit, and it is a different exercise. The Pulse is the cheapest way to find out whether you want to work with us. It is not a smaller version of the audit.
Do we need a technical team?
No. Some of our clients have engineers, some have an IT provider, some have neither. Whatever we build is handed over properly, and whoever looks after your systems today can look after this too. We will brief them ourselves if that helps.
Who owns what you build?
You do. Your business logic, your data, your integrations, all of it, on payment rather than on continued payment. Anything of ours that ends up inside your system is licensed to you permanently at no cost, so you are never renting your own software back from us.
What if our requirements change halfway through?
They will. That is why builds run to a capped budget rather than a fixed price. You get a ceiling to plan against, and inside it we can change direction when we learn something instead of stopping to raise a change request. Nobody has to negotiate to do the obvious thing.
How long does this take?
The Pulse is two hours. The audit's first stage is days rather than weeks. Builds are scoped to the shortest piece that stands on its own, which usually means weeks rather than quarters.
Hard problems do require hard engineering though, so we can't always deliver in a few weeks. Our goal though is to get the time to value as close to zero as possible.
We tried something already and it stalled. Is that a problem?
It is common enough that it is almost a qualification. A stalled pilot usually tells us more about where the real blockers are than a blank page would, and your team has already learnt something expensive. Bring it.
“frac exists to be the firm I could never hire.”
Frac Consulting was built to be the opposite of the firm that sells you AI it does not use itself. Twenty years of senior technology leadership, two of them building AI systems in production, and a network of senior engineers brought in by name when a build needs them.
Senior technology leadership. Readify, MatchBox Exchange, Brandcrush.
We built and run our own AI platform, Talent Hustler, and carry its uptime and its bill.
Start with the audit.
Or just ask a question about it.
A $500 Pulse session is two hours, one on one, live. Bring what you are working on and we will get you to a set of next steps you can act on.
Invoiced before the session.