"Free AI audit" is a phrase that can mean almost anything. Which is why it usually means nothing.
Sometimes it is a sales call with a different name. Sometimes it is a discovery project with an invoice attached.
So rather than tell you ours is different, here is the whole thing, start to finish. What happens before the call. The questions we ask. How we score what we hear. And what you walk away with if you never speak to us again.
It takes 15 minutes. That is not marketing shorthand. It is the length of the Cal.com slot.
Before the call
You book straight into the calendar and pick a time. Done. There is no intake form and no brief to prepare.
The only useful homework is noticing which part of your week annoys you. That is where we start.
Would you rather not talk to a human yet? There is a self-serve version: the free AI readiness assessment. Seven scored questions, an instant score, no email gate. It names the two weakest foundations in your business.
The assessment checks whether AI would stick. The call works out where it would pay. Do it first if you like. It is not required.
The first half: function mapping
We do not open with "where do you think AI could help?" That question produces guesses, and guesses are what stalled the last pilot.
Instead we map functions. Those are the recurring jobs that run your week, whether anyone enjoys them or not. A launch that needs its email, its page and its announcement written. The weekly numbers somebody compiles by hand. The website changes that take a month to ship. The inbox admin that eats your evenings.
For each candidate we walk through the last real occurrence, not the tidy version. The last thing you announced to customers: who wrote the email, the post and the page? And how long did it take from ready to announced? The number you checked this morning to know the business is fine. Where does it live, and how old was it when you saw it?
Real history is harder to argue with than a hypothetical. Yours and ours both.
Those questions are not improvised. We keep a fixed list of validation questions. We work through whichever ones fit your functions, in the same wording, on every call. More on why in a moment.
The second half: severity times proof
Each function that surfaces gets two scores. Out loud, with you in the room.
Severity asks how much it actually hurts. Does it block revenue? Do you feel it every week? Are you already paying a person, an agency or a tool to do it? A job that irritates you once a quarter scores low, however easy it looks to automate.
Proof asks whether an improvement could be shown with a number you would not have to take on trust. Is there a baseline today? If a system ran this function next month, what figure would tell you it was working? Could someone rebuild that figure on demand, rather than assert it in a slide?
The recommendation only ever comes from where the two meet.
High severity with low proof means fix the measurement first, not buy an AI system. Without the number, neither of us would know whether it was working. Low proof is how the last wave of AI pilots got away with fizzling out quietly.
High proof with low severity makes a lovely demo and a poor business case. We say so and move on.
The function worth running is the one that hurts weekly and can be proven monthly.
The ten questions habit
The validation questions deserve their own explanation. They are the most honest part of the process.
We log the answers after every call. They diagnose your business. They also test ours.
Our positioning rests on assumptions about what actually hurts in companies like yours. Desk research cannot confirm those assumptions. Only callers can. When answers keep coming back different from what we predicted, we change the offer, not the question.
The audit is our research instrument as much as your diagnostic. We would rather say that plainly than pretend the value flows one way.
That is also why the call is free and stays free. We are not doing you a favour. We are trading a structured quarter-hour of diagnosis for ground truth we cannot get any other way.
What you leave with, even if you never hire us
Every caller ends with the same four things:
- A named first function. Not "AI could help somewhere", but the specific job we would run first, and why it beat the others on the call.
- Its scores, with reasons. Where it landed on severity and on proof, and what would move either one.
- One number to start tracking now. With us or without us, there is usually a measurement missing. Start collecting it, and every later decision gets easier and cheaper.
- A plain recommendation. Sometimes that is "this is a fit, and here is what running it would look like". Sometimes it is "keep using ChatGPT for this, it does not need us". Sometimes it is "fix the measurement, then talk to anyone you like in a few months". All of those are live outcomes on every call, by design.
There is no report deck afterwards and no email sequence chasing you. If the recommendation was "not us", the call did its job.
What does not fit in a call this size
A handful of things do not survive the format. We would rather name them than let you assume otherwise.
A full audit of every function in your business. One call surfaces the function that comes up first. Usually the one already annoying you enough to book. Run several past us and we will pick the one with the clearest case, and say so, rather than quietly score all of them.
A technical review. We are not inspecting your codebase, your data pipeline or your existing tool stack on the call. If the answer is to build something, the technical shape gets scoped afterwards, with access to the real systems.
A security or compliance sign-off. Anything touching customer data, regulated information or an existing vendor contract needs the right people and documents in the room. A quarter-hour call is not that room.
Buy-in from people who are not on the call. One stakeholder talking to us for a quarter-hour moves the conversation along. It does not replace the conversation those people still need to have with each other.
Certainty about fit. The call produces a recommendation, not a guarantee. Neither of us knows how a system performs until it has run for a stretch and been checked against real numbers. That is what the monthly check afterwards is for.
None of that is a hedge to protect us. It is the same instinct behind publishing our own failures alongside our wins. State the limit, rather than let someone find it the expensive way.
If there is a fit
When the scoring points at a real fit, the proposal that follows is specific. We build an AI agent for that one function, run it on a schedule, and publish a monthly check you can read. Failures included.
You can see the evidence style before you ever book. Our case studies describe the work without naming the businesses, and every number in them comes with the command that reproduces it if you ask.
The audit is the front door to that standard, so the audit gets held to it too.
Book it, or test yourself first
Want the self-serve read on whether AI would stick in your business? Take the free AI readiness assessment. It is quick and asks for nothing in return.
Want the diagnosis? Book the free 15-minute call. Bring the part of your week that annoys you.
You will leave with a named function, its two scores, and one number worth tracking. Whatever you decide to do about it.