An AI audit is a structured assessment of where AI and automation can save time, cut cost, or unlock revenue inside a specific business. Done well, it ends with a prioritised list of opportunities, an estimated ROI for each, and a clear roadmap for what to deploy first. Done badly, it ends with a 40-slide deck full of generic advice.
I have sat across from a lot of founders at the start of one of these. The look on their face is almost always the same, somewhere between hopeful and braced, because they half-suspect their business is held together with more tape than they would say out loud. It usually is. That is not a failure; it is just what happens when a company grows faster than anyone had time to document it. The audit is the first time most of them see the whole thing laid out in one place.
This is what ours actually involves, end to end.
What an AI audit actually is
Most "AI audits" sold today are sales calls dressed up as discovery. The "auditor" runs through a generic questionnaire, recommends three buzzword-flavoured projects, and quotes you for them. That is not an audit. That is pre-sales.
A real audit is process-led, not technology-led. We start with what your team actually does every day, the workflows, the handoffs, the places where things slow down or break, and only then ask what technology could help. Not the other way around. The sequence matters more than most people realise. When you lead with the technology, you end up buying solutions in search of problems.
A real audit produces specific, actionable opportunities with cost and time estimates attached, not vague themes like "leverage AI for productivity." Every recommendation we make has a number on it: how many hours this recovers per week, what it costs to build, what it costs to run, and what the payback window looks like. You can decide whether to act on any of it with real information instead of gut feeling.
It also includes things we are not the right partner for. If the best solution to your problem is a Zapier flow your ops manager can build in an afternoon, we say so. This is not charity. It is how we earn the work that does require our level. And the output is yours no matter what happens next. You do not have to hire us to use the roadmap. The €49 buys the deliverable. If we end up being the people who build it, that is because we made a strong enough case during the audit, not because we held the information hostage.
The four phases of our audit
Phase 1: Process mapping (Day 1-3)
We map every recurring process in your business. Customer onboarding, order processing, support, sales follow-ups, hiring, finance close, reporting: every workflow that repeats more than once a week.
For each one we capture: who does it, how often, how long it takes, what tools are involved, what the inputs and outputs are, and where the bottleneck or pain point is. Most businesses have between 30 and 80 distinct processes once mapped. Most have never seen them written down in one place.
This phase alone often delivers value that justifies the audit fee, even before any automation gets recommended. You finally have a map.
Phase 2: Opportunity scoring (Day 3-5)
Each process gets scored on three axes. The first is automation feasibility: not "could AI theoretically do this someday" but "can current tools handle this reliably today, deployed in a business like yours." We score against what actually ships, not what is on the roadmap. The second axis is time recoverable: how many hours per week come back if this workflow runs automatically. The third is risk: what happens if the automation fails, and how visible is that failure. A process that touches customer-facing communication or financial transactions carries more risk than an internal reporting flow that only you ever see.
The scoring produces a 2x2: high-feasibility and high-time-saved goes to the top of the roadmap. High-risk items get pushed later or left alone entirely. We are deliberately conservative on the risk axis, because recommending automation that fails publicly is a worse outcome for both of us than recommending fewer things with higher confidence.
Phase 3: ROI estimation (Day 5-7)
For every prioritised opportunity, we estimate three numbers. The first is build cost: what it costs to deploy, expressed as a rough range rather than a quote. A quote requires a full scoping conversation; the audit gives you the range you need to make the decision about whether to have that conversation. The second is recurring cost: model API usage, tooling subscriptions, and the ongoing maintenance that every automation eventually needs. The third is annualised return: hours saved at your team's loaded cost, plus revenue impact where it is measurable, whether that is a lift in conversion rate, recovered lost revenue from stockouts, or a faster sales cycle that pulls deals forward.
Every estimate has a range, not a point. We would rather say "€8,000-€15,000 annual return" than pretend to a precision we cannot defend from a seven-day audit. The range is honest. The point estimate would not be.
Phase 4: Roadmap and strategy call (Day 7-10)
You receive: the full process map, the scored opportunity list, the ROI table, and a recommended sequencing: what to deploy first, second, third, and what to leave alone. Then we book a 60-minute call to walk you through it, answer questions, and let you push back on anything that does not fit your reality.
After the call, you have everything you need to either build the roadmap in-house, hire someone else, or hire us. There is no obligation either way.
What we typically find
After running this audit on dozens of businesses, three patterns show up over and over:
Pattern 1: One person is a single point of failure
Almost every business has one. We mapped a 40-person company last year whose entire fulfilment process lived inside the head of a single operations manager, the one who knew which supplier to call when the usual one ran dry, which customers needed handling with care, which shortcuts were actually safe. She had not taken a proper holiday in three years. Not because anyone forbade it. Because the business quietly stopped working when she did, and she knew it. So she stayed.
AI does not replace someone like her. But it can capture and codify what she knows, the decision rules, the supplier logic, the exceptions, so the company keeps breathing when she finally switches her phone off. When we showed that founder how much of the business was riding on one un-backed-up brain, it was not the cost savings that landed. It was the relief.
Pattern 2: 30-50% of "skilled work" is data shuffling
When we time-track skilled roles (sales, ops, customer success, even engineering), 30-50% of the hours go to copying numbers between systems, formatting reports, chasing approvals, and re-entering data. Almost all of it is automatable, and almost none of it is what those people were hired for.
Pattern 3: The dashboards lie
The reports that get sent to leadership weekly are usually wrong, late, or both. Either the underlying data is messy, or the people pulling the numbers are interpreting them inconsistently. By the time leadership notices a trend, it is often months old.
A clean data layer plus AI summarisation fixes this in weeks. Suddenly leadership knows what is actually happening, and decisions get made on real signal instead of last quarter's vibes.
The biggest opportunity in most businesses is not "deploy AI." It is finally seeing your operation clearly. The audit forces that visibility. Whatever you do next, the map matters.
What you walk away with
Concretely, you receive a documented map of every recurring process in your business, typically 30-80 processes for a company between 5 and 200 people, many of which have never been written down in one place before. That map alone, for a lot of founders, is the most useful thing to come out of the week.
On top of the map, you receive a scored and prioritised list of automation opportunities, usually 8-20 viable candidates, ranked by the effort-to-payback ratio we calculated during the scoring phase. Each prioritised opportunity comes with a cost range and an ROI estimate: what it costs to build, what it costs to run, and what it returns annually at your team's loaded hourly rate. We also give you a recommended deployment sequence, what to tackle first, second, and third, with rough timelines and dependency notes so you understand why the order matters.
The final piece is a 60-minute strategy call where we walk through everything, answer questions, and let you push back on anything that does not fit your actual constraints. You also receive a written executive summary you can hand to a co-founder, an investor, or a board without needing to translate it. Total deliverable size is typically 20-40 pages of working material, plus the call. You can use it however you want: to hire us, to brief another vendor, to run an internal sprint, or simply to understand your own operation more clearly than you did before.
Why €49 (and why it pays back many times over)
€49 is well below cost. A real AI audit takes 7-10 days of senior consulting work, and a comparable engagement from a traditional consulting firm runs €5,000-€20,000. We charge €49 for two reasons, and they are both deliberate.
The first is that it filters for seriousness. A founder who is not willing to spend €49 to find out where AI could save them €50,000 a year is not someone we are going to build a successful engagement with. Free filters too softly. It attracts curiosity browsers. A small number like €49 filters for intention without being a barrier to anyone who actually means it.
The second reason is that the audit is our pitch. If we spend seven days mapping your operation, identify €100,000 in automation opportunity, and walk you through it clearly and credibly, you are naturally far more likely to want to hire us for some of it than if you had only seen a sales deck. The €49 audit is how we earn the right to propose the work, not how we monetise a consulting service.
The math: even if you never hire us, you walk away with a roadmap a consulting firm would charge €5,000-€20,000 for. If you do hire us, the audit fee is credited toward the first deployment.
The honest summary: most businesses are running on processes nobody fully understands, with AI opportunities sitting in plain sight that no one has had the quiet hour required to notice. The audit buys you that hour. Whatever you do with what you see next, whether you hire us, hire someone else, build it yourself, or just sleep a little better knowing where the tape is, the map is yours to keep. Most founders tell us the clarity alone was worth more than the forty-nine euros. We think so too.