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.
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 looks like this:
- It is process-led, not technology-led. We start with what your team actually does, not with what AI tools exist.
- It produces specific, actionable opportunities with cost and time estimates, not vague themes like "leverage AI for productivity."
- It includes things we are not the right partner for. If the best fix is a Zapier flow your ops manager can build, we say so.
- The output is yours regardless. You do not have to hire us to use it. The €49 buys the deliverable; we just make a strong case to be the people who build it.
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:
- Automation feasibility — how much of this can AI realistically handle today (not in 2027), with current tools?
- Time recoverable — hours saved per week if automated.
- Risk — what happens if the automation fails? (A process that touches money or customer-facing communication has higher risk than internal reporting.)
The scoring produces a 2x2: high-feasibility / high-time-saved goes to the top of the roadmap. High-risk items get pushed later or left alone. We are deliberately conservative — recommending automation that fails publicly is a worse outcome than recommending less.
Phase 3: ROI estimation (Day 5-7)
For every prioritised opportunity, we estimate three numbers:
- Build cost — what it costs to deploy (rough range, not a quote).
- Recurring cost — model API costs, tooling, maintenance.
- Annualised return — hours saved at your team's loaded cost, plus revenue impact where measurable (e.g. lift in conversion, recovered stockouts, faster sales cycle).
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.
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 at least one process that runs entirely through one person's head — the ops manager who knows every supplier, the founder who personally writes every quote, the senior engineer who manages all deploys. When they are out, the business limps.
AI does not replace these people. But it can capture and codify what they know, so the business does not break when they are sick or on holiday.
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:
- A documented map of every recurring process in your business.
- A scored, prioritised list of automation opportunities (typically 8-20).
- A cost and ROI estimate for each prioritised opportunity.
- A recommended deployment sequence with rough timelines.
- A 60-minute strategy call to walk through everything and answer questions.
- A written executive summary you can hand to a co-founder or board.
Total deliverable size is typically 20-40 pages, plus the call. You can use it however you want — to hire us, to brief another vendor, to run an internal sprint, or just to know.
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. We charge €49 for two reasons:
- It filters seriousness. A founder who is not willing to pay €49 to find out where AI could save them €50,000 a year is not someone we want as a client. Free filters too softly.
- It earns the conversation. If we find €100,000 of automation opportunity in your business and we built credibility doing it, you are far more likely to hire us for some of it. The audit is our pitch.
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. The audit makes both visible. What you do with the visibility is up to you.