AI audit & strategy

First we map where AI actually pays off — then we build

We look at your processes, data and tools and tell you where automation and AI have real returns — and where they don't. You walk away with a prioritized deployment plan, not promises.

A low-commitment first step that ties you to nothing

Most companies approach automation backwards — they buy a tool or commission development first, and only then find out whether it solves the right problem. The audit flips the order. It's a short, well-bounded phase, after which you know exactly what's worth investing in and in what sequence. It doesn't lock you into hiring us for the build afterwards. The output is yours and stands on its own, whether your internal team runs with it or another vendor does. Think of it as a second opinion before you spend the bigger budget — it typically costs a fraction of what it would cost to build the wrong thing and then rebuild it.

What the audit actually examines

We sit down with your real processes — not the idealized version from a slide deck, but how things genuinely run. We track where people retype data from one system into another, where work waits on approvals, where the same manual task repeats every week, and where the same mistakes keep recurring. We look at your data: what shape it's in, where it lives, whether it's connected or scattered across spreadsheets and inboxes. We map the tools you already have — often a lot can be solved by connecting existing software better, not by buying more. And we hunt for time leaks: the quiet half-hours a day that add up to whole roles. That's usually where the fastest returns hide.

We'll also tell you where AI doesn't pay off

This is the part most vendors skip, because they're selling deployment. We're not. If a process is too variable, runs too rarely, or hinges on judgment that can't be reliably formalized, we'll say so plainly — automating it would cost more than it saves. We'll also flag when an "AI solution" is needlessly heavy and the same problem is solved by a simple script, a template, or a change in the process itself. The goal isn't to deploy as much technology as possible. The goal is for every euro you put in to return something. An honest "don't do this" is often worth more to you than another line item in a quote.

The deliverable: a prioritized plan with ROI estimates

You won't get a generic deck about trends. You'll get a concrete document: a list of opportunities ranked by benefit-to-effort ratio, with an estimate of how much time or cost each one saves and what its deployment will require. Every item carries a rough ROI estimate — not exact science to the decimal, but enough to decide what to do now, what to do in six months, and what to leave alone. It also includes a suggested order: what to start with so you see results quickly and earn the team's trust, and what to defer until the foundations are in place.

How it de-risks the whole project

The most expensive mistake in automation isn't badly written code — that gets fixed. The most expensive thing is building the whole system for a process that should have been simplified first, or one that won't exist in a year. The audit catches that mistake before it costs money. When we go into development with a plan in hand, you know up front what you'll get, why we're doing it this way, and how it pays back. No surprises halfway through, no "we should probably buy this too." For you, it means the decision to invest is grounded in data about your own company — not in a vendor's promise.

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