AI Consulting
AI consulting that starts with how your business works. You get a written plan for what is worth doing with AI, what it will cost and what to skip.
What AI consulting is for
Many companies start with AI from the wrong end. Someone senior reads that it matters, a project starts, a tool gets bought, and eighteen months later there's a chatbot nobody uses and a cost nobody can justify.
We start with what your company does every day. We find the parts that are repetitive, slow or error-prone, and work out which of them AI can really improve. Some can. Many can't, and finding out before you build is the whole point of getting advice. If you plan to sell an AI product yourself, building an AI MVP covers running costs, testing and GDPR.
How the assessment works
We talk to the people doing the work, as well as leadership. The person who processes the invoices knows exactly where the time goes, and they're rarely asked.
We look at your data. What you hold, where it lives, whether your systems agree, and whether your records are good enough to use. This is the most common reason a promising project dies, so we check it in week one.
We do the sums for each idea. Current cost, build cost, running cost and payback period. Where we're unsure, we say so and give a range.
You get a written recommendation. Ranked, with our reasoning, plus what we recommend against and why. It's priced and scoped, so you can approve or turn it down as it stands.
What we've learned since 2021
The wins are smaller and duller than the sales pitch suggests. Reading documents. Sorting an inbox. Drafting a reply that a person then edits. Spotting a pattern in data someone has been eyeballing for years. Each one is small, and together they add up.
Failures have the same few causes. Not enough data, or data that contradicts itself. A process that changes so often that automating it means rebuilding it every month. And nobody inside the company owning the result, which quietly sinks more projects than any technical problem.
What we don't do
We don't sell a platform, and we take nothing from any vendor we recommend. We don't write strategy documents that stop at principles. And we won't tell you AI is going to transform your industry. You've read that already, and it doesn't tell you what to do on Monday.
If you're in Hungary
Our team has been in Budapest since 2021. That means Central European Time, briefs and workshops in English or Hungarian, and people you can meet before you commit a budget. The Hungary version of this page is AI consulting in Hungary, with the five stages and the costs.
How it works
- A fixed-scope assessment you keep
- We spend two to three weeks looking at how your company really works: where the repetitive effort is, what data you hold and what state it's in, and which decisions rest on guesswork. You get a written assessment ranked by payback. It's useful even if you hire someone else to build.
- Ranked by payback
- For each idea we estimate what it costs now, what it would cost to build and run, and when the savings catch up. Most lists come back with two or three things clearly worth doing, several to revisit next year, and a few to drop. We tell you which ones to drop.
- A close look at your data
- Most AI projects that stall do so because of the data: it's spread across systems that disagree, it was never recorded, or it was recorded too inconsistently to use. We check this early, because finding out in month four is how a project becomes a write-off.
- We can build it, or tell you who should
- We can build what we recommend, and often do. But if the right answer is a product you can buy, or a change to how you work with no software at all, that's what the assessment will say.
- Written for whoever signs it off
- The assessment is written for the people who approve it: what we recommend, what it costs, what could go wrong and how you'd know it worked. No slide deck of industry statistics, and no list of vendors.
Projects like this
What's included
Included
- Interviews with the people doing the work, as well as leadership
- A check of what state your data is in
- A payback estimate for each idea, with ranges where we're unsure
- A ranked written recommendation, priced and scoped
- What we recommend against, and why
- The document is yours whether or not you build with us
Not included
- Building it, which we quote separately if you want it
- Software licences or AI model usage
- Change management and staff training programmes
- Paid vendor shortlists (we don't produce them)
What we build with
- Python
- SQL
- OpenAI
- Anthropic
- n8n
- PostgreSQL
What do we get at the end?
How long does it take?
Why start with data rather than tools?
Will the answer always be to hire you to build it?
Do you take commission from vendors?
What have you learned doing this since 2021?
Also in AI & automation
Tell us about your project.
Get in touch ↗