Services
Three ways to work with us that most engagements start with, the technical compliance sprint for the AI Act (the EU regulation on artificial intelligence), a readiness audit, industry pages and three documents on how we work. Each page sets out the scope and when we advise against the project — because the cheapest implementation is the one you do not have to do.
Describe one processThree ways to work with us
Three ways to work with us, each of which can be named, priced and accepted — not a catalogue of everything that can be done with AI. Pick the one that describes your situation; if none does, start with the conversation at the foot of this page.
AI implementation
One recurring process — implemented, tested and accepted.
We take one recurring piece of work off your hands and leave a solution that works and has been signed off, not an endless transformation plan. From checking it pays off, through integration and tests, to handing it over to your team.
AI implementation →Connecting an AI assistant to your system (MCP)
When an AI assistant is meant to use the functions of your system, and a ready-made integration cannot do it.
One API (the interface other software uses to connect to your system), one AI app, and, to start, read-only access or actions a person approves. Permissions you can trace, acceptance tests, and when a plain API is enough.
Connecting an AI assistant to your system (MCP) →AI agents in your development team
When the team already pays for coding agents, and the result depends on who is at the keyboard.
One repository, one family of tasks, code review rules and automated checks every change must pass — measured by task turnaround and rework, not by lines generated. Not a course.
AI agents in your development team →Not sure where to start? Start with a single-process pilot — we test one process on your data before you fund a full implementation.
Three pages take the first of them further, each covering one of its most common variants — usually a stage or a consequence of the implementation, not a separate way of working:
- AI automation — when the process is known and repetitive, and the point is to take copying work off people — and where a person stays involved in the process.
- AI agent implementation — when there are too many paths to write down as rules — the project starts with permissions and with what happens when the agent gets something wrong.
- Voicebot — when the phone rings and there is nobody to answer it — you buy the bot on subscription; our project connects it to your systems and settles which calls it must not take.
Regulation and the starting point
Not sure yet which process is worth improving? The audit helps you assess the options and choose a first step. You can order it on its own or as the start of an implementation. If you need to implement AI Act requirements identified by your lawyer, see the technical compliance sprint, a short fixed-scope project.
AI Act technical compliance sprint
Once your lawyer has settled which duties apply — or needs a register of systems to do so.
A register of AI systems, notices and content marking (Article 50), documentation and an AI-literacy workshop (Article 4) — fixed scope and price, 5–10 working days.
AI Act technical compliance sprint →AI readiness and opportunity audit
The starting point when it is not yet clear where AI creates value.
Processes, data, systems, integrations, people, risk and economics — a readiness assessment, prioritised opportunities and a pilot plan, with no obligation to hire us for the implementation.
AI readiness and opportunity audit →Industries and processes
The same way of working, grounded in the processes of one industry or one department. If you are looking for answers for your own area, start with the page that speaks to it:
- AI in manufacturing — Which processes to start with — and why the first results are usually in the production office, not on the floor.
- Customer service automation — What to automate before a chatbot: identifying what enquiries are about and routing them, replies drafted for approval, and the work behind the scenes.
- Accounting automation — The system reads, posts and reconciles — a person approves, and the responsibility stays with them.
- AI in logistics — Orders, transport documents, slot bookings and settlements — before anyone promises route optimisation.
- AI in a trading company — Orders, offers and customer enquiries — document processes where results show in weeks.
- AI in construction — Tenders, cost invoices and subcontractor settlements — before anyone promises site analytics from photos.
- AI in a sales team — Enquiries, quotes and the CRM — a shorter path from enquiry to offer, with no cold-email machines.
- AI for law firms — Case files, recordings and the court portal — AI reads, cross-checks and watches the deadlines; a lawyer checks and signs the result.
How we work
Three documents answer the questions that come up most often in a sales conversation, and are worth reading whichever one you pick:
- Delivery methodology — Four phases, a concrete output at the end of each, the split of decisions — and the conditions under which we advise against a project.
- Security and GDPR — Where data goes in an AI model integration, who is controller and who is processor, and how the AI Act differs from the GDPR (General Data Protection Regulation).
- What we don't do — What we will not build, and the eight conditions under which we advise against a project.
Not sure where to start?
Describe the process you want to improve. We will tell you where to start — including when the answer is that it is not worth doing yet.
Free 20–30-minute call. Write or call, and we’ll reply with two time slots.
Describe one process
The message goes straight to our mailbox. If you would rather e-mail or call, both are above.
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We usually reply the same working day, at the latest the next one.
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