Service 05 / 07 — AI & Automation
Every business runs on repetitive work: answering the same ten questions, retyping data between tools, chasing documents and follow-ups. We build AI assistants and automation pipelines that quietly take that work over — reliably, in your customers' language, inside the tools you already use.
We're allergic to AI theater. We start with one workflow that costs you real hours, automate it end-to-end, measure the time it gives back, and only then expand. Systems that work beat demos that impress.
Sound familiar?
Nobody notices it as a line item, but it's there: forty-five minutes a day answering questions the website already answers, an hour moving order data from email into a spreadsheet, an afternoon each week chasing documents that arrive as photos of paper. Multiply by every employee, every week, every year.
Hiring doesn't fix it — new people inherit the same manual loops plus onboarding. And most 'AI transformation' pitches don't fix it either, because they start with technology in search of a problem and end as a demo nobody uses after week two.
The boring truth: the wins are in specific, repetitive, rule-bound workflows. Automate one properly — with fallbacks, human handoff and monitoring — and it pays for itself in months, then keeps paying back for years. Then you do the next one.
What we build
Support and sales assistants trained strictly on your approved knowledge — answering instantly in your customers' language, 24/7, escalating to a human the moment confidence drops.
Your CRM, email, sheets and invoicing connected so data moves itself — built with n8n, Make or custom code, whichever earns its keep.
Invoices, orders and forms read, extracted and filed automatically — with a human reviewing only the flagged exceptions instead of retyping everything.
Inquiries scored, enriched and routed to the right person with context and a drafted reply — minutes after they arrive, because speed-to-reply wins deals.
Private assistants over your documentation, contracts and data — so your team stops searching and starts asking.
Claude and other frontier models built into your product or process — scoped, evaluated, monitored, and boring in the best way.
What working with us looks like
01
Week 1
A process audit that maps where your team's time actually goes — not where the org chart says it goes. Every repetitive workflow gets a price tag in hours per month. We pick the one with the fastest payback, and write down how we'll measure success before building anything.
You walk away with
A ranked automation roadmap with hours attached to each item.
02
Weeks 2–4
The chosen workflow gets automated completely — not a proof of concept that dies in a slide deck, but a working system processing real volume alongside your team. Small enough to ship in weeks, real enough to trust.
You walk away with
A live automation handling real work within a month.
03
Weeks 4–6
Edge cases, malformed inputs, API hiccups, the customer who writes in all caps at 3 AM — this phase is the difference between a demo and infrastructure. Guardrails, human handoff, logging and alerting go in. The assistant only answers from approved knowledge, and admits when it doesn't know.
You walk away with
A system that runs with light oversight.
04
Month 2
Thirty days of honest measurement against the baseline from phase one: hours saved, response times, error rates, what your team did with the reclaimed time. If the numbers disappoint, you'll hear it from us first — with a fix or a refund of our recommendation.
You walk away with
A payback report in hours and euros, not vibes.
05
Ongoing
With the pilot paying for itself, the roadmap resumes: next workflow, then the next. Each one reuses infrastructure the previous one built, so automation number three costs less than number one. Boring, compounding, permanent.
You walk away with
An operations layer that scales without headcount.
Tools, chosen on purpose
Technology choices are business decisions wearing technical clothes. Here's what we reach for on this kind of work — and why.
Frontier reasoning with the strongest instruction-following we've tested — the difference between an assistant that helps and one that improvises.
Self-hostable workflow automation — your business logic and data stay under your control, EU-hosted when compliance demands it.
For lighter integrations where speed of change matters more than infrastructure — right tool, right size.
Custom glue where off-the-shelf connectors end — because the last 10% of a workflow is usually where the value hides.
Your knowledge base, structured for retrieval — assistants answer from your facts, not the internet's guesses.
At the end
A payback report comparing before and after — automation justified in your P&L, not our pitch deck.
Approved-knowledge boundaries, human handoff and full logs — AI that behaves like an employee, not a slot machine.
Data minimalism by design, EU hosting where required, processing agreements in writing.
Each automation reuses the last one's plumbing — the second workflow ships faster and cheaper than the first.
Fair questions
Anything else on your mind? Ask directly — a real person answers within one business day.
Anywhere a person repeats the same digital task weekly: answering common inquiries, transferring orders between tools, sending follow-ups, processing documents. If it's repetitive and mostly rule-based, it's a candidate. If it requires fresh judgment every time, it isn't — and we'll say so in the audit.
We design for data minimalism: a workflow sees only what it needs, hosting is EU-based where compliance requires, and data processing agreements are signed before anything runs. For sensitive workflows we use private deployments rather than public tools. You get the architecture in writing.
It will, occasionally — the design question is what happens next. Our assistants answer only from your approved knowledge, escalate to a human when confidence drops, and log every interaction for review. You define the boundaries; we enforce them technically. The failure mode is 'let me connect you with a colleague', never a confident invention.
We quote each pilot fixed after the process audit, and always against the hours it saves — so you see the payback period before committing. If the math doesn't clear within months, we'll tell you not to build it. A recommendation against our own invoice is the cheapest trust we can buy.
In our experience it replaces the worst parts of their jobs. The hours come back and get spent on work that actually needs judgment — sales conversations, service quality, the backlog nobody reached. Teams that automate tend to grow into better work, not shrink.
Yes — same discipline, different surface: scoped features, evaluation before launch, monitoring after. We've built assistants into client dashboards and mobile apps. If your product roadmap has an 'AI something' box on it, we can help turn it into a spec.
Pairs well with
