AI solutions

We believe the right moment for AI in operations is neither 2021 nor 2030. It is right now.

For years, we have been supporting companies in German-speaking countries with their visibility, branding, and digital communication. During this time, AI has gone from being a technical term to an everyday reality—not only in the tools we use ourselves, but also in the questions our partners ask.

The questions are remarkably similar—regardless of whether a small business with twelve employees or a company with one hundred and fifty calls. It's less about whether AI is beneficial. It's about where it should be implemented in this specific business without jeopardizing everything else.

Unsere Aufgabe ist nicht, KI zu verkaufen. Sondern zu klären, was wirklich gebraucht wird — und was nicht.

This page is not a brochure, a promotional poster, or a promise that everything will be better if you just invest quickly enough. It's an invitation to think like us—and, if it's a good fit, to work together.

AI solutions

Where do I even begin?

This approach is most effective where a process regularly stalls, affects multiple people, and can be clearly described. So, not the most spectacular, but the most troublesome issue. We'll start with an initial consultation, observe one or two days of your daily work routine, and give you an honest assessment of whether or not we see potential solutions.

What is hype — and what will last?

The difference rarely lies in the model itself, but almost always in the use case. Chatbots on company websites are usually a nuisance, while an internal system that makes your knowledge base searchable is usually invaluable. We'll tell you in advance which category your project falls into.

Is it worth it with only a few employees?

Usually, that's precisely when it happens. Small businesses have the most obvious bottlenecks: one person prepares quotes, one does the accounting, one handles support. Every lever has an immediate effect. If there's no benefit, we'll say so—even if it costs us a project.

AI is a tool, not a strategy.

When people say "AI strategy," they usually mean business strategy. We use AI where it makes an existing goal faster, better, or more precise—not the other way around.

The problem comes first.

We never start with the model. We start with the work that is not working satisfactorily today, and ask: what form of intelligence—human or machine—would truly improve it?

Model-independent, permanent.

We don't tie you to a single provider. Whether it's OpenAI, Anthropic, Mistral, Llama, or a locally hosted model — we build in such a way that the underlying infrastructure can be replaced if something better comes along tomorrow.

People remain the core.

The best AI implementation we've seen hasn't replaced people — it's taken away the boring parts of their jobs so that the more demanding ones have more space.

When requests become answers that sound like you.

It's not the chatbot on the homepage that matters—it's the quieter details: how emails are sorted and prepared, how offers are created from just a few keywords in your signature style, how recurring inquiries arrive at the team already partially answered. This saves hours without anyone losing personal contact.

Your company's memory — searchable, not buried.

Manuals, protocols, contracts, product data: usually present, rarely findable. A well-built internal AI system transforms your own documents into a colleague who answers questions, cites sources, and doesn't need a coffee break. Particularly effective when onboarding new colleagues.

Receipts, invoices, contracts — made readable without typing.

The invisible work on Friday afternoons. AI reads receipts, compares amounts, highlights irregularities, and prepares payment reminders. In the end, a human always makes the decision—but the pile on which the decision is made is smaller and more organized.

Remain visible, even when search becomes an answer engine.

Google ist nicht mehr die einzige Bühne. ChatGPT, Perplexity, Gemini beantworten Fragen, bevor eine Website besucht wird. Wir arbeiten seit Monaten mit Generative Engine Optimization und Entity SEO — damit deine Marke auch dann vorkommt, wenn nicht mehr geklickt wird.

Scheduling, quality, material — these factors are crucial when prepared better.

Photos become article numbers, voice memos become checklists, delivery times become scheduling proposals. We don't make the decision for you—we do the preliminary work so that decisions can be made faster and with a better foundation.

Business figures that are not only explained by a tax advisor.

Monthly reports, accounting exports, Excel spreadsheets — AI translates them into understandable briefings that management actually reads. Including outlooks, anomalies, and specific questions you should ask your team or consultants.

How we work.

Our process is tried and tested, but never formulaic. We're a collective of freelancers—that means you're speaking directly with the person who will ultimately be doing the work, right from the start. No game of telephone, no account manager layer between you and the tradesperson.

Every project begins with an initial meeting. We listen: what's working, where the problems lie, what's already been tried, and what's explicitly not desired. At the end of this meeting, we openly state whether we see a worthwhile application—and if so, where.

After that, we work in manageable steps. We first build a prototype so you can test early on whether the solution fits your everyday life. Only then do we scale. This approach saves time and prevents a project from straying from its original purpose.

Viele unserer Partner begleiten wir seit Jahren — durch Relaunches, neue Produkte, Wachstumsschritte. KI ist in dieser Zusammenarbeit der jüngste Baustein, aber sie ändert nichts an der Haltung: wir bleiben Ansprechpartner, auch wenn das Projekt längst läuft.

Which models we build with.

We are vendor-independent. The choice of model depends on the task, not convenience. For text-based tasks, we use platforms like Claude, GPT, or Mistral, depending on the context. For multilingual applications, we often use Llama or Gemma. For sensitive data, we rely on locally hosted models within the EU.

Voices from our work