Service
AI agents & automation
Agents that take over the recurring work your team should not be doing by hand.
From automatic document processing to an assistant that pre-qualifies inquiries: we build AI agents that give back measurable time, reliably and transparently.
What is an AI agent, and how does it differ from classic automation?
Classic automation follows fixed if-then rules. An AI agent also handles tasks that require understanding, such as classifying a text, reading the right fields from an invoice, or answering an inquiry sensibly. In practice we combine both: the reliable rule for the workflow, and the language model exactly where understanding is needed.
Which tasks can an AI agent take over in an SME?
An AI agent takes over recurring, rule-based work that your team does by hand today. Typical areas are reading and booking documents and invoices, pre-sorting and answering inquiries, reconciling data between two systems, and producing recurring reports. We automate first where a task occurs often, follows clear rules, and eats time today.
What does it actually deliver?
An agent gives your team back the hours currently spent on copy-and-paste, lookups, and transfers, while lowering the error rate. That this pays off is no longer a niche topic: according to Bitkom, 36 percent of German companies now use AI, nearly twice as many as the year before. The biggest lever is the process that runs by hand most often and most expensively in your company.
Which agents have we already built?
We build agents for concrete workflows, not as a demo. Two examples from practice:
- Invoices that book themselves: drop an invoice into the folder, the agent reads it via OCR, renames and files it, and enters the data in a structured way, with no manual input. View the case study
- From order to verified campaign: a multi-step workflow checks the address against the order via OCR, builds a personalised campaign, and leaves the final approval to a human. View the case study
How do I know the agent works reliably?
Every agent is built so its steps are traceable and verifiable. The human keeps control over critical decisions, and every action is logged, so you can trace any process back if in doubt.
How does a project run?
Every project follows three steps, so you get clarity on value and cost early:
- Potential analysis: we review your processes and show which agent delivers the biggest lever first. More on the potential analysis
- Implementation at a fixed price: you get a binding offer for a clearly defined agent, self-hosted on your infrastructure.
- Operation and further development: on request, we take over maintenance, monitoring, and further development as a fixed package. More on operation
What does an AI agent cost, and when does it pay off?
We build agents at a fixed price, and they pay off through the hours your team gets back. In the potential analysis we show up front which process has the biggest lever, so you automate first where it pays off fastest.
Who owns the code and data?
You do. The agent runs self-hosted on your infrastructure, your data stays in house, which makes GDPR-compliant use much easier than with a US SaaS. You own the code, with no per-user licence and no lock-in.
When is an AI agent worth it, and when not?
An agent is worth it for tasks that occur often, follow clear rules, and cost time today. For rare edge cases or decisions that need genuine judgement and responsibility, automation is the wrong path, or it belongs safeguarded with a human approval step. We tell you honestly when a process is not worth automating.