AI & Automation
Relieve routine tasks, improve decision quality – without the hype.
AI as a Standalone Service – or Add-On to Your Project
AI is no longer a future topic – it is a practical tool for everyday relief. I offer AI automation standalone (e.g. for manual emails, data processing, reports) or as an add-on to ongoing ERP/compliance projects. This is not about “AI strategy” – it is about concrete automations that work tomorrow, with the tools available today.
Realistic Use Cases
Text-Based Routine Tasks Emails, standard texts, meeting notes, summaries – employees often spend 20–30 % of their time on these. With AI assistants and no-code tools, this can be significantly accelerated or fully automated.
Data Processing and Structuring Reading emails, extracting information, transferring it into systems – made for automation. Example: scanning invoices and automatically writing key data into your accounting software.
Management Reports and Dashboards Monthly reports are often a time-consuming manual process. Automated, the entire flow – data retrieval, calculation, distribution – runs on its own.
First Contact and Simple Inquiries An AI chatbot answers common questions and gathers information – only difficult cases are escalated to a person.
How We Proceed
Step 1: Identify Time Drains We look for tasks that occur regularly, cost significant time, and are rule-based – requiring little human intuition. Prerequisites: clear rules and consistent data.
Step 2: Select the Right Solution Sometimes an Excel macro is enough, sometimes you need a chatbot or a no-code platform. We evaluate based on cost, integration, security, and maintainability.
Step 3: Build and Test We build the automation step by step and test it with real data.
Step 4: Training and Handover Your team learns to understand the automation and adjust it when needed.
Limits of AI Automation
Making strategic decisions – AI summarises data, but the decision is yours.
Inventing new processes – Automation optimises what exists; it does not replace strategic thinking.
Handling unclear requirements – The clearer the rule, the better the result.
Replacing human relationships – Standard inquiries yes, real customer problems need a person.
A Concrete Example
A finance team spends 2–3 days every month on report generation: pulling data, updating formulas, creating charts, writing emails. Automated, everything runs on its own – from data retrieval at 06:00 to management notification. Cost: approx. 100–300 € per month. Setup: 2–3 days. ROI: recovered after two months.
Next Steps
AI automation is not all-or-nothing. If you have a repetitive, time-intensive process – whether in finance, HR, customer service, or back office – let us discuss whether automation makes sense.