Career history
In the news
- Our internal AI hackathon was about timesheet accuracy. A textbook example of data quality as the foundation for AI. At tillit and DATAshaper we believe in practice what you preach. So we tackle our own processes too, not just those of clients. Timesheets feed invoicing, planning and reporting. Without correct data going in, no reliable insights or AI coming out. Five teams, one problem, each from a different angle. Our framework was the common thread: - Strategy: fewer wrong invoices and credit notes, so direct time
- Sovereign AI, applied to not the sexiest topic: an ERP data migration. We needed the Installed Base, the equipment installed at our customers. It didn't exist as structured data anywhere. It was hidden in thousands of free-text customer notes. The classic approach: a team reading note by note for days and retyping serial numbers, brands and models into an Excel. Repetitive, slow and extremely boring work. Instead we let an LLM read the notes and extract everything into a structured dataset that DATAshaper prepares for SAP.
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