Challenges
Manual invoice processing ties up resources and is prone to errors. While traditional OCR systems can recognize text, they cannot understand its meaning or context. The goal was to develop an AI-based solution that semantically analyzes invoice content and automatically extracts relevant information such as supplier data, invoice numbers, or items—regardless of format. At the same time, a seamless connection to the existing ERP system via API was required to avoid media breaks.
Solution
As part of a prototype, we developed an AI-based application based on large language models (LLMs). The approach includes:
The solution recognizes structured content from unstructured PDF or image data, compares it with ERP master data and ideally carries out a dark booking. In case of unclear cases, targeted manual post-processing is required.
Results
Detection rates of over 90% have already been achieved in the prototype phase. The AI can flexibly process different invoice formats, improve data quality and significantly reduce manual effort. The solution thus creates the basis for scalable, automated invoice processing that saves time, prevents errors and is easy to integrate into existing systems.