Automated Invoice Data Extraction into SAP System
Problem to be Solved
Every day, this organization processes a large volume of invoice documents. Extracting information from unstructured data in files, images, PDFs, and emails takes up a lot of employees' time. Therefore, the organization needs an intelligent document processing system to automatically extract, categorize, and store this data into SAP without overburdening employees or increasing the risk of errors.
Problem Statement
- How can we handle large volumes of invoices with so many different formats? Each company may issue invoices with its own unique format.
- How can we reduce the effort of reviewing? Only review forms that are suspected to be inaccurate.
- How can we handle multiple languages? (for example, in European countries)
How QAI solution solves the problem?
- The system consists of a mail bot, a portal, and an AI engine.
- The Mail Bot can receive orders from users. Once it receives an order, it sends the information to the portal for processing.
- After the order is processed (via OCR), the mail bot sends a notification to the user about the processing results.
- In cases of data errors or when the confidence level is low, the mail bot sends an email to the operator for review.
- Portal allows files to be uploaded, extracts information, and exports data to SAP.
- The AI system, integrating OCR, NLP/LLM, and various image and text processing models, enables recognition of many types of invoices in different languages. The system can process new formats/layouts without requiring model retraining.
- The AI system also assesses the reliability of extracted information, highlighting invoices that need operator review.
Why the problem was not solved before?
- Too many formats.
- Diverse languages.
- Excessive review effort.
Results from the solution
- Average accuracy: >80%.
- Save processing time.
- Reduce errors in the SAP data entry process.
3/4/2025
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