Case Study: Centralizing Diverse E-Commerce Invoices Using Invoice LLM Model

Title

Case Study: Centralizing Diverse E-Commerce Invoices Using Invoice LLM Model

Author

1. Dharti Patel, Student, Sardar Patel University, Vallabh Vidya Nagar, India
2. Dr. H. B. Pandit, Professor, Sardar Patel University , Vallabh Vidya Nagar, India

Abstract

E-commerce platforms handle various invoices, including PDFs, handwritten documents, and scanned JPG images. This diversity in invoice formats presents significant challenges when centralising data for accounting and tax purposes. Manual processing leads to operational inefficiencies and limits scalability. This case study discusses how integrating an Invoice LLM (Large Language Model), combined with Optical Character Recognition (OCR) for handwritten and scanned invoices, helps extract and centralise key entities from different formats, reducing manual intervention and increasing operational efficiency.

Keywords

Conclusion

Combining OCR for handwritten and scanned invoices with an LLM-based entity extraction model offers an effective solution for e-commerce companies with diverse invoice formats. This approach automates the extraction process, enhances accuracy, and enables the centralisation of invoice data, allowing businesses to scale their operations efficiently. By adopting this technology, e-commerce companies can streamline their financial workflows, reduce manual labour, and ensure compliance with reporting standards.

Author Contrubution

The sole responsibility for the study design, data gathering, results analysis, and manuscript drafting lies with the author.

Funding

The authors received no financial support for the research, authorship, or publication of this article from any funding agencies.

Conflict of Interest

All authors confirm that there are no conflicts of interest associated with this research.

Data Sharing Statement

No data are available for sharing in this research.

Software And Tools Use

No particular software or tools were employed in this study.

Acknowledgements

My thanks go to those who assisted with this study and manuscript preparation, and to the peer reviewers for their constructive feedback.