Background
Our client required an AI-powered solution to detect fraudulent expenditure invoices and effectively extract critical data from scanned invoices of different complexities in order to streamline expense management and ensure regulatory compliance. To achieve these objectives, Elogix created a cutting-edge application that used OpenAI's GPT-3.5 model and a combination of NLP and ML techniques.
Problem Statement
The different formats of invoices were the major challenge while extracting the pertinent data from the scanned documents.
Solution
Using NLP and ML techniques, Elogix created an AI-driven solution for invoice data extraction:
Flexible Extraction
Our program avoids the use of field labels by adjusting to diverse invoice layouts.
PDF to Text Conversion
PyPDF2 was used to transform PDF files to text, allowing for data analysis.
NLP Methods
The use of Bag-of-Words (BOW) and Levenshtein distance aided in precise data processing.
User-Friendly Interface
Users can upload scanned invoice SDS files, review findings(after processing is complete), and export data in a summary format to CSV files.
The AI-powered application, developed by Elogix, demonstrated the revolutionary power of technology in invoice data extraction and invoice fraud detection. The solution provided our client with efficient expense management and precise data extraction from complicated invoices by seamlessly integrating AI models and innovative methodologies, creating a new standard for automation in these crucial areas.