This project involved developing an AI-driven solution to automate the processing of invoices for KC Nederlands. The aim was to create a robust system capable of handling both text and image-based PDFs, extracting relevant data accurately and efficiently.

OCR Integration: Implemented Optical Character Recognition (OCR) to extract text from image-based PDFs.

PDF Text Extraction: Utilized Python libraries to directly extract text from text-based PDFs.

Entity and Table Extraction: Developed algorithms to identify and extract tables and specific entities (such as invoice numbers, dates, amounts, etc.) from the invoices.

TensorFlow and PyTorch: Leveraged TensorFlow and PyTorch for building and training deep learning models aimed at improving the accuracy of data extraction.

Research Paper Implementation: Integrated cutting-edge techniques and methodologies from recent research papers to enhance model performance.

LLM Open Source and OpenAI: Utilized large language models from open-source communities and OpenAI to improve the understanding and processing of invoice data.

FastAPI: Created a scalable and efficient API using FastAPI to allow seamless integration with other systems and applications used by KC Nederlands.

Duration: The project was developed over a span of 2 years.

User Base: The solution is currently utilized by over 300,000 users, indicating its effectiveness and reliability.

Programming Languages: Python

Frameworks and Libraries: TensorFlow, PyTorch, FastAPI

Technologies: OCR (Optical Character Recognition), PDF text extraction

AI and Machine Learning: Implementation of research papers, utilization of LLM (Large Language Models) from open-source and OpenAI

Machine Learning and AI: Expertise in TensorFlow, PyTorch, and large language models

API Development: Proficiency in creating APIs using FastAPI

Data Extraction: Advanced skills in OCR and PDF text extraction

Research Implementation: Ability to integrate cutting-edge research into practical applications

This comprehensive AI invoice automation system significantly enhances the efficiency of invoice processing, reducing manual effort and improving accuracy for KC Nederlands.