Smart Document OCR & LLM Document Intelligence 

Project Overview

This project delivers an AI prototype capable of extracting structured data from PDF invoices and technical documents using a combination of OCR and LLM reasoning. The system converts unstructured files into clean, reliable Excel datasets ready for accounting or downstream automation. 

Business Problem

Manual extraction from PDFs is slow, inconsistent and error-prone.

Documents differ in layout, structure and quality, making traditional rule-based parsing unreliable.

The client needed a lightweight, automated solution to read invoices, identify key fields and export the results into a unified format without manual intervention. 

Solution 

I developed a Python-based OCR + LLM pipeline that reads scanned PDF files, detects fields such as names, IDs, dates, totals and tax values, and exports everything into a structured Excel file.

The system uses GPT reasoning to handle layout variations and improves extraction accuracy beyond 90 percent in internal tests.

The prototype runs on a cloud GPU and is designed for future expansion to new document formats. I developed a Python-based OCR + LLM pipeline that reads scanned PDF files, detects fields such as names, IDs, dates, totals and tax values, and exports everything into a structured Excel file.

The system uses GPT reasoning to handle layout variations and improves extraction accuracy beyond 90 percent in internal tests.

The prototype runs on a cloud GPU and is designed for future expansion to new document formats. 

Project Milestones 

Project Conclusion 

This project delivers a complete, automated system for extracting structured data from invoices and technical PDFs using advanced OCR and GPT based reasoning. All documents are processed into clean, reliable Excel outputs ready for immediate use in accounting workflows.

The OCR module ensures high accuracy text extraction across variable layouts, while the LLM layer interprets fields, validates values and resolves inconsistencies. The result is a robust prototype that transforms unstructured PDFs into fully organized, machine-ready datasets.

This solution provides a strong foundation for future expansions, including multi-format support, multi-language OCR and deeper automation of financial document processing.

Impact

• Eliminates manual extraction and reduces processing time

• Produces standardized, high-quality datasets for accounting systems

• Improves accuracy thanks to OCR validation and GPT cross-checking

• Handles documents with different layouts and structures

• Easily extendable to new document types and additional data fields 

⭐ Client Reviews