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Custom Document Management System for Automated PDF Processing and Data Extraction

digiteum.com

Agriculture

Information technology

Challenges in Document Management and Data Extraction

The client faces significant inefficiencies in processing multi-format PDF invoices due to diverse document structures, non-standardized formats, and reliance on manual data verification. Existing OCR solutions lack accuracy for complex documents, leading to high operational costs and error rates.

About the Client

Agriculture analytics and research provider leveraging data-driven insights for agricultural productivity and sustainability

Project Goals for Automated Document Processing

Automate PDF invoice processing across diverse formats
Achieve 80%+ data extraction accuracy through custom algorithms
Reduce manual verification costs by 70%
Implement scalable cloud storage with AWS integration
Enable future expansion into a full document management ecosystem

Core System Functionalities and Features

Tesseract OCR integration for multi-format PDF text recognition
Custom data extraction algorithms for invoice metadata
Deep Learning-enhanced text recognition for scanned documents
Automated validation rules for data classification
AWS cloud storage integration with security protocols
User interface for document upload and result visualization
API for future system integrations

Technology Stack Requirements

Tesseract OCR v4

AWS Cloud Services

Python-based data processing pipelines

TensorFlow/PyTorch for Deep Learning

RESTful API architecture

System Integration Needs

AWS S3 for document storage
AWS IAM for security management
Third-party OCR services for comparative analysis

Operational Requirements

Horizontal scalability for 10,000+ daily document processing
99.9% system uptime SLA
End-to-end data encryption
Response time under 5 seconds for 95% of requests
Modular architecture for algorithm updates

Expected Business Impact of Automated Document Management

Implementation will reduce document processing time by 65%, decrease operational costs through automated validation, and enable 24/7 document processing capacity. The system's machine learning capabilities will continuously improve accuracy, supporting exponential growth in document volume while maintaining compliance with industry data standards.