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AI-Powered Document Classification System for Construction Lifecycle Management
  1. case
  2. AI-Powered Document Classification System for Construction Lifecycle Management

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AI-Powered Document Classification System for Construction Lifecycle Management

yslingshot.com
Construction
Real Estate
Engineering

Challenges in Manual Document Management

Manual classification of 45,000+ construction-related documents (PDFs, Office files, images, AutoCAD drawings) caused input errors, workflow disruptions, and inefficiencies in document management processes.

About the Client

A multinational construction lifecycle management platform provider operating in the UK, Ireland, Australia, Qatar, and UAE

Project Goals for Automated Document Classification

  • Automate document classification using AI technologies
  • Reduce manual data entry errors by 96% document-level accuracy
  • Improve workflow efficiency across international operations
  • Ensure GDPR-compliant document handling
  • Support multi-format document processing

Core System Functionalities

  • Multi-label document classification (3 labels per document)
  • Tesseract OCR integration for text extraction
  • Ensemble machine learning model for 98% label-level accuracy
  • RESTful API for document classification
  • AWS cloud deployment with security compliance

Technologies for Implementation

OCR
NLP
Python
scikit-learn
Tesseract OCR
AWS

System Integrations

  • Existing Document Management System (DMS)
  • Cloud storage platforms
  • User authentication systems

Non-Functional Requirements

  • Scalability for 100k+ documents
  • 99.9% system uptime
  • GDPR compliance
  • Multi-region deployment support
  • Response time under 2 seconds

Expected Business Impact of AI Document Classification

Automated classification will eliminate manual entry errors, reduce processing time by 70%, enable seamless document management across 5 international markets, and achieve annual cost savings of $250k+ through improved operational efficiency.

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