Cloud System for Document Digitization

Azati, in collaboration with DIGATEX, developed a custom AI-powered document digitization system for complex engineering documents. The solution helps process, extract, and collate data from technical documents such as pipeline layouts, industrial plans, and maps.

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All Technologies Used

Java
Java
Pandas
Pandas
Python
Python
Keras
Keras
Scikit-Learn
Scikit-Learn
Numpy
Numpy
Tensorflow
Tensorflow
Tesseract
Tesseract
OCR
OCR
MongoDB
MongoDB
Matplotlib
Matplotlib

Motivation

The goal was to create a fast and cost-effective solution for digitizing large volumes of complex documents. The customer needed a way to automate the extraction of data from a wide range of documents with flexible structures and custom abbreviations.

Main Challenges

Challenge 1
Identifying Document Templates

Documents came from many different vendors, each with their own templates. The challenge was to automatically identify the correct template for each document.

Challenge 2
Extracting Data from Complex Documents

Each document template had a unique set of fields, custom abbreviations, and symbols, making it difficult to extract data.

Challenge 3
Overcoming Data Obscuration

Many technical documents had layers of information, with important data obscured by other elements or abbreviations.

Key Features

  • Document Digitization Module: Converts physical documents into digital format using OCR powered by AI.
  • Data Extraction Module: Automatically identifies and extracts data from various document templates.
  • Error Detection Module: Ensures the accuracy of extracted data by flagging potential errors.
  • Performance Monitoring Module: Tracks the system’s performance, enabling real-time adjustments to improve efficiency.

Our Approach

Researching OCR Technologies
Azati decided to build a custom Optical Character Recognition (OCR) engine powered by Artificial Intelligence.
AI Model Development
The team built an AI model that works similarly to human cognition, using algorithms to detect and extract data from flexible documents.
MVP Creation
Azati’s engineers created an MVP in less than two weeks, processing the first set of documents and achieving an impressive accuracy rate.
Continuous Improvement
With continuous tuning, the system’s accuracy improved to 97%, ensuring reliable data extraction.

Project Impact

AI-powered Solution: Azati’s AI-powered solution revolutionized the customer’s document processing workflow.

Automation and Efficiency: By automating the identification of templates and the extraction of data, the solution significantly increased throughput.

Reduced Costs: The system reduced document processing costs by five times, freeing up 30 employees from routine tasks.

Faster Processing: The system processed 120,000 documents in less than 24 hours, achieving a fourfold decrease in data extraction time.

Faster Time to Market: The project was completed in six weeks, far ahead of the customer’s original six-month timeline.

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