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OCR & eSignature Integration

Browser-Based OCR & eSignature Integration
Document Management | United States

OCR & eSignature Integration

Overview

The US-based healthcare client needed a solution to extract and process information from document images while supporting a seamless eSignature workflow. The project focused on using browser-based OCR to capture text, organize the extracted information, and integrate it with Adobe Sign.

Challenges
Challenges

Browser-Level OCR:

Text extraction was limited by browser based OCR capabilities.


Image Quality:

High-resolution image snippets with clear text were required for reliable extraction.


Data Categorization:

Extracted information needed to be organized using defined patterns.


Future Scalability:

The solution needed options to support more complex data processing.

Solutions
Solutions

Offline HTML Solution:

Built the POC within a single HTML file without complex server setup.


Tesseract.js OCR:

Enabled automatic text extraction from image snippets.


RegEx Data Processing:

Used predefined patterns to categorize extracted information.


Adobe Sign Integration:

Passed extracted data to Adobe Sign through predefined URL parameters.

Result
Results
  • OCR Proof of Concept, delivered as a browser-based solution.

  • Automated Text Extraction, from image snippets.

  • Structured Data Processing, using predefined RegEx patterns.

  • eSignature Integration, through Adobe Sign.

Conclusion
Conclusion

This project demonstrated a browser-based approach to OCR and data processing using Tesseract.js and RegEx, with Adobe Sign integration for eSignature workflows. The POC also established scalability options through cloud OCR services or a custom Python backend.

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