Angular, AWS, MySQL, NnodeJs, Python

Insurance Claim
Claim Processing System


Our comprehensive system streamlines insurance processes, including automated claims handling, payment management, and AI-driven claim classification. Integration with an EHR system enhances efficiency, while a user-friendly interface allows real-time human intervention for AI-generated outputs.


Manual Processing Strain:
Traditional manual sorting and data extraction made insurance claim handling time-consuming and error-prone.
Data Extraction Challenges:
Inaccuracies from manual data extraction and standard OCR tools hindered the quality of processed claims.
Resource-Intensive Labeling:
Manual labeling of vast data for AI training was resource-intensive and prone to errors.
Limited Automation:
Existing systems lacked automation, leading to delays due to the need for human intervention.


AI-Powered Automation:
Developed an AI system to automate claims handling, utilizing deep learning to classify and sort scanned documents.
Precise Data Extraction:
Implemented advanced image segmentation and OCR techniques, enhancing data extraction accuracy.
Efficient Labeling Process:
Streamlined data labeling and cleaning methods, improving AI algorithm accuracy and efficiency.
Real-Time Expertise:
User-friendly interface allows real-time human intervention for AI-generated outputs, ensuring accuracy.
EHR Integration Efficiency:
Integrated EHR systems for seamless patient data incorporation, reducing errors and redundancy.
Moreover, we also integrated the new website with the capital markets to assist the visitors seamlessly.

Development Process











Sales & ROI

As a result of the new properly designed website, our client FINews, was able to engage with the
audience well and close more sales in a short span of 2 months. They gained the ROI after 3
months with our assistance.


Conversion rate
in 2022


Increase in monthly

Team & Role

A dedicated team of 15 individuals contributes their expertise to this project, including:

  • Process mapping
  • UI/UX design
  • Web application development
  • Machine learning & AI pipeline design and development
  • Quality assurance
  • Maintenance and ongoing support

Tools / Technologies

The project leverages a robust technology stack to ensure efficient performance and reliability.



NodeJS / Express


Python / Flask

(Machine Learning & AI)




(Deep Learning)


(Cloud Infrastructure)


(Image Processing)




FINews’s objective was to build a user-friendly and aesthetically pleasing website that would
encourage greater traffic and sales. Deline Media was able to develop a user-friendly and
responsive website for them which enabled their customers to explore the capital market and
current forex rates fast enough.

Technical Achievements

Deep Learning Classification Architecture:
We have successfully designed and trained a comprehensive deep learning architecture and pipeline for insurance company classification based on scanned images. The pipeline can effectively identify the corresponding insurance company from scanned images.
Image Segmentation and OCR:
Our developed deep learning pipeline efficiently segments images and extracts relevant information. This capability is particularly useful for identifying and cropping areas with pertinent information for OCR purposes.
Enhanced OCR Accuracy:
We have extensively worked with various OCR engines to extract text information from images. Moreover, our expertise includes training open-source OCR engines like Tesseract to enhance their accuracy and performance.
Data Labeling and Cleaning:
We bring substantial experience to the table in terms of labeling and cleaning thousands of documents, a critical aspect in training AI algorithms for improved accuracy and efficiency.

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New York, USA
Lahore, Pakistan
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