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Overview
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
Challenges
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.
Solution
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.
Development Process
Research
Planning
Designing
Development
Maintenance
Team & Role
A dedicated team of 12 individuals contributes their expertise to this
project, including:
project, including:
01
Process mapping
02
Web application development
03
UI/UX Designers
04
Quality assurance
05
Machine learning & AI pipeline design and development
06
Maintenance and ongoing support
Tools/Technologies
The project leverages a robust technology stack to ensure efficient
performance and reliability.
performance and reliability.
Technical Achievements
NLP and AI Services: Key focus on NLP and AI functionalities, including: