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Business Challenge

Hospitals and diagnostic centers manage massive volumes of documents daily. Traditional document processing methods present several key challenges:

Time-consuming: Manual data entry at scale demands significant human effort.

Error-prone: Human mistakes can lead to serious data inconsistencies.

Difficult to scale: As document volume grows, manual processes become inefficient and unsustainable.

Document OCR Solution

Our Solution: AI-Based Document Detection & OCR

To overcome these challenges, we introduced an AI-powered system that automates document detection, structure identification, and information extraction—designed specifically for the healthcare industry.

Document Workflow

How It Works

Input Image Acquisition: Documents are captured via scanners, mobile devices, or uploaded from digital sources.

AI Server Processing: Captured images are sent to an AI-powered vision model that detects and segments document structures such as tables, headers, and key-value pairs.

Data Storage & Processing: Extracted data is stored in a NoSQL database for easy retrieval and structured analysis.

The structured data can be used for automation, analytics, or integration with existing ERP systems.

Our Approach

Our Approach

Data collection

Annotation process

AI model training

Parsing and data structuring

Outcome Highlights

Up to 80% reduction in manual data entry efforts

Higher accuracy and consistency in document interpretation

Seamless integration with healthcare IT systems

Scalable and adaptable for large volumes of medical documents