PDF data extraction and validation with AI
Automation of the extraction of structured data from PDF documents to streamline backend processing and reduce manual workload
Client
Under a non-disclosure agreement (NDA)
Business challenges
- Manual processing of PDFs
- Time-consuming operations
- Lack of scalability
Our solutions
- Automated data extraction
- Optical character recognition (OCR) integration
- Document classification
- Data editing and validation
Project Implementation
To address the challenges of manual PDF processing, Twelvedevs developed an automated data extraction system that significantly improved efficiency and scalability. By integrating Amazon Textract for OCR and Amazon Bedrock for backend processing, the system reduced manual intervention and improved data accuracy.
The project began with research and development to evaluate the best OCR technology. The first MVP focused on converting data from PDFs into a predefined JSON schema for easy backend integration. In parallel, the system was tested for OCR performance, ensuring accurate data extraction from varied document formats.
Following MVP development, the team conducted integration testing, ensuring that both Textract and Bedrock delivered reliable results. The system's architecture was designed for future scalability, with plans for external user access and further optimization.
Future work includes integrating Amazon Comprehend for document classification, further reducing manual effort and enhancing workflow. The solution will continue to scale, meeting growing demands and improving operational efficiency.
Technology stack
- Node.js
- TypeScript
- Amazon Textract
- Amazon Bedrock
- Amazon Comprehend
- AWS
Key activities
Business outcomes
The implemented solution enabled the client to achieve the following results:
- Increase productivity by reducing manual document handling and cutting processing time
- Enhance accuracy by automating data extraction and reducing human errors
- Get flexible solution that can easily accommodate higher document volumes as the business expands
