Developed a customizable PDF data extraction engine with OCR support for scanned PDFs, designed for speed, accuracy, and scalability. The solution significantly reduced processing time while enhancing data quality and operational efficiency.

Reduced processing time from 4 minutes to 0.2 seconds.

Achieved near 100% accuracy, eliminating reliance on external models.

Cut operational costs by 90%+ through in-house optimizations.

Engineered a precise table extraction mechanism for complete control over data formatting.

Ensured structured outputs for easy integration into downstream applications.

Built an automated error-handling framework for real-time failure detection.

Enabled swift issue resolution to maintain uninterrupted processing.

Leveraged AWS services (Lambda, S3, Textract) to create a fully scalable pipeline.

Ensured seamless deployment and cost-effective processing across large datasets.

🚀 Success Highlights:

Extreme Speed Gains: 99.95% reduction in processing time.

Cost Savings: Over 90% reduction in operational expenses.

Scalability & Accuracy: Optimized architecture for enterprise-level data processing.

This solution revolutionized PDF data extraction by delivering unmatched speed, accuracy, and cost-efficiency, providing a powerful alternative to traditional models.