AT A GLANCE
A scalable document processing solution was developed to extract and analyze text and tables from a large corpus, enable real-time semantic search, and support topic modeling and entity recognition. The system streamlined access to insights, improved usability by 80%, and enhanced decision-making with rapid searches and comprehensive data organization.
Client information
CHALLENGE
The client required an advanced system to extract text and tables from a large document corpus (38 books), enable efficient semantic search, and support topic modeling and entity recognition for faster knowledge discovery and improved decision-making, all while handling large-scale data processing.
SOLUTION
A robust document processing pipeline was developed using Tesseract OCR and Cascade TabNet for accurate text and table extraction from PDFs. The extracted data was integrated into an interactive Dash app with semantic search capabilities, powered by Top2Vec for topic modeling and Scispacy for entity recognition. Additionally, a GPU-accelerated semantic similarity pipeline leveraging Rapids ensured fast, scalable searches across the document corpus, enabling high-performance access to relevant insights.
IMPACT
TOOLS
Ready to achieve measurable results? Tell us about your challenges, and we’ll show you how we can help
