Ragie, a data processing tool, demonstrated impressive capabilities in a FinanceBench evaluation by efficiently handling over 50,000 pages of complex financial documents, outperforming Shared Store retrieval benchmarks by 42%. Despite excelling in text data processing, Ragie initially struggled with tables, a crucial component for accurate data interpretation. To address this, Ragie's table extraction and chunking pipeline was enhanced, incorporating advanced models for table structure detection, OCR for header and row extraction, and specialized chunking methods that preserve data integrity. These improvements resulted in a 25% increase in table extraction speed and superior performance in FinanceBench tests, with Ragie exceeding single store benchmarks by 58% and complex shared store benchmarks by 137%. These innovations have strengthened Ragie's ability to support developers with robust solutions for large-scale, multi-modal datasets.