Effectively using unstructured information is crucial for businesses aiming to stay competitive. Traditional data ingestion methods often struggle to maintain data quality and relevance, particularly when preparing massive datasets for AI-driven chat applications. Standard text parsers treat documents as simple text, ignoring complex structures like tables, figures, and hierarchical sections. This leads to significant context loss and misinterpretations, ultimately hindering the performance of Retrieval-Augmented Generation (RAG) systems. Our advanced insight generation approach offers a powerful solution by improving data ingestion and indexing through state-of-the-art AI, dynamic chunking, vector embedding, and intelligent indexing.
Preserving Structure and Context: Intelligent OCR and Document Intelligence
A key innovation in this pipeline is the integration of intelligent Optical Character Recognition (OCR) with Azure Document Intelligence. Unlike traditional OCR, our intelligent OCR recognizes complex document layouts, including tables, charts, and multi-column formats. These AI-powered capabilities preserve the original structure and hierarchy of the content, ensuring that crucial contextual information is retained. Document Intelligence further enhances this process by:
