Editor's take

EasyOCR successfully extracts text from a scanned PDF, but Docling goes further by also identifying document structure like sections and figures.

This distinction is crucial for Retrieval Augmented Generation (RAG) applications. While EasyOCR provides raw text, making it difficult for RAG models to understand context and relationships within the document, Docling's structural understanding enables more accurate information retrieval and summarization. Enterprises relying on RAG for internal document analysis, such as those using models like GPT-4 or Claude 2, will find Docling's approach significantly more valuable for building robust knowledge bases.

Future developments should focus on the scalability and accuracy of Docling's structural parsing, particularly with complex layouts and older scanned documents. It will be important to observe how well Docling handles mixed-language documents and if its performance can rival proprietary solutions like Amazon Textract or Google Document AI in enterprise settings.