How to Consistently Extract Metadata from Complex Documents

Extracting metadata from documents is crucial for downstream tasks like filtering and improving RAG systems. The process can be approached in three main ways: using simple but rigid Regex, a more flexible combination of OCR and an LLM, or the most powerful but costly Vision LLMs. Each method has trade-offs, with Vision LLMs being necessary for visual information like checkboxes or handling poor OCR on handwritten text. Key challenges include managing costs, processing long documents efficiently, and deciding which approach is best suited for the specific type of data being extracted.