Using Vision Language Models to Process Millions of Documents

Vision Language Models (VLMs) are powerful for processing documents where the meaning of text depends on its visual position, a task difficult for standard LLMs. Key application areas include agentic use cases like computer operation and debugging, visual question answering, document classification, and structured information extraction. Effective use involves creating detailed prompts that define categories, handle edge cases, and specify output formats like JSON. However, VLMs have limitations, including high computational costs from processing high-resolution images and difficulties with very long documents.