Documents underlie every business process. Traditionally, businesses fully depended on people to understand and process them, before their approach evolved to incorporate AI and automation. With the advent of AI agents—AI-based software entities able to plan, work, and make decisions independently—document-driven processes can now be automated end to end, freeing people for more important tasks.
However, AI agents struggle with consistency and scale. Typical AI agents perform well when asked to understand and process a small number of simple documents. Yet, accuracy and performance degrade at an enterprise scale of hundreds, thousands, or even millions. Furthermore, complex documents—containing elements like embedded tables, graphs, and inferred values—can be a real challenge for agents to understand.