When LLMs fail on document workflows, people usually blame prompts or models.
But the real problem is often upstream: the input document is broken.
If your extracted content has mixed columns, lost structure, malformed tables, or inconsistent reading order, the LLM has to compensate for that chaos.
And when it compensates, it guesses.
This is why so many “LLM failures” are really input quality failures in disguise.
Fix the document layer, and you usually get:
- Simpler prompts
- More reliable outputs
- More auditable extractions
- Better scalability