LLM APIs for Document Processing: Extraction and Summaries

LLM APIs are useful for document workflows because they can understand messy text, summarize long content, extract fields, and answer questions.

Document processing is also one of the easiest ways to overspend if you send full documents to large models every time.

Common workflows

LLM document processing includes:

summarization
field extraction
contract review
invoice processing
policy Q&A
document classification
compliance review
search and retrieval

Each workflow needs different model and context choices.

Extraction needs validation

If you extract structured fields, validate outputs with schemas. Track missing fields, invalid values, and hallucinated data.

For important workflows, keep humans in the loop.

RAG vs long context

Use RAG when users ask narrow questions about large document collections. Use long-context models when the task requires broad understanding of an entire document.

Many systems use both.

Control document size

Reduce cost by:

removing boilerplate
deduplicating pages
chunking by section
summarizing intermediate content
routing simple documents to smaller models

Final thoughts

LLM APIs can transform document processing, but success depends on context strategy, validation, routing, and cost controls.