---
title: "Extract Structured Data From Documents With Multimodal Models"
description: "Combine file parsing, page images, schemas, citations, and validation for dependable document extraction."
language: en
canonical: https://navinresearch.com/blog/multimodal/document-ai-extraction.md
topics: ["document AI extraction", "multimodal document processing", "structured data extraction"]
---

# Extract Structured Data From Documents With Multimodal Models

Combine file parsing, page images, schemas, citations, and validation for dependable document extraction.

**Short answer:** Use native text extraction when available, page images when layout matters, and a strict output schema for target fields. Preserve page references and mark uncertainty. Validate totals, dates, identifiers, and cross-field rules before downstream use.

## Implementation steps

1. Classify document type and detect unreadable or missing pages.
2. Extract text and layout with stable page identifiers.
3. Ask for only required fields plus page evidence.
4. Run domain validations and send exceptions to review.

## Validation checklist

- Create a labeled set spanning templates and scan quality.
- Measure exact field accuracy and missing-field behavior.
- Test prompt injection embedded inside documents.

## Common mistakes

- Sending hundreds of pages without retrieval.
- Guessing absent values.
- Discarding page-level evidence.

## Practical decision

Ship the smallest design that passes the checks above. Record the model, prompt, tool, dataset, and runtime versions used in testing so later changes can be compared rather than guessed. Recheck the linked documentation before relying on provider-specific limits, model names, prices, or preview features; those details change more quickly than the engineering principles in this note.

## Official sources

- [Google, Gemini image understanding](https://ai.google.dev/gemini-api/docs/image-understanding)
- [OpenAI, Structured outputs guide](https://platform.openai.com/docs/guides/structured-outputs)

---

Reviewed: 2026-08-24. This concise engineering note is educational, not a claim that Navin Research created or independently verified the cited provider technology.