> ## Documentation Index
> Fetch the complete documentation index at: https://agents.nanonets.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Structured Data Extraction

> Extracts structured fields from documents (PDF, Office, CSV, images, markdown, XML, text) using AI.

Extracts structured fields from documents (PDF, Office, CSV, images, markdown, XML, text) using AI. Display name **"Data Extraction"**. On by default for new agents.

This output is already presentation-ready; don't reformat it with another AI step.

## Authentication and enablement

No integration. Uses the agent's extraction model. Password-protected files cannot be unlocked here — call `file_utils` with `operation: "unlock"` first, then pass the same file reference.

## Inputs

* `file_url` (required): document URL (`${VAR_N}` from an upload or prior step).
* `extraction_instructions` (required): what to extract, in natural language.
* `output_schema` — optional JSON Schema for the result shape (config-time; not shown as a per-run input).
* `model` — optional extraction-model override (configured tool).

## Output

Display-ready structured data, typically `{value, word_id_groups}` per field so citations work in the feed. Can merge/combine prior extraction results into one table when instructed.

## Limits and side effects

* Cannot open password-protected files.
* Large documents may paginate internally; free-tier orgs can hit a page cap.
* No external writes.

## Expected errors

* Missing `file_url` or `extraction_instructions`.
* Locked file (unlock with `file_utils` first).
* Unsupported or empty document.