# PDF to Structured Data (Excel/JSON) with OCR (`nibble/pdf-to-structured-data`) Actor

Convert PDF invoices, forms, statements and reports into clean structured JSON (text, tables, key/values) with an OCR fallback for scanned pages.

- **URL**: https://apify.com/nibble/pdf-to-structured-data.md
- **Developed by:** [Simon Fletcher](https://apify.com/nibble) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 file converteds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).


# README

PDF to Structured Data turns **PDF invoices, receipts, purchase orders, bank statements, forms and reports into clean, structured JSON** — full text, detected tables, and key/value fields — with an **OCR fallback for scanned pages**. Send a URL, an uploaded file, or a base64 payload; get back agent-ready data you can push straight into Excel, a database, or an AI workflow. Built on the [Apify platform](https://apify.com/actors), so you get an API, scheduling, and [integrations](https://apify.com/integrations) (Make, Zapier, n8n) out of the box.

### What does PDF to Structured Data do?

It reads each PDF you give it and emits **one structured record per document**:

- **`text`** — the full document text, whitespace-normalized.
- **`tables`** — every detected table as a clean rows/cells matrix (no HTML).
- **`keyValues`** — `Label: value` fields parsed out automatically (invoice number, dates, totals, account numbers…).
- **`pages`** — an optional per-page breakdown of text and tables.

Output is **agent-first**: compact JSON with no HTML blobs or nested junk, so it drops directly into AI agents (via the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp)), spreadsheets, or a data pipeline.

### Why use PDF to Structured Data?

- **Back-office automation** — convert incoming invoices, receipts and POs into rows for accounting/ERP import.
- **Data extraction at scale** — batch hundreds of PDFs per run via the API or a schedule.
- **AI/RAG ingestion** — feed clean text + tables to an LLM without a bespoke parser.
- **No subscription lock-in** — pay only for what you convert (see Pricing), instead of a fixed monthly SaaS seat.

### How to use PDF to Structured Data

1. Open the **Input** tab.
2. Provide your PDFs one of three ways:
   - **PDF URLs** — paste public links to the files.
   - **Uploaded files** — upload PDFs (passed as key-value-store keys).
   - **Base64 PDFs** — inline payloads for API/agent callers.
3. (Optional) toggle table extraction, key/value detection, per-page breakdown, or the OCR fallback.
4. Click **Start**. Each converted document appears as a row in the **Output** dataset.

### Input

| Field | Type | Description |
| --- | --- | --- |
| `pdfUrls` | array | Public URLs of PDFs to download and convert. |
| `keyValueStoreKeys` | array | Keys in the run's key-value store holding uploaded PDF bytes. |
| `pdfBase64` | array | Base64-encoded PDF payloads (inline). |
| `includePages` | boolean | Include the per-page `pages` breakdown (default `true`). |
| `extractTables` | boolean | Detect and emit tables (default `true`). |
| `detectKeyValues` | boolean | Parse `Label: value` fields (default `true`). |
| `ocrFallback` | boolean | OCR scanned/image-only pages with Tesseract (default `true`). |

Example input:

```json
{
  "pdfUrls": [{ "url": "https://example.com/invoice-1001.pdf" }],
  "extractTables": true,
  "detectKeyValues": true
}
````

### Output

Each input PDF becomes one dataset item. You can download the dataset in **JSON, CSV, Excel, or HTML**.

```json
{
  "source": "invoice-1001.pdf",
  "status": "ok",
  "error": null,
  "pageCount": 1,
  "text": "INVOICE\nInvoice Number: INV-1001\nDate: 2026-03-14\nBill To: Acme Corp\nItem Qty Price\nWidget 2 10.00\nGadget 1 25.00\nTotal: 45.00",
  "pages": [
    {
      "page": 1,
      "text": "INVOICE\nInvoice Number: INV-1001\n...",
      "tables": [[["Item", "Qty", "Price"], ["Widget", "2", "10.00"], ["Gadget", "1", "25.00"]]]
    }
  ],
  "tables": [
    { "page": 1, "index": 0, "rows": [["Item", "Qty", "Price"], ["Widget", "2", "10.00"], ["Gadget", "1", "25.00"]] }
  ],
  "keyValues": {
    "Invoice Number": "INV-1001",
    "Date": "2026-03-14",
    "Bill To": "Acme Corp",
    "Total": "45.00"
  },
  "meta": { "extractor": "pdfplumber", "ocrUsed": false, "charCount": 126, "tableCount": 1 }
}
```

#### Output fields

| Field | Type | Description |
| --- | --- | --- |
| `source` | string | The URL, key, or label of the input PDF. |
| `status` | string | `ok` or `error`. |
| `error` | string / null | Failure reason when `status` is `error`. |
| `pageCount` | number | Number of pages in the PDF. |
| `text` | string | Full normalized document text. |
| `pages` | array | Per-page `{ page, text, tables }` (when `includePages`). |
| `tables` | array | Detected tables as `{ page, index, rows }`. |
| `keyValues` | object | Parsed `Label: value` fields. |
| `meta` | object | `extractor`, `ocrUsed`, `charCount`, `tableCount`. |

A document that fails to parse returns a row with `status: "error"` and a reason — one bad file never aborts the rest of the batch.

**Very large documents:** Apify caps a single dataset row at ~9 MB. When a converted PDF's `text` + `pages` + `tables` would exceed that, the full record is written to the run's **key-value store** and the dataset row is trimmed: `pages` and `tables` are omitted, `text` is truncated, and the row carries `truncated: true` plus `fullResultKey` (the key-value-store key of the complete, untruncated record). `keyValues` and `meta` always stay complete inline.

### Pricing

This Actor uses **pay-per-event**: you are billed **per successfully converted document**, so you only pay for results. High-volume users can be moved to a flat monthly rental tier — see the Actor's pricing details. On a per-document basis this is dramatically cheaper than fixed PDF-extraction SaaS subscriptions.

### Tips and advanced options

- **Batch for efficiency** — pass many PDFs in one run to amortize startup cost.
- **Turn off OCR** (`ocrFallback: false`) for digital (text-layer) PDFs to run faster.
- **Turn off `includePages`** if you only need document-level `text`, `tables` and `keyValues` — the output gets smaller.

### FAQ and support

- **Does it handle scanned PDFs?** Yes — pages with no text layer are OCR'd with Tesseract. Digital PDFs are extracted directly (faster, more accurate).
- **What about pages rotated sideways?** Handled automatically. Pages flagged as rotated 90/180/270 degrees are read via OCR on the upright-rendered image (Tesseract), so `keyValues` and text are recovered correctly instead of coming out with broken line order. The output sets `"ocrUsed": true` for these pages. Correctly-oriented digital pages are extracted directly and are unaffected.
- **What about personal data?** You supply your own documents; process only files you're authorized to. Don't submit documents containing data you may not process.
- **Found a problem?** Use the **Issues** tab on the Actor page — include a sample PDF and the output you expected.

# Actor input Schema

## `pdfUrls` (type: `array`):

Public URLs of PDF files to convert. Each item is downloaded (with retries) and converted to structured data.

## `keyValueStoreKeys` (type: `array`):

Keys in this run's default key-value store that hold PDF bytes. This is how files uploaded via the Console form are passed to the Actor.

## `pdfBase64` (type: `array`):

Base64-encoded PDF payloads, for API or AI-agent callers that send the file inline instead of by URL.

## `includePages` (type: `boolean`):

Emit a 'pages' array with per-page text and tables. Turn off for a smaller, document-level-only output.

## `extractTables` (type: `boolean`):

Detect tables and emit them as row/cell matrices (great for invoices, statements, price lists).

## `detectKeyValues` (type: `boolean`):

Parse 'Label: value' lines (invoice number, dates, totals, …) into a keyValues object.

## `ocrFallback` (type: `boolean`):

If a page has no text layer (scanned/image-only), OCR it with Tesseract. Slower; leave on for mixed inputs.

## Actor input object example

```json
{
  "pdfUrls": [
    {
      "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
    }
  ],
  "includePages": true,
  "extractTables": true,
  "detectKeyValues": true,
  "ocrFallback": true
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "pdfUrls": [
        {
            "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("nibble/pdf-to-structured-data").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "pdfUrls": [{ "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf" }] }

# Run the Actor and wait for it to finish
run = client.actor("nibble/pdf-to-structured-data").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "pdfUrls": [
    {
      "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
    }
  ]
}' |
apify call nibble/pdf-to-structured-data --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=nibble/pdf-to-structured-data",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "PDF to Structured Data (Excel/JSON) with OCR",
        "description": "Convert PDF invoices, forms, statements and reports into clean structured JSON (text, tables, key/values) with an OCR fallback for scanned pages.",
        "version": "0.0",
        "x-build-id": "qdxk3R3CR0vRurZn7"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/nibble~pdf-to-structured-data/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-nibble-pdf-to-structured-data",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/nibble~pdf-to-structured-data/runs": {
            "post": {
                "operationId": "runs-sync-nibble-pdf-to-structured-data",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/nibble~pdf-to-structured-data/run-sync": {
            "post": {
                "operationId": "run-sync-nibble-pdf-to-structured-data",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "properties": {
                    "pdfUrls": {
                        "title": "PDF URLs",
                        "type": "array",
                        "description": "Public URLs of PDF files to convert. Each item is downloaded (with retries) and converted to structured data.",
                        "items": {
                            "type": "object",
                            "required": [
                                "url"
                            ],
                            "properties": {
                                "url": {
                                    "type": "string",
                                    "title": "URL of a web page",
                                    "format": "uri"
                                }
                            }
                        }
                    },
                    "keyValueStoreKeys": {
                        "title": "Key-value store keys (uploaded files)",
                        "type": "array",
                        "description": "Keys in this run's default key-value store that hold PDF bytes. This is how files uploaded via the Console form are passed to the Actor.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "pdfBase64": {
                        "title": "Base64 PDFs",
                        "type": "array",
                        "description": "Base64-encoded PDF payloads, for API or AI-agent callers that send the file inline instead of by URL.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "includePages": {
                        "title": "Include per-page breakdown",
                        "type": "boolean",
                        "description": "Emit a 'pages' array with per-page text and tables. Turn off for a smaller, document-level-only output.",
                        "default": true
                    },
                    "extractTables": {
                        "title": "Extract tables",
                        "type": "boolean",
                        "description": "Detect tables and emit them as row/cell matrices (great for invoices, statements, price lists).",
                        "default": true
                    },
                    "detectKeyValues": {
                        "title": "Detect key/value fields",
                        "type": "boolean",
                        "description": "Parse 'Label: value' lines (invoice number, dates, totals, …) into a keyValues object.",
                        "default": true
                    },
                    "ocrFallback": {
                        "title": "OCR fallback for scanned pages",
                        "type": "boolean",
                        "description": "If a page has no text layer (scanned/image-only), OCR it with Tesseract. Slower; leave on for mixed inputs.",
                        "default": true
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```