# AI OCR for Tax Documents: Invoices, Balance Sheets & Tables (`acmegen.ai/ocr-tax-document-ai`) Actor

Extract structured data from invoices, receipts, balance sheets and tabular PDFs with AI. Returns issuer, dates, totals, taxes and tables as JSON. Upload a file or pass URLs; batch or real-time API.

- **URL**: https://apify.com/acmegen.ai/ocr-tax-document-ai.md
- **Developed by:** [Acmee AI](https://apify.com/acmegen.ai) (community)
- **Categories:** Automation, Integrations, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $450.00 / 1,000 tax document extracteds

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## 🧾 AI OCR for Tax Documents (Invoices, Balance Sheets & Tables)

Turn invoices, receipts, balance sheets, bank statements and tabular PDFs into **clean, structured JSON** with AI. Upload a file or pass document URLs, and get back the document type, issuer/recipient, dates, totals, taxes, line-item tables and a summary - ready for your accounting system or spreadsheet.

> 🎯 **Built for Tax & accounting teams.** Not a generic text dump: the AI detects the document type and extracts the fields that matter, plus the tables, preserving layout meaning.

***

### What you get (per document)

| Field | Description |
|---|---|
| `documentType` | invoice, receipt, balance\_sheet, income\_statement, bank\_statement, purchase\_order, table, other |
| `issuerName` / `issuerTaxId` | Vendor/company and tax ID (VAT, CNPJ, EIN...) |
| `recipientName` / `recipientTaxId` | Buyer/customer and tax ID |
| `documentNumber`, `issueDate`, `dueDate` | Document identification |
| `currency`, `subtotal`, `taxAmount`, `totalAmount` | Monetary fields (plain numbers) |
| `tables[]` | Extracted tables (line items, balances...) with columns + rows |
| `keyValues` | Any other labelled fields (payment terms, account no., period...) |
| `summary` | One-line description |
| `fileMetadata` | `type`, `sizeBytes`, `pageCount` (PDF) |

***

### How to use

**Upload a file** in the input, or **pass URLs** for batch:

```json
{
  "documentUrls": [
    "https://example.com/invoice.pdf",
    "https://example.com/receipt.jpg"
  ]
}
```

Supports **PDF, PNG, JPG and WebP**. Up to **50 documents per run** (send larger volumes via sequential calls). PDFs are read natively (multi-page); images are auto-optimized before analysis.

***

### Pricing

Charged **per document successfully extracted** (event `tax-document-extracted`). Documents that fail to download or can't be read are **not charged**.

***

### Example output

```json
[
  {
    "documentUrl": "https://example.com/invoice.pdf",
    "success": true,
    "documentType": "invoice",
    "issuerName": "ACME Ltda",
    "issuerTaxId": "12345678000190",
    "recipientName": "Globex Inc",
    "documentNumber": "INV-2024-001",
    "issueDate": "2024-03-15",
    "dueDate": "2024-04-15",
    "currency": "USD",
    "subtotal": 1100.0,
    "taxAmount": 150.0,
    "totalAmount": 1250.0,
    "tables": [
      { "title": "Line items", "columns": ["description", "qty", "unitPrice", "total"],
        "rows": [ { "description": "Consulting", "qty": 10, "unitPrice": 110, "total": 1100 } ] }
    ],
    "keyValues": { "paymentTerms": "Net 30" },
    "summary": "Invoice from ACME Ltda to Globex Inc, total USD 1250.",
    "fileMetadata": { "type": "pdf", "sizeBytes": 84210, "pageCount": 1 },
    "failureReason": null,
    "processedAt": "2026-01-01T12:00:00.000Z",
    "error": null
  }
]
```

***

### FAQ

**Which documents work best?**
Clear digital PDFs and sharp scans/photos. Very low-resolution or handwritten documents may not be readable - the reason is reported in `failureReason`.

**Does it handle multi-page PDFs?**
Yes. PDFs are read natively, including tables and layout, across pages.

**Can I upload a file directly?**
Yes - use the upload field in the input, or call the API with a document URL.

**Can I call it in real time?**
Yes. The Standby endpoint `POST /extract` responds synchronously. See below.

***

#### 🔌 API integration

**Batch run:**

```bash
curl -X POST "https://api.apify.com/v2/acts/acme-ai~ocr-tax-document-ai/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"documentUrls":["https://example.com/invoice.pdf","https://example.com/receipt.jpg"]}'
```

**Standby (`POST /extract`):**

```bash
curl -X POST "https://acme-ai--ocr-tax-document-ai.apify.actor/extract" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  --compressed \
  -d '{"documentUrls":["https://example.com/invoice.pdf","https://example.com/receipt.jpg"]}'
```

The token goes in the `Authorization: Bearer` header, never in the URL.

***

### Notes

This Actor analyzes documents you provide. You are responsible for having the right to process them and any personal or financial data they may contain.

# Actor input Schema

## `documentUrls` (type: `array`):

Upload one or more files (PDF, PNG, JPG, WebP) or paste public document URLs. Up to 50 per run.

## Actor input object example

```json
{
  "documentUrls": [
    "https://upload.wikimedia.org/wikipedia/commons/b/bc/Volkswagen_Invoice.jpg",
    "https://upload.wikimedia.org/wikipedia/commons/4/45/Tesco_grocery_receipt_Finchley_1994.jpg",
    "https://upload.wikimedia.org/wikipedia/commons/2/29/Cascadia_Wikimedians_User_Group_-_Balance_sheet_as_of_Dec_31%2C_2015.jpg"
  ]
}
```

# Actor output Schema

## `results` (type: `string`):

Extracted documents (one record per document).

# 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 = {
    "documentUrls": [
        "https://upload.wikimedia.org/wikipedia/commons/b/bc/Volkswagen_Invoice.jpg",
        "https://upload.wikimedia.org/wikipedia/commons/4/45/Tesco_grocery_receipt_Finchley_1994.jpg",
        "https://upload.wikimedia.org/wikipedia/commons/2/29/Cascadia_Wikimedians_User_Group_-_Balance_sheet_as_of_Dec_31%2C_2015.jpg"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("acmegen.ai/ocr-tax-document-ai").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 = { "documentUrls": [
        "https://upload.wikimedia.org/wikipedia/commons/b/bc/Volkswagen_Invoice.jpg",
        "https://upload.wikimedia.org/wikipedia/commons/4/45/Tesco_grocery_receipt_Finchley_1994.jpg",
        "https://upload.wikimedia.org/wikipedia/commons/2/29/Cascadia_Wikimedians_User_Group_-_Balance_sheet_as_of_Dec_31%2C_2015.jpg",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("acmegen.ai/ocr-tax-document-ai").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "documentUrls": [
    "https://upload.wikimedia.org/wikipedia/commons/b/bc/Volkswagen_Invoice.jpg",
    "https://upload.wikimedia.org/wikipedia/commons/4/45/Tesco_grocery_receipt_Finchley_1994.jpg",
    "https://upload.wikimedia.org/wikipedia/commons/2/29/Cascadia_Wikimedians_User_Group_-_Balance_sheet_as_of_Dec_31%2C_2015.jpg"
  ]
}' |
apify call acmegen.ai/ocr-tax-document-ai --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,acmegen.ai/ocr-tax-document-ai"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/xW8tX1bENPkzXnKuV/builds/WoBgC2misk3MpIybG/openapi.json