---
title: AI Document Table Data Extraction API
slug: extract-table-data
url: https://apyhub.com/apyhub/service/extract-table-data
provider: ApyHub
categories: [Artificial Intelligence, Data Extraction, Image Processing]
auth: api_key
---

# AI Document Table Data Extraction API

Extract table data from a file or URL. Returns Azure or ApyHub parsing output for invoice, report, and document table capture.

## Endpoints

| Method | Path | Description | Atoms |
| --- | --- | --- | --- |
| POST | `/ai/document/extract/table/file` | What it does Extracts table data from a document at the provided URL and returns parsed results in… | 500 |
| POST | `/ai/document/extract/table/url` | What it does Extracts table data from a document or webpage referenced by a URL and returns parsed… | 500 |

## About

## What it does
Table Extraction helps you pull tabular data out of a file or a URL. Send a binary file to `POST /file` or a document URL to `POST /url`, and choose whether you want ApyHub's structured table extraction output or Azure Document Intelligence output by setting `requested_service`.

Use it when you need to turn PDFs or other table-bearing documents into machine-readable data for downstream processing. The file-based endpoint accepts `file` uploads and optional Azure credentials such as `azure_key`, `azure_region`, `azure_endpoint`, `azure_account_id`, and `azure_access_token`. The URL-based endpoint accepts `url` plus optional Azure credentials in an `azure` object. Both endpoints return a `data` object with `azure` and `apyhub` results, so you can compare the raw Azure parsing output with the structured ApyHub extraction output.

That makes Table Extraction useful for invoice capture, report ingestion, and spreadsheet-like data collection from documents that are not already structured. Build workflows that move table rows into your database, validate extracted line items, or feed document data into analytics pipelines.

If you already have documents stored remotely, use the URL endpoint. If you're processing uploads directly in your app, use the file endpoint.

| Provider (requested_service) | Atoms |
|------------------------------|------:|
| Azure                        |   500 |
| ApyHub                       |  2000 |

## Usage

Authenticate with an ApyHub API key in the `apy-token` header.
Full docs and a live playground: https://apyhub.com/apyhub/service/extract-table-data