---
title: AI Text Keyword Extraction API
slug: extract-keywords-from-text
url: https://apyhub.com/apyhub/service/extract-keywords-from-text
provider: ApyHub
categories: [Artificial Intelligence, SEO]
auth: api_key
---

# AI Text Keyword Extraction API

Extract keywords from plain text for tagging, search, and content analysis. Supports ApyHub or Azure results with optional language selection.

## Endpoints

| Method | Path | Description | Atoms |
| --- | --- | --- | --- |
| POST | `/ai/text/extract/keywords` | Extract keywords from text Extracts keywords from the text you provide in the request body. You can… | 500 |

## About

## What it does
Keyword Extraction helps you send text and get the most relevant keywords back. Use it when you need a quick way to summarize a document, index content, or power search and tagging workflows.

POST a `body` object with `text`, and optionally set `language`. If you want ApyHub to handle the request, leave `requested_service` at its default of `apyhub`; if you need to route through Azure, set it to `azure` and include the `azure` credentials object. The service is designed for plain text input, so it fits articles, support tickets, notes, and other unstructured content.

The response returns a `data` object with either an `apyhub` result or an `azure` result, depending on the service you request. That makes it useful for building content pipelines where you need keyword signals for search relevance, topic clustering, or lightweight document classification.

If you are normalising incoming text at scale, Keyword Extraction gives you a simple interface for turning raw paragraphs into structured keyword output without adding a separate NLP step to your app.

| 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-keywords-from-text