# Extract team members from a company team page

**Use case:** 

Turn a company's people or team page into a table of names, job titles and profile links with one plain-English prompt. Point it at any team, speakers or staff page.

## Input

```json
{
  "urls": [
    "https://www.ycombinator.com/people"
  ],
  "prompt": "every person: name, job title and profile link",
  "maxItemsPerPage": 100
}
```

## Output

```json
{
  "url": {
    "label": "URL",
    "format": "string"
  },
  "status": {
    "label": "Status",
    "format": "string"
  },
  "itemCount": {
    "label": "Items",
    "format": "integer"
  },
  "title": {
    "label": "Page title",
    "format": "string"
  },
  "error": {
    "label": "Error",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Extract Data from Website: AI Structured Data Extraction Actor is ready to run with the inputs already set for "Extract team members from a company team page". [Sign up or log in](https://console.apify.com/create-task-from-example/MolrQDJfvZD5Xpw6y) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Extract team members from a company team page" task

The Extract Data from Website: AI Structured Data Extraction Actor will start running based on the input automatically. You can also change all the input fields, like page urls, what to extract, and more, to match your specific use case.

### 3. Receive the "Extract team members from a company team page" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as URL, status, items, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Extract team members from a company team page" task via API](https://apify.com/dtkfoundry/ai-page-extractor.md).

## About this Actor

This example demonstrates how to use [Extract Data from Website: AI Structured Data Extraction](https://apify.com/dtkfoundry/ai-page-extractor.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/dtkfoundry/ai-page-extractor.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/dtkfoundry/ai-page-extractor.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).