# Aml Screening API (`vivid_astronaut/aml-screening`) Actor

- **URL**: https://apify.com/vivid\_astronaut/aml-screening.md
- **Developed by:** [BRAINIALL Team](https://apify.com/vivid_astronaut) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 results

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 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

## Aml Screening API

Aml Screening service powered by Azure. Fast, reliable, and scalable API.

### Features

- **Fast Processing**: Lightning-fast aml screening api powered by Azure
- **Reliable**: 99.9% uptime with automatic failover
- **Scalable**: Handle single requests or bulk operations
- **Secure**: Enterprise-grade security with API key authentication
- **Well Documented**: Comprehensive API documentation and examples

### Use Cases

- **Development**: Integrate into your development workflow
- **Automation**: Build automated pipelines
- **Integration**: Connect with other services

### Input Parameters

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `data` | object | No | Input data to process. Send your API request payload here. |
| `endpoint` | string | No | Specific endpoint to call (e.g., /api/v1/process) |

### Output Format

```json
{
  "success": true,
  "result": { ... },
  "timestamp": "2026-01-07T00:00:00Z"
}
```

### Code Examples

#### JavaScript (Node.js)

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

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const input = {
  "data": {},
  "endpoint": "/api/v1/process"
};

const run = await client.actor("vivid_astronaut/aml-screening").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

#### Python

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run_input = {
  "data": {},
  "endpoint": "/api/v1/process"
}

run = client.actor("vivid_astronaut/aml-screening").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)
```

#### cURL

```bash
curl -X POST "https://api.apify.com/v2/acts/vivid_astronaut~aml-screening/runs?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
  "data": {},
  "endpoint": "/api/v1/process"
}'
```

### Pricing

**Model**: Pay per result
**Price**: $0.005 per result

You only pay for successful results. Platform usage costs are included.

### API Documentation

Full API documentation is available at:

- [Apify API Reference](https://docs.apify.com/api/v2)
- [Actor API Endpoints](https://docs.apify.com/api/v2#/reference/actors)

### Support

- **Issues**: Report bugs via Apify Console
- **Documentation**: [Apify Docs](https://docs.apify.com)
- **Community**: [Apify Discord](https://discord.gg/apify)

### Version History

See [CHANGELOG.md](./CHANGELOG.md) for version history.

***

*Powered by Azure Cloud Infrastructure*

# Actor input Schema

## `data` (type: `object`):

Input data to process. Send your API request payload here.

## `endpoint` (type: `string`):

Specific endpoint to call (e.g., /api/v1/process)

## Actor input object example

```json
{
  "data": {},
  "endpoint": "example_endpoint"
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("vivid_astronaut/aml-screening").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("vivid_astronaut/aml-screening").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 '{}' |
apify call vivid_astronaut/aml-screening --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=vivid_astronaut/aml-screening",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/hejUcpHxbm1oUy8Q8/builds/P0wXXDda63bBRv80I/openapi.json