# Triage urgent restaurant reviews with AI

**Use case:** 

Scan five recent reviews for one restaurant, classify critical feedback with Bayesian triage and export structured JSON. Dry-run mode skips event charges and state writes.

## Input

```json
{
  "placeUrls": [],
  "query": "restaurant Luxembourg",
  "maxPlaces": 1,
  "maxReviewsPerPlace": 5,
  "alertThreshold": 3,
  "dryRun": true,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

## Output

```json
{
  "place": {
    "label": "Business",
    "format": "string"
  },
  "author": {
    "label": "Author",
    "format": "string"
  },
  "rating": {
    "label": "Rating",
    "format": "number"
  },
  "date": {
    "label": "Review date",
    "format": "string"
  },
  "urgency": {
    "label": "Urgency",
    "format": "string"
  },
  "urgencyConfidence": {
    "label": "Urgency confidence",
    "format": "number"
  },
  "isNew": {
    "label": "New review",
    "format": "boolean"
  },
  "alerted": {
    "label": "Slack alert sent",
    "format": "boolean"
  },
  "text": {
    "label": "Review text",
    "format": "string"
  },
  "verdict": {
    "label": "Verdict",
    "format": "string"
  }
}
```

## How it works

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

The Google Maps Review Alerts to Slack — new reviews only Actor is ready to run with the inputs already set for "Triage urgent restaurant reviews with AI". [Sign up or log in](https://console.apify.com/create-task-from-example/CX1fzNUDt8cWVskfi) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Triage urgent restaurant reviews with AI" task

The Google Maps Review Alerts to Slack — new reviews only Actor will start running based on the input automatically. You can also change all the input fields, like place urls, search query (alternative), and more, to match your specific use case.

### 3. Receive the "Triage urgent restaurant reviews with AI" 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 business, author, rating, 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 "Triage urgent restaurant reviews with AI" task via API](https://apify.com/travelmonitorlab/review-radar.md).

## FAQ

### How does this task classify urgent reviews?

Review Radar applies a Bayesian classifier to review text and returns urgency plus a confidence score for each collected review.

### Will this task repeatedly report old reviews?

With dryRun disabled, Review Radar uses persistent state to distinguish new reviews from reviews already seen.

### What input should I change first?

Replace the restaurant query with your business name and city, or supply canonical Google Maps place URLs in your duplicated task.

## About this Actor

This example demonstrates how to use [Google Maps Review Alerts to Slack — new reviews only](https://apify.com/travelmonitorlab/review-radar.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/travelmonitorlab/review-radar.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/travelmonitorlab/review-radar.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`).