# AI Hiring & Business Opportunity Radar (`four_leaf_communications/ai-hiring-opportunity-radar`) Actor

Monitor public Greenhouse, Lever, and Ashby job boards for AI, automation, cybersecurity, and sales expansion signals. Generate structured hiring intelligence reports and distinguish baseline findings from newly detected opportunities on subsequent scans.

- **URL**: https://apify.com/four_leaf_communications/ai-hiring-opportunity-radar.md
- **Developed by:** [Four Leaf Communications](https://apify.com/four_leaf_communications) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $100.00 / 1,000 hiring signal reports

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## AI Hiring & Business Opportunity Radar

**Turn public corporate job postings into structured hiring signals.** Monitor selected company job boards for activity related to artificial intelligence, business automation, cybersecurity, and sales-team expansion. Compare repeated scans to identify newly observed activity without re-reporting unchanged signals.

Built by **Four Leaf Communications**.

### What it does

- Reads publicly accessible job-board feeds hosted on **Greenhouse, Lever, and Ashby**.
- Classifies relevant postings into four categories: **AI / machine-learning hiring**, **business automation**, **cybersecurity**, and **sales hiring / team expansion** (three or more matching roles for the sales-expansion signal).
- Produces a **structured report per matching company and signal category**, with role counts, supporting job evidence, and observation details.
- Maintains **persistent scan history** across runs under the same Apify account, so unchanged findings are not repeatedly presented as new.
- Provides outputs in Apify's default dataset for review, export, or use in downstream workflows.

**Important:** Hiring activity is a research signal, not proof of a purchase budget, an approved project, or an actual hire.

### Quick start

1. Enter one or more public Greenhouse, Lever, or Ashby job boards in **Company job boards**. Each entry needs the provider and its board slug, along with the company name.
2. Choose the **Signals to report**. Leave **Optional persistent state store** empty for automatic history tracking.
3. Keep **Run safe synthetic demo** off when you want live data.
4. Click **Start**. Review **Output → Signal report dataset**. For regular monitoring, schedule repeat runs using an Apify task.

#### Example input

```json
{
  "boards": [
    {
      "provider": "lever",
      "boardSlug": "applydigital",
      "companyName": "Apply Digital",
      "region": "global"
    }
  ],
  "demoMode": false,
  "includeBaseline": true,
  "includeExisting": false,
  "signalCategories": [
    "AI_IMPLEMENTATION",
    "BUSINESS_AUTOMATION",
    "CYBERSECURITY",
    "SALES_HIRING"
  ]
}
```

Replace the example company and board slug with the organization you want to monitor. The board must have a publicly accessible, supported feed.

### Understanding the results

Each dataset item represents **one company-category hiring signal report**, not one raw job listing. Reports include fields such as:

| Field | Meaning |
| --- | --- |
| `companyName` | Company being monitored |
| `categoryLabel` | Matching hiring-signal category |
| `observationType` | Type of observation, including an initial `BASELINE_INVENTORY` |
| `isNewSincePriorScan` | Whether the signal is new relative to available prior history |
| `matchedActiveRoles` | Number of relevant currently observed postings |
| `newMatchingRoles` | Number of newly observed matching roles |
| `evidenceStrength` | Strength indicator based on matching evidence |
| `evidence` | Supporting job links and excerpts, where available |
| `observedAt` | Observation timestamp |

#### First scan vs. later scans

On the **first scan**, the Actor creates an inventory of the currently visible postings. If **Report matching roles on first scan** is enabled, qualifying baseline reports may appear. They are correctly labeled `BASELINE_INVENTORY`, **not** newly discovered jobs; `isNewSincePriorScan` is false.

On **subsequent scans**, the Actor compares observed postings with persistent history. By default, unchanged categories are not reported again. **Zero results can be a successful outcome**, meaning no qualifying new report was generated. Check the run log or `RUN_SUMMARY` for details.

Automatic history tracking has been validated across repeated runs. For consistent comparisons, keep running under the same Apify account with the same company-board configuration. Advanced users can supply an existing permitted store through **Optional persistent state store** (`stateStoreId`).

### Pricing

At launch, the pay-per-event price is **$0.10 per Hiring Signal Report** (one item written to the default dataset), plus a nominal **$0.00005 Actor Start** event. A baseline report is a chargeable report, just like a newly detected signal. Runs producing no reports incur no report-item charge. The current Apify Store pricing panel is the authority if pricing changes.

The synthetic demo uses illustrative data, not live company evidence. Because demo results may be written to the default dataset, they may also incur report-event charges when run as a paid Store Actor.

### Use cases

- Research companies investing in AI or automation talent.
- Watch cybersecurity hiring activity across a competitive set.
- Identify possible sales-organization expansion.
- Feed structured changes into internal research, reporting, and agent workflows.

### Coverage and limitations

- Supports **public Greenhouse, Lever, and Ashby feeds** only; this is **not** a universal job-search crawler.
- A job posting can remain online after a role is filled, and feeds may be delayed or unavailable.
- Classification is based on job-posting evidence. Results can contain false positives or miss relevant roles, so verify promising signals independently.
- The product does not provide private contact details, prove business intent, or send automatic email alerts. Scheduling and downstream notifications must be configured separately.
- Historical comparisons depend on continued access to the same persistent store and on the stability of the source data.

### Support

Developed by **Four Leaf Communications**. For product information, visit [4leafcommunications.com](https://4leafcommunications.com).

# Actor input Schema

## `demoMode` (type: `boolean`):

ON: run against fictional sample job feeds to check the output. Turn OFF to scan real company boards. Synthetic records are labelled in output.

## `boards` (type: `array`):

Provider and public board ID, e.g. the 'example' part of boards.greenhouse.io/example, jobs.lever.co/example or jobs.ashbyhq.com/example. No login, arbitrary URLs or private employee data.

## `signalCategories` (type: `array`):

Choose which kinds of posted-job evidence should appear in output. Job ads are not verified purchasing plans.

## `stateStoreId` (type: `string`):

Leave blank for automatic history tracking across runs in your Apify account. Advanced users can optionally select an existing key-value store they own with read/write permissions.

## `includeBaseline` (type: `boolean`):

For a new board without prior state, output CURRENT hiring evidence (marked BASELINE, not newly posted).

## `includeExisting` (type: `boolean`):

OFF: after the first scan, only output categories with a newly observed matching role. ON: output all currently matching categories on every run.

## Actor input object example

```json
{
  "demoMode": true,
  "boards": [
    {
      "provider": "lever",
      "boardSlug": "lever",
      "companyName": "Lever",
      "region": "global"
    }
  ],
  "signalCategories": [
    "AI_IMPLEMENTATION",
    "BUSINESS_AUTOMATION",
    "CYBERSECURITY",
    "SALES_HIRING"
  ],
  "includeBaseline": true,
  "includeExisting": false
}
```

# Actor output Schema

## `signals` (type: `string`):

Up to four reports per scanned company, each with up to five source-linked job posting excerpts.

## `summary` (type: `string`):

Scanned boards, successful/failed sources, job counts and whether change tracking was enabled.

# 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 = {
    "boards": [
        {
            "provider": "lever",
            "boardSlug": "lever",
            "companyName": "Lever",
            "region": "global"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("four_leaf_communications/ai-hiring-opportunity-radar").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 = { "boards": [{
            "provider": "lever",
            "boardSlug": "lever",
            "companyName": "Lever",
            "region": "global",
        }] }

# Run the Actor and wait for it to finish
run = client.actor("four_leaf_communications/ai-hiring-opportunity-radar").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "boards": [
    {
      "provider": "lever",
      "boardSlug": "lever",
      "companyName": "Lever",
      "region": "global"
    }
  ]
}' |
apify call four_leaf_communications/ai-hiring-opportunity-radar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,four_leaf_communications/ai-hiring-opportunity-radar"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/gbLWnYh4Pl8u9ShkY/builds/IuAE7HsFl7DytILUR/openapi.json