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

{
  "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.