# Multi-ATS Compliance Program Demand Intelligence (`neuton/multi-ats-compliance-program-demand-intelligence`) Actor

Research compliance mentions in Greenhouse, Lever and Ashby jobs with source excerpts, framework counts and explicit sample coverage. No inferred buying intent.

- **URL**: https://apify.com/neuton/multi-ats-compliance-program-demand-intelligence.md
- **Developed by:** [Neuton Scripts](https://apify.com/neuton) (community)
- **Categories:** Jobs, Business, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$18.00 / 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/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

## Multi-ATS Compliance Program Demand Intelligence

Find SOC 2, ISO 27001, PCI DSS, HIPAA, GDPR, and FedRAMP mentions in public Greenhouse, Lever, and Ashby job descriptions. For GRC research and account qualification, see which published roles mention a framework and read the exact supporting excerpt. A mention does not establish certification, software adoption, buying intent, budget, or a role requirement: it can also appear in employer boilerplate.

### Start in 30 seconds

```json
{
  "companies": [
    {
      "company": "Stripe",
      "boards": [
        {
          "provider": "greenhouse",
          "slug": "stripe"
        }
      ]
    },
    {
      "company": "Cloudflare",
      "boards": [
        {
          "provider": "greenhouse",
          "slug": "cloudflare"
        }
      ]
    },
    {
      "company": "OpenAI",
      "boards": [
        {
          "provider": "ashby",
          "slug": "OpenAI"
        }
      ]
    },
    {
      "company": "Palantir",
      "boards": [
        {
          "provider": "lever",
          "slug": "palantir"
        }
      ]
    }
  ],
  "maxJobsPerCompany": 100,
  "termDictionary": [
    "SOC 2",
    "SOC2",
    "ISO 27001",
    "ISO27001",
    "PCI DSS",
    "PCI-DSS",
    "HIPAA",
    "GDPR",
    "FedRAMP"
  ]
}
```

Run the sample, inspect the Dataset, then replace the companies and public ATS identifiers. Save recurring inputs as Apify Tasks or call this Actor through API, webhooks, Make, n8n, Zapier, ChatGPT, Claude, or Neuton Actors MCP.

### Output

Each complete, matching company analysis includes `company`, `totalOpenJobs`, `jobsAnalyzed`, `sampleCapped`, `matchedJobs`, `complianceCounts`, `evidenceJobs`, `evidenceJobUrls`, `boardSnapshots`, and `scrapedAt`. Each evidence job includes its title, public URL, provider, and literal matched excerpts. `technologyCounts` and `technologyShares` are compatibility fields for the same canonical compliance terms. Aliases such as SOC2 and SOC 2 count once per job. There is no purchase-intent score or inferred buyer team.

`totalOpenJobs` is the fetched unique population from the selected boards, not every opening a company may have. `jobsAnalyzed` is the bounded sample, ordered by provider and source job ID; it is not a latest-jobs or statistically representative sample. `sampleCapped` is true when that sample excludes jobs. Term shares use the analyzed sample as the denominator.

### Buyer workflows

- Research target accounts from source-linked compliance mentions
- Compare literal compliance-framework mentions on a schedule
- Send evidence-backed company signals into CRMs, warehouses, alerts, and RAG workflows
- Compare companies across Greenhouse, Lever, and Ashby public boards
- Keep absent, unknown, and unsupported signals explicit instead of inventing data

### Pricing

Launch price: **$18.00 per 1,000 completed company analyses** ($0.018 each). One fully fetched, analyzed company with at least one matching mention produces one billable row. A completed company with no matching mentions produces no chargeable row. If any requested source fails, the entire run fails before output and no result rows are billed. Diagnostics and duplicate inputs are not billed. Confirm the live price in the Actor's pricing panel before running.

### Reliability and data contract

This HTTP-only Actor uses public board endpoints without account cookies or a proxy. Supply 1-10 companies with 1-3 boards each, 1-25 terms, and a 1-500 job analysis cap. Only Greenhouse, Lever, and Ashby are supported. Full source retrieval is required before analysis, so the analysis cap does not limit download size. Responses are bounded at 24 MB; Lever pagination is bounded at 2,000 jobs per board. Oversized, malformed, incomplete, or inaccessible boards fail closed.

After clicking Run, open the Dataset to inspect company rows and `evidenceJobs`; use Export for JSON or CSV. Check `RUN_SUMMARY` in the key-value store to distinguish complete no-match results from source failures. Save a small known-good input as a Task before scheduling broader research. Through Neuton MCP or the Apify API, request the same bounded input and inspect the run status and summary before using the dataset in an AI answer.

### Responsible use

Use public hiring evidence for legitimate recruiting, sales research, market analysis, education planning, and investment research. Do not infer protected characteristics, private budgets, layoffs, employee performance, or guaranteed purchase intent. Do not use results for spam or consequential automated decisions. Verify material decisions against the linked source.

### SEO keywords

compliance hiring research, SOC 2 job mentions, ISO 27001 hiring data, FedRAMP job descriptions, GRC account research, Greenhouse jobs, Lever jobs, Ashby jobs, public ATS compliance evidence, MCP company research.

# Actor input Schema

## `companies` (type: `array`):

1-10 companies, each with 1-3 public boards. Supported providers: greenhouse, lever, ashby. Slugs contain letters, digits, underscores or hyphens. URLs and credentials are not accepted.

## `maxJobsPerCompany` (type: `integer`):

Analyze up to this many jobs ordered by provider and job ID. Full board retrieval is still required. Output distinguishes fetched population from capped sample.

## `termDictionary` (type: `array`):

Case-insensitive public job-text terms used by the deterministic analysis.

## Actor input object example

```json
{
  "companies": [
    {
      "company": "Stripe",
      "boards": [
        {
          "provider": "greenhouse",
          "slug": "stripe"
        }
      ]
    },
    {
      "company": "Cloudflare",
      "boards": [
        {
          "provider": "greenhouse",
          "slug": "cloudflare"
        }
      ]
    },
    {
      "company": "OpenAI",
      "boards": [
        {
          "provider": "ashby",
          "slug": "OpenAI"
        }
      ]
    },
    {
      "company": "Palantir",
      "boards": [
        {
          "provider": "lever",
          "slug": "palantir"
        }
      ]
    }
  ],
  "maxJobsPerCompany": 100,
  "termDictionary": [
    "SOC 2",
    "SOC2",
    "ISO 27001",
    "ISO27001",
    "PCI DSS",
    "PCI-DSS",
    "HIPAA",
    "GDPR",
    "FedRAMP"
  ]
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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("neuton/multi-ats-compliance-program-demand-intelligence").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("neuton/multi-ats-compliance-program-demand-intelligence").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 '{}' |
apify call neuton/multi-ats-compliance-program-demand-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,neuton/multi-ats-compliance-program-demand-intelligence"
        }
    }
}
```

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/YpSZ5gWvTemGCdQfP/builds/DFVvkqlSY2XUJWLK1/openapi.json