# Company Tech Stack from Job Postings — Technographics API (`wleeaf/company-tech-stack-from-jobs`) Actor

Find companies using Snowflake, Salesforce, Kubernetes, HubSpot and ~90 more tools, inferred from their own job postings across 17 ATSs and 1.7M jobs: 150K+ company×technology rows for 14,000+ companies, with job counts and dates. Ready for sales prospecting.

- **URL**: https://apify.com/wleeaf/company-tech-stack-from-jobs.md
- **Developed by:** [Taceddin Sancak](https://apify.com/wleeaf) (community)
- **Categories:** Lead generation, Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $20.00 / 1,000 company records

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

## Company Tech Stack from Job Postings

Find **companies that use a technology** — Snowflake, Salesforce, Kubernetes, HubSpot, Databricks, SAP and
\~90 more — inferred from their **own job postings**. Built from ~1.7M open roles across 17 applicant-tracking
systems (Greenhouse, Workday, Oracle Recruiting, SmartRecruiters, Lever, Ashby, BambooHR, Personio, …).

### What you get per row

| Field | Example |
|---|---|
| `company_name`, `country_code`, `ats` | Acme Inc · US · greenhouse |
| `technology`, `category` | Snowflake · data |
| `jobs_mentioning` | 4 open roles name the tool |
| `example_titles`, `departments` | Senior Data Engineer; Analytics Engineer · Data Platform |
| `first_posted`, `last_posted` | Dates of the matching postings |

### Why job postings

A company hiring a "Snowflake data engineer" is using Snowflake *now* — and is spending money around it.
That makes this list useful for:

- **Sales prospecting** — every account using a competitor or a complementary tool.
- **Partner/integration targeting** — companies on the platforms you integrate with.
- **Market sizing** — adoption of a tool by country and category.

### Example inputs

US companies with 2+ open roles mentioning Snowflake or Databricks:

```json
{"technologies": ["Snowflake", "Databricks"], "countries": ["US"], "minJobsMentioning": 2}
```

Check a target-account list for their CRM:

```json
{"companies": ["stripe", "datadog", "notion"], "categories": ["crm"]}
```

### Method

Only unambiguous names are matched with word boundaries; brand names that are also companies (Stripe, Notion,
SAP, OpenAI…) count only when the posting talks about *using* them, and a company's mention of its own name
is ignored. `jobs_mentioning` lets you require stronger evidence.

### Pricing

Pay per result: charged only for rows returned.

# Actor input Schema

## `technologies` (type: `array`):

e.g. Snowflake, Salesforce, Kubernetes, HubSpot, Databricks. Leave empty for all.

## `categories` (type: `array`):

e.g. data, crm, cloud, infra, ai, erp, security, marketing, observability, bi, database.

## `countries` (type: `array`):

Company's job location country, e.g. US, GB, DE.

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

Only rows for companies whose name contains any of these — check a target account list.

## `minJobsMentioning` (type: `integer`):

Raise to 2-3 for stronger evidence that the tool is in active use.

## `postedSince` (type: `string`):

Only companies with a matching posting on or after this date.

## `maxResults` (type: `integer`):

Maximum rows to return. You are charged per row returned.

## Actor input object example

```json
{
  "technologies": [
    "Snowflake"
  ],
  "minJobsMentioning": 1,
  "maxResults": 100
}
```

# Actor output Schema

## `companies` (type: `string`):

Company-technology rows with evidence from job postings.

# 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 = {
    "technologies": [
        "Snowflake"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("wleeaf/company-tech-stack-from-jobs").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 = { "technologies": ["Snowflake"] }

# Run the Actor and wait for it to finish
run = client.actor("wleeaf/company-tech-stack-from-jobs").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 '{
  "technologies": [
    "Snowflake"
  ]
}' |
apify call wleeaf/company-tech-stack-from-jobs --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,wleeaf/company-tech-stack-from-jobs"
        }
    }
}
```

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/o5gDcZPaTEuMml125/builds/RW9CJlzYjlHaYfrgx/openapi.json