# Built In Tech Companies Scraper (`automation-lab/builtin-companies-scraper`) Actor Scrape tech company profiles from Built In — name, location, industries, tech stack, headcount, and more. Filter by city or scrape all. - **URL**: https://apify.com/automation-lab/builtin-companies-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Built In Tech Companies Scraper Extract structured company profiles from [Built In](https://builtin.com/companies) — the leading tech company directory. Get company name, HQ location, industries, tech stack, employee count, website, and more — all in one clean JSON dataset. ### 🏢 What does it do? This actor crawls Built In's company directory and profile pages to extract comprehensive company data. For each company, it returns: - **Company identity**: name, slug, profile URL, website, logo - **Location data**: HQ city, state, country, street address, zip code - **Headcount**: total employee count - **Industries**: all industry tags (Cloud, Software, FinTech, etc.) - **Tech stack**: every technology listed on the company profile (programming languages, frameworks, tools, SaaS products) - **Jobs link**: direct URL to the company's open positions on Built In You can scrape the full global directory (1,000+ companies), filter by city (Austin, Boston, Chicago, NYC, SF, Seattle, and 80+ other locations), or supply a list of specific company URLs. ### 👥 Who is it for? **B2B Sales & Outreach Teams** — Build targeted prospect lists filtered by tech stack, location, and headcount. Know which CRM a company uses before your first call. **Technical Recruiters** — Find companies using the specific technologies your candidates know. Filter Austin-based companies with 200–500 employees using React and AWS. **Market Intelligence Analysts** — Track tech adoption across the industry. Which frameworks are gaining share in NYC fintech? Built In's tech stack data answers that. **Competitive Intelligence** — Monitor industry peers, benchmark headcount trends, and map the technology landscape of a vertical. **Data Enrichment Pipelines** — Augment your CRM or data warehouse with fresh company profiles and tech stacks at scale. ### ✅ Why use this actor? Built In is a curated, high-quality directory of tech companies that self-report their stack and culture. Unlike LinkedIn or Crunchbase: - **Tech stack is explicit**: Companies list their actual technologies, not inferred from job postings. - **Location is precise**: Built In tracks city-level presence across 80+ US metros and international hubs. - **Data is self-maintained**: Companies update their profiles to attract talent, so data is current. - **No login required**: All data is publicly accessible. ### 📦 Data extracted per company | Field | Type | Description | |-------|------|-------------| | `name` | string | Company name | | `slug` | string | URL slug (e.g. `salesforce`) | | `profileUrl` | string | Full Built In profile URL | | `websiteUrl` | string | Company's own website | | `logoUrl` | string | Company logo image URL | | `description` | string | Company mission/about text | | `city` | string | HQ city | | `state` | string | HQ state/region | | `country` | string | HQ country code | | `streetAddress` | string | Street address | | `zipCode` | string | Postal code | | `totalEmployees` | number | Employee headcount | | `industries` | array | Industry tags (Cloud, Software, FinTech, etc.) | | `techStack` | array | Technology names used by the company | | `jobsUrl` | string | Link to open jobs on Built In | ### 💰 How much does it cost to scrape Built In company profiles? This actor uses Pay-Per-Event pricing. You are charged: - **$0.005 per run** (one-time start fee) - **$0.003 per company profile** (BRONZE tier — see volume discounts below) **Cost examples:** | Companies scraped | Estimated cost | |---|---| | 20 (test run) | ~$0.07 | | 100 | ~$0.31 | | 500 | ~$1.51 | | 1,000 | ~$3.01 | | 5,000 | ~$9.01 (GOLD discount) | **Volume discounts** are applied automatically based on your Apify subscription: | Tier | Per-company price | |---|---| | FREE | $0.00345 | | BRONZE | $0.003 | | SILVER | $0.00234 | | GOLD | $0.0018 | | PLATINUM | $0.0012 | | DIAMOND | $0.00084 | ### 🚀 How to use it #### Option 1: Scrape all companies in a city 1. Open the actor on Apify 2. Set **Location** to a city slug (e.g. `austin`, `boston`, `chicago`, `new-york`, `san-francisco`, `seattle`, `los-angeles`, `denver`, `atlanta`) 3. Set **Max companies** to your desired limit 4. Click **Start** #### Option 2: Scrape specific company profiles 1. Add company profile URLs to **Company or directory URLs** (e.g. `https://builtin.com/company/stripe`) 2. Set **Max companies** to the number of profiles to scrape 3. Click **Start** #### Option 3: Scrape from a directory page 1. Add a Built In directory URL to **Company or directory URLs** (e.g. `https://builtin.com/companies/location/austin`) 2. The actor will paginate through all results automatically #### Option 4: Global company list 1. Leave **Location** and **Company or directory URLs** empty 2. Set **Max companies** to your desired limit 3. The actor will crawl the global directory ### 📥 Input parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `startUrls` | array | `[]` | Company profile or directory URLs to scrape | | `location` | string | `""` | Built In city slug (e.g. `austin`) | | `maxCompanies` | number | `100` | Max company profiles to extract | | `maxRequestRetries` | number | `3` | Retries for failed requests | **Location slugs** (examples): `albuquerque`, `atlanta`, `austin`, `baltimore`, `boston`, `charlotte`, `chicago`, `colorado`, `dallas`, `dc`, `denver`, `detroit`, `houston`, `indianapolis`, `los-angeles`, `miami`, `minneapolis`, `nashville`, `new-york`, `orlando`, `philadelphia`, `pittsburgh`, `portland`, `raleigh`, `sacramento`, `san-antonio`, `san-diego`, `san-francisco`, `seattle`, `st-louis`, `tampa`, `tucson` ### 📤 Output example ```json { "name": "Stripe", "slug": "stripe", "profileUrl": "https://builtin.com/company/stripe", "websiteUrl": "https://stripe.com", "logoUrl": "https://builtin.com/sites/www.builtin.com/files/2021-10/stripe.jpeg", "description": "Stripe is a technology company that builds economic infrastructure for the internet...", "city": "Dublin", "state": "Dublin", "country": "IE", "streetAddress": "Grand Canal Street Lower", "zipCode": null, "totalEmployees": 5360, "industries": ["Payments", "Software"], "techStack": ["React", "Ruby", "Python", "Go", "AWS", "Kafka", "PostgreSQL"], "jobsUrl": "https://builtin.com/jobs?companyId=84805&allLocations=true" } ```` ### 💡 Tips & best practices **Filter by tech stack after export**: The actor returns the full tech stack array. Use a spreadsheet or Apify's dataset filter to find companies using `React`, `Kubernetes`, `Salesforce`, etc. **Combine location + max companies**: Start with a city like `new-york` and `maxCompanies: 500` to get a rich B2B prospect list. **Enrich existing lists**: Use `startUrls` to re-scrape specific companies for regular data refresh. **Rate limiting**: The actor uses Built In's residential proxy and respects rate limits with delays between requests. Large runs (1,000+ companies) may take 30-60 minutes. **Empty fields**: Some companies don't list all data. `techStack` may be empty for non-tech companies. `streetAddress` and `zipCode` are optional. ### 🔗 Integrations **Outreach sequence automation**: Export the dataset to Google Sheets → enrich with Clay → push to HubSpot sequences for tech-stack-targeted outreach. **Talent sourcing pipeline**: Combine with [Built In Jobs Scraper](https://apify.com/automation-lab/builtin-jobs-scraper) to correlate company profiles with open roles — recruit at companies where Python + ML engineers are hiring. **Market map tracking**: Schedule weekly runs for a list of competitor URLs. Track headcount changes over time in Airtable or a data warehouse. **Sales intelligence enrichment**: Import into Salesforce or HubSpot → match against existing accounts → fill missing `techStack` and `totalEmployees` fields on existing CRM records. **CRM data refresh**: Use the Apify REST API to trigger runs on-demand when your SDR team needs fresh company data before a campaign launch. ### 🖥️ API usage #### Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' }); const run = await client.actor('automation-lab/builtin-companies-scraper').call({ location: 'austin', maxCompanies: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items[0]); // { name: 'SailPoint', city: 'Austin', techStack: ['Angular', 'AWS', ...], ... } ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient(token='YOUR_APIFY_TOKEN') run = client.actor('automation-lab/builtin-companies-scraper').call(run_input={ 'location': 'boston', 'maxCompanies': 200, }) dataset = client.dataset(run['defaultDatasetId']) for item in dataset.iterate_items(): print(item['name'], item.get('techStack', [])) ``` #### cURL ```bash curl -s -X POST \ "https://api.apify.com/v2/acts/automation-lab~builtin-companies-scraper/runs?token=YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"location": "chicago", "maxCompanies": 50}' | jq '.data.id' ``` ### 🤖 MCP (Claude / AI Assistant Integration) Use this actor directly inside Claude Code, Claude Desktop, or any MCP-compatible AI tool. **Claude Code:** ```bash claude mcp add --transport http apify "https://mcp.apify.com?tools=automation-lab/builtin-companies-scraper" ``` **Claude Desktop / Cursor / VS Code** — add to your MCP config: ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com?tools=automation-lab/builtin-companies-scraper", "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" } } } } ``` **Example prompts once connected:** - *"Scrape the top 50 tech companies in Austin and export to a spreadsheet"* - *"Find all Built In companies using Kubernetes and Terraform"* - *"Get company profiles for these 10 Built In URLs: \[list]"* - *"What's the average headcount of San Francisco tech companies on Built In?"* ### ⚖️ Legal & compliance Built In's company profiles are publicly accessible without authentication. This actor: - Accesses only public pages available to any anonymous visitor - Does not bypass login, paywalls, or any access controls - Does not collect personal data about individuals - Respects robots.txt and uses reasonable request delays - Is intended for commercial B2B data use cases (market research, sales intelligence, talent sourcing) Users are responsible for ensuring their use of scraped data complies with applicable laws (GDPR, CCPA) and their end-use terms. For personal data processing at scale, consult your legal team. ### ❓ FAQ **Q: How many companies are on Built In?** Built In lists thousands of tech companies globally. The main directory has 100+ pages of 20 companies each, and location-specific pages add depth. The Austin directory alone has 141 pages. With `maxCompanies` set high, you can collect thousands of profiles. **Q: Is the tech stack data reliable?** Companies self-report their tech stacks to attract talent. Data quality is high for companies that actively maintain their Built In profile, but some smaller or less-active companies may have empty tech stacks. **Q: Why are some companies missing location data?** Built In displays location data based on what companies have entered in their profiles. Some companies (especially those with remote-first or international structures) may not specify a primary HQ address. **Q: The run succeeded but I got fewer companies than expected. Why?** This can happen when the location has fewer companies than your `maxCompanies` limit, or when some profile pages return temporary errors. Check the actor logs for any skipped URLs. **Q: Can I scrape a specific Built In city page like /companies/location/chicago?** Yes — paste `https://builtin.com/companies/location/chicago` into the **Company or directory URLs** field, and the actor will paginate through all companies in that city directory. **Q: How often should I re-run for fresh data?** For prospect list refreshes, monthly runs are usually sufficient. For headcount tracking or competitive intelligence, weekly runs give better signal. ### 🔗 Related scrapers - [Built In Jobs Scraper](https://apify.com/automation-lab/builtin-jobs-scraper) — scrape open job listings from Built In - [LinkedIn Company Scraper](https://apify.com/automation-lab/linkedin-company-scraper) — LinkedIn company profiles - [Crunchbase Scraper](https://apify.com/automation-lab/crunchbase-scraper) — startup funding & investor data # Actor input Schema ## `startUrls` (type: `array`): List of Built In company profile URLs (e.g. https://builtin.com/company/google) or directory URLs (e.g. https://builtin.com/companies/location/austin) to scrape. Leave empty to use the Location filter or scrape all companies. ## `location` (type: `string`): Filter companies by Built In location slug (e.g. 'austin', 'new-york', 'chicago', 'san-francisco', 'boston', 'seattle', 'los-angeles', 'denver', 'atlanta'). Leave empty to scrape all locations globally. ## `maxCompanies` (type: `integer`): Maximum number of company profiles to scrape. Each company profile costs 1 result credit. Set low for testing. ## `maxRequestRetries` (type: `integer`): Number of retry attempts for failed HTTP requests. ## Actor input object example ```json { "startUrls": [], "maxCompanies": 20, "maxRequestRetries": 3 } ``` # Actor output Schema ## `overview` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [], "location": "", "maxCompanies": 20, "maxRequestRetries": 3 }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/builtin-companies-scraper").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [], "location": "", "maxCompanies": 20, "maxRequestRetries": 3, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/builtin-companies-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [], "location": "", "maxCompanies": 20, "maxRequestRetries": 3 }' | apify call automation-lab/builtin-companies-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/builtin-companies-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Built In Tech Companies Scraper", "description": "Scrape tech company profiles from Built In — name, location, industries, tech stack, headcount, and more. Filter by city or scrape all.", "version": "0.1", "x-build-id": "fqTIeqV79aOBPn4mK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~builtin-companies-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-builtin-companies-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~builtin-companies-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-builtin-companies-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~builtin-companies-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-builtin-companies-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "startUrls": { "title": "🔗 Company or directory URLs", "type": "array", "description": "List of Built In company profile URLs (e.g. https://builtin.com/company/google) or directory URLs (e.g. https://builtin.com/companies/location/austin) to scrape. Leave empty to use the Location filter or scrape all companies.", "items": { "type": "string" } }, "location": { "title": "📍 Location", "type": "string", "description": "Filter companies by Built In location slug (e.g. 'austin', 'new-york', 'chicago', 'san-francisco', 'boston', 'seattle', 'los-angeles', 'denver', 'atlanta'). Leave empty to scrape all locations globally." }, "maxCompanies": { "title": "Max companies", "minimum": 1, "type": "integer", "description": "Maximum number of company profiles to scrape. Each company profile costs 1 result credit. Set low for testing.", "default": 100 }, "maxRequestRetries": { "title": "Max request retries", "minimum": 0, "maximum": 10, "type": "integer", "description": "Number of retry attempts for failed HTTP requests.", "default": 3 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```