Built In Startup Scraper — Tech Stack, Employees, Industries & Jobs

Need to know what tech a startup runs — and whether it's hiring — without a pricey BuiltWith subscription? This Actor turns BuiltIn.com — the directory of US tech-startup ecosystems (NYC, SF, LA, Chicago, Boston, Austin, Seattle and more) — into clean, structured company profiles: tech stack, exact employee count, industries, HQ, founded year, perks and open jobs.

Look up companies by name, by URL, or a whole sector at once with a preset (SaaS, Fintech, AI/ML, eCommerce, Gaming, Crypto). Every run is live — today's Built In profile, not a stored snapshot. No login, no BuiltWith subscription — you pay only for what you pull.

• 🛠️ Full tech stack — every technology a company lists (React, Python, Docker, Snowflake, AWS…) — a BuiltWith alternative for the startup segment
• 👥 Exact employee count — the real number from Built In's structured data, not a "51–200" bucket
• 🏢 Firmographics + hiring — HQ, industries, founded year, perks and open-job count, all in one record
• ⚡ One run → one clean, flat dataset (JSON / CSV / Excel / API)

Quick start (API)

Scrape three named companies in one call:

curl -X POST "https://api.apify.com/v2/acts/foxlabs~builtin-intelligence/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{ "companyNames": ["Notion", "Datadog", "Asana"], "maxResults": 3 }'

Prefer no code? Open the Input tab, type company names or pick a sector preset, set Maximum companies as your cost cap, and click Start — then download the results.

What you get

One clean, flat record per company:

Field	Type	Description
name	string	Company name
url	string	Built In profile URL
slug	string	Built In URL slug (stable id)
description	string	Company description / pitch
tagline	string	Short pitch line (when present)
website	string	Company website
logo	string	Logo image URL
headquarters	string	HQ as City, State, Country
headquartersCity / headquartersState / headquartersCountry / headquartersPostalCode	string	Structured HQ parts
yearFounded	integer	Founding year
employees	integer	Exact employee count (from Built In structured data)
industries / industriesText	array / string	Industry tags (array + comma-joined string)
techStack / techStackText	array / string	Technologies the company lists (array + joined string)
perks	array	Benefits & culture perks
openPositions	integer	Open-job count on the profile
social	object	Public company handles: { linkedin, twitter, facebook, instagram, youtube } (only those exposed)
scrapedAt	string	ISO timestamp of the scrape

Fields a profile doesn't expose come back as null or an empty array — never a guess. A page that 404s or can't be parsed is returned as a small { url, error, scrapedAt } row rather than silently dropped.

Sample output

// Illustrative record (shape is exact; values shown for illustration)
{
  "name": "Notion",
  "url": "https://builtin.com/company/notion",
  "slug": "notion",
  "description": "Notion blends your everyday work tools into one — docs, wikis, projects and AI.",
  "tagline": "One workspace. Every team.",
  "website": "https://www.notion.so/product",
  "logo": "https://cdn.builtin.com/cms/notion-logo.png",
  "headquarters": "San Francisco, CA, US",
  "headquartersCity": "San Francisco",
  "headquartersState": "CA",
  "headquartersCountry": "US",
  "headquartersPostalCode": "94110",
  "yearFounded": 2016,
  "employees": 1000,
  "industries": ["Artificial Intelligence", "Productivity", "Software"],
  "industriesText": "Artificial Intelligence, Productivity, Software",
  "techStack": ["Go", "JavaScript", "MySQL", "Python", "Snowflake", "TypeScript"],
  "techStackText": "Go, JavaScript, MySQL, Python, Snowflake, TypeScript",
  "perks": ["Health Insurance", "Remote Work", "Equity"],
  "openPositions": 9,
  "social": { "linkedin": "https://www.linkedin.com/company/notionhq", "twitter": "https://twitter.com/NotionHQ" },
  "scrapedAt": "2026-07-05T10:00:00.000Z"
}

Download the dataset as JSON, CSV, Excel, HTML or XML.

Input & filters

• Company names or slugs — type names one per line (e.g. Notion, Datadog); each resolves to its Built In page.
• Company URLs — paste exact Built In URLs, or upload a .txt/.csv for bulk lookups (best for tricky slugs).
• Sector preset — pick a sector (SaaS, Fintech, AI/ML, eCommerce, Gaming, Crypto) to seed curated anchor companies plus Built In's live industry directory.
• Discovery (presetDepth) — 0 scrapes only the curated anchors; 1+ also harvests companies from the sector's directory pages, filtered to the sector by an industry-keyword whitelist so off-sector entries are dropped.
• Maximum companies — the hard cost cap on results (0 = unlimited).
• Concurrency and max directory pages — advanced throughput knobs.

You must provide at least one of: a preset, companyNames, or companyUrls. Presets and your own lists can be combined — they merge.

Example inputs (copy & paste)

// 1) Specific companies — just type names
{ "companyNames": ["Notion", "Datadog", "Asana"] }

// 2) A whole sector — curated anchors + Built In's live directory
{ "preset": "saas", "maxResults": 100 }

// 3) Bigger AI/ML sweep with directory discovery
{ "preset": "ai-ml", "presetDepth": 2, "maxResults": 500 }

// 4) Curated anchors only — no directory expansion (presetDepth 0)
{ "preset": "fintech", "presetDepth": 0 }

// 5) A different vertical — eCommerce / DTC companies
{ "preset": "ecommerce", "maxResults": 250 }

// 6) Exact companies by Built In URL (tricky slugs / bulk .txt upload)
{ "companyUrls": [{ "url": "https://builtin.com/company/notion" }], "maxResults": 20 }

// 7) Deep sector crawl — page more directory listings for a fuller sweep
{ "preset": "crypto-web3", "presetDepth": 3, "maxListingPages": 50, "maxResults": 1000 }

Use cases

• Tech-stack-based sales targeting. Selling a developer tool or infra product? Pull a whole sector, then filter techStack for companies already using an adjacent tool (Snowflake, Kafka, Salesforce) and prioritise outreach to a warm, qualified list.
• Talent sourcing & recruiting. Get companies plus their open-job count and the exact tech they use — so you can target the right engineers with the right pitch, and time outreach to teams that are actively hiring.
• Competitive & market intelligence. Map an entire tech sector (AI, fintech, gaming) with employee counts and founding years to size the market, spot the leaders and track who's scaling.
• CRM enrichment. Feed in a list of names or URLs and append current HQ, headcount, industries and tech stack to refresh stale records — missing values return null, never a guess.
• VC & startup sourcing. Screen a sector by founded year, size and stack to surface early-stage or fast-growing companies that fit your thesis.
• LLM / RAG context. Feed structured, per-company startup data into retrieval pipelines for grounded answers about the tech ecosystem.

Performance & throughput

The Actor is pure HTTP (CheerioCrawler — no headless browser), so it's fast and cheap: it fetches server-rendered Built In pages, parses the embedded structured data, and pushes a flat record. Throughput scales with concurrency (1–50, default 10) and is bounded only by your Apify plan. In preset + Discovery mode it pages through each sector's directory to find companies, then scrapes each profile; failed fetches retry automatically. Maximum companies is always your hard cost and time cap. Datacenter proxy is sufficient — no residential proxy needed.

Integrations

JavaScript (apify-client):

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('foxlabs/builtin-intelligence').call({
  preset: 'saas', maxResults: 100,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Python (apify-client):

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("foxlabs/builtin-intelligence").call(run_input={
    "companyNames": ["Notion", "Datadog", "Asana"],
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["name"], item.get("techStackText"))

Also works with Make / n8n / Zapier (Apify app → run this Actor, map the input), scheduled runs, webhooks, and the Apify MCP server for AI agents.

Data quality

Every field comes straight from the company's own Built In profile — the Actor reports exactly what the page exposes and never fabricates a value; missing fields are null or an empty array. Identity fields (name, URL, slug) and the structured HQ/industry data are read from the page's embedded JSON-LD, so they're clean and reliable. Tech stack, exact employee count and perks are optional on Built In — larger, well-maintained profiles list a full stack and headcount, while smaller or newer companies may list few technologies or none. Treat those fields as high-signal when present, and pair with a runtime tech-detection tool if you need stack data for every company.

Pricing

Pay per result — $4 per 1,000 companies (~$0.004 each). Cost scales linearly with maxResults, which is your hard cap:

• 100 companies ≈ $0.40
• 1,000 companies ≈ $4
• 10,000 companies ≈ $40

There's an Apify free tier to evaluate the full feature set before you scale. Datacenter proxy is sufficient, so there are no residential-proxy or third-party costs.

FAQ

Is Built In data public / can I scrape it? Built In company profile pages are publicly accessible — this Actor reads them with no login or paywall bypass. Always confirm your specific use complies with Built In's Terms of Service.

Can I use the data commercially? The pages are public, but Built In's content is not released under an open-data licence. You're responsible for how you use the output — review Built In's ToS and any applicable law before redistributing.

How fresh is the data? It's live — every run reads today's Built In profile, not a stored snapshot.

Do I need a Built In account or API key? No. No key, no login.

How accurate is the tech stack? It comes from each company's own Built In profile — accurate when listed, but the field is optional, so smaller or newer companies may list few technologies or none. For runtime tech detection across every company, pair with BuiltWith.

Will a typed name always resolve to the right company? Usually, but a shared name can land on a different Built In company (e.g. monday). Paste the exact URL in Company URLs when in doubt.

What export formats are available? JSON, CSV, Excel, HTML, XML, or via the Apify API/integrations.

How many companies can I get in one run? Up to 100,000 via maxResults; a preset with Discovery on can surface hundreds per sector.

Why are some fields empty? Coverage varies by company; missing values return null or an empty array — the Actor returns exactly what the profile exposes, never invented data.

Need revenue, valuation, funding or M&A? Use the foXLabs Owler or Craft.co company scrapers — Built In is tech-startup focused (stack, size, hiring).

Troubleshooting

• No companies to scrape error → you passed neither a preset nor companyNames/companyUrls. Pick a sector preset or add at least one company.
• A row has an error field → that page returned a non-200 status or exposed no company name (404 / redirect). The Actor logs it as a row instead of dropping it silently.
• Tech stack (or employees) is empty for a company → that profile simply doesn't list it; these fields are optional on Built In — it's the source, not a miss.
• A preset run returns fewer companies than expected → Discovery may be off (presetDepth: 0), or maxResults / max directory pages capped it. Raise presetDepth, maxResults, or max directory pages.

Notes, limits & legal (honest)

• Public pages only. The Actor reads publicly accessible Built In profile pages; it does not log in or bypass any paywall.
• Terms of Service. Built In's content belongs to Built In and is not open-licensed. You are responsible for ensuring your use of the output complies with Built In's Terms of Service and applicable law.
• Optional fields. Tech stack, exact employee count and perks are optional on Built In; when absent they're returned as null / empty — never fabricated.
• Company-level data. Records describe companies; social holds public company handles, not personal data.
• Not affiliated with Built In or Built In Inc.; this Actor reads their publicly available pages.

Support

Questions, a field you'd like added, or a custom build? Open the Issues tab on this Actor, or email info@foxlabs.com.tr. We reply fast.

If this Actor saves you time, a ⭐ review really helps.

Changelog

0.2 — 2026-07-05

• Reworked docs: API quick-start, full field table, sample output, integration snippets (JS/Python/Make/MCP), FAQ & troubleshooting. Exposed maxListingPages (max directory pages per sector) in the input form.

0.1

• Initial release. Structured tech-company profiles from BuiltIn.com — tech stack, exact employee count, industries, HQ, founded year, perks, open jobs and public social handles — by name, URL, or sector preset (SaaS, Fintech, AI/ML, eCommerce, Gaming, Crypto) with live directory discovery.

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Part of the foXLabs data platform — public-data company, contact, firmographic, technographic, jobs and AI-search intelligence scrapers. Match results across Actors by company domain for a 360° view. Browse the full suite at data.foxlabs.com.tr.