🏢 Linkedin Company Details Scraper Fast

Get complete LinkedIn company profiles in bulk — from LinkedIn URLs or simply from company names. Website, industry, company size, employee and follower counts, headquarters and every office address, founded year, specialties, logo, similar companies and the latest posts. No cookies, no LinkedIn account, no risk.

• ⚡ Blazing fast — around 100 companies in ~20 seconds, using only 256 MB of memory.
• 📧 Contacts enrichment add-on — emails, phone numbers and social media profiles (Facebook, Instagram, X, YouTube, TikTok…) from each company's website.
• 🔎 Boolean text search — keep only the companies whose profile matches (fintech OR payments) AND NOT crypto.
• 🔍 Search by name — don't have the URLs? Type the company names and we find their LinkedIn pages for you.
• 🔒 No cookies or login — your LinkedIn account is never used or put at risk.
• 🧠 Smart matching — works with any LinkedIn URL format, country subdomains, /about or /jobs pages, company IDs, and even old company handles that were renamed.
• 🆕 Always fresh — data is collected live from LinkedIn at run time, never from a stale cache.
• 💰 Affordable — $0.40 per 1,000 companies, and you pay only for results: companies that can't be found are never charged.
• 📤 Export to Excel, CSV, JSON, HTML or XML, or connect it to Google Sheets, HubSpot, Zapier, Make, n8n and your own app via API.

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🤔 What can I use it for?

• 🧲 Lead generation & enrichment — enrich your CRM or prospect lists with website, industry, size and location of each company.
• 🎯 Account-based marketing — qualify target accounts by employee count, followers, industry and headquarters.
• 🕵️ Competitor intelligence — track competitors' growth (employees, followers), offices and what they post.
• 📈 Market research — map entire industries and discover similar companies automatically.
• 💼 Recruiting & sales intelligence — find company size, locations and open-jobs links before reaching out.
• 🤖 AI agents & data pipelines — feed clean, structured company data to your AI workflows.

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📦 What data do you get?

	Data
🏢	Company name, LinkedIn ID, handle and URL, page type (company / showcase / school)
📝	Tagline and full description ("About")
🌐	Website
🏭	Industry, company type (Public, Privately Held…), specialties
👥	Company size range, number of employees on LinkedIn, number of followers
📅	Founded year
📍	Headquarters and all office locations split into street, city, region, postal code and country
🖼️	Logo and cover image
🔗	Similar companies (name, industry, location, LinkedIn URL) and affiliated / showcase pages
📰	Latest posts (text, date, likes, link)
💼	Link to the company's open jobs on LinkedIn
📧	Add-on: emails, phone numbers and Facebook, Instagram, LinkedIn, X, YouTube, TikTok, Pinterest and Discord profiles from the company website

Example result

{
  "id": "2135371",
  "universalName": "stripe",
  "linkedinUrl": "https://www.linkedin.com/company/stripe",
  "pageType": "COMPANY",
  "name": "Stripe",
  "tagline": "Help increase the GDP of the internet.",
  "description": "Stripe builds programmable financial services. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to…",
  "website": "https://stripe.com",
  "logo": "https://media.licdn.com/dms/image/v2/D560BAQE2ZfJyfn-VCg/company-logo_200_200/…",
  "industry": "Technology, Information and Internet",
  "companyType": "Privately Held",
  "companySize": "5,001-10,000 employees",
  "employeeCountRange": { "start": 5001, "end": 10000 },
  "employeeCount": 16622,
  "followerCount": 1753590,
  "foundedOn": { "year": 2010 },
  "headquarter": "South San Francisco, California",
  "locations": [
    {
      "line1": "354 Oyster Point Blvd",
      "city": "South San Francisco",
      "geographicArea": "California",
      "postalCode": "94080",
      "country": "US",
      "headquarter": true,
      "text": "354 Oyster Point Blvd, South San Francisco, California 94080, US"
    },
    {
      "line1": "1 Wilton Park, Wilton Terrace",
      "city": "Dublin",
      "geographicArea": "County Dublin",
      "postalCode": "D02 FX04",
      "country": "IE",
      "headquarter": false,
      "text": "1 Wilton Park, Wilton Terrace, Dublin, County Dublin D02 FX04, IE"
    }
  ],
  "jobSearchUrl": "https://www.linkedin.com/jobs/search?f_C=2135371",
  "similarOrganizations": [
    { "name": "Airbnb", "universalName": "airbnb", "linkedinUrl": "https://www.linkedin.com/company/airbnb", "industry": "Software Development", "location": "San Francisco, CA" }
  ],
  "affiliatedPages": [
    { "name": "Stripe Support", "universalName": "stripe-support", "linkedinUrl": "https://www.linkedin.com/showcase/stripe-support/", "industry": "Technology, Information and Internet" }
  ],
  "recentPosts": [
    { "url": "https://www.linkedin.com/posts/stripe_introducing-personal-agent-protocol-activity-7513299438086332416-zrLF", "text": "We're working with Meta, Sierra, Genesys, Instinct, Rocket, …", "publishedAt": "2026-10-06T18:09:36.392Z", "likes": 291 }
  ],
  "originalQuery": { "url": "https://www.linkedin.com/company/stripe" }
}

Contacts enrichment add-on

Turn on 📧 Company contacts enrichment and each company's website is visited to collect contact details, added to the same row:

{
  "name": "Bancolombia",
  "website": "http://www.bancolombia.com",
  "emails": ["notificacijudicial@bancolombia.com.co"],
  "phones": ["601343 0000", "604510 9000"],
  "facebooks": ["https://www.facebook.com/bancolombia"],
  "instagrams": ["https://instagram.com/bancolombia"],
  "twitters": ["https://twitter.com/Bancolombia"],
  "linkedIns": ["https://www.linkedin.com/company/22690"],
  "youtubes": [], "tiktoks": [], "pinterests": [], "discords": []
}

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💰 How much does it cost?

Simple pay-per-result pricing — no subscription, no monthly fee:

	Price
🏢 Company profile	$0.40 per 1,000 companies ($0.0004 each)
📧 Contacts enrichment add-on (optional)	+$0.40 per 1,000 companies — charged only when contacts are found

Examples: 1,000 company profiles cost $0.40; with contacts enrichment, at most $0.80. Companies that can't be found are never charged, and the run stops automatically at your spending limit.

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🚀 How to use it

1. Click Try for free.
2. Paste LinkedIn company URLs — and/or type company names in the search field.
3. Click Start.
4. Download your data as Excel, CSV or JSON, or use it via API.

No setup, no cookies, no LinkedIn account.

🔎 Boolean text search

Fill Text search (boolean) to keep only the companies whose name, tagline, description, industry or specialties match. Companies that don't match are not charged (nor enriched with contacts).

Syntax	Meaning	Example
AND, &&, +term, or a space	both	software AND cloud, software cloud
OR, ||	either	logistics OR "last mile"
NOT, !term, -term	exclude	marketing -agency
"…"	exact phrase	"machine learning"
( )	grouping	(AI OR IA) AND (bank* OR fintech)
*	wildcard	consult* matches consulting, consultancy

Matching works on whole words and ignores case and accents: AI doesn't match "said", and logistica matches "Logística".

Accepted inputs

• Company pages: https://www.linkedin.com/company/google
• Country subdomains and sub-pages: https://co.linkedin.com/company/bancolombia/about/
• Company handles: netflix
• Company IDs: https://www.linkedin.com/company/9997324
• Showcase and school pages: https://www.linkedin.com/showcase/rappi-ads/
• Company names: Anthropic, Mercado Libre

Example input:

{
  "companies": [
    "https://www.linkedin.com/company/google",
    "https://www.linkedin.com/company/microsoft"
  ],
  "searches": ["Anthropic", "Mercado Libre"],
  "scrapeContacts": true
}

Already using another LinkedIn company scraper? Your companies / searches input works as-is.

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❓ FAQ

Do I need a LinkedIn account or cookies?

No. Linkedin Company Details Scraper Fast only reads public company information. Your LinkedIn account is never involved, so it can't be restricted.

How fast is it?

About 100 companies in ~20 seconds, depending on LinkedIn's load. With the contacts enrichment add-on, about 100 companies in 1.5 minutes (every company website is visited). Thousands of companies take just a few minutes.

How does the search by company name work?

For each name we find the best-matching LinkedIn company page (an exact name match is preferred) and return its full profile. For maximum precision with common names, use the LinkedIn URL.

What happens if a company can't be found?

It is skipped, reported in the run log and not charged. Renamed company handles are detected automatically.

How does the contacts enrichment work?

When the add-on is on, we visit each company's website (homepage plus its contact/about page when needed) and extract emails, phone numbers and social media profile links. It is charged only for companies where at least one contact is found.

Is the data up to date?

Yes. Every run collects the data live from LinkedIn — nothing is served from a cache.

Can I integrate it with my tools?

Yes. Use Apify integrations for Google Sheets, HubSpot, Zapier, Make, n8n, Slack and more, webhooks, or the Apify API with ready-to-use clients for JavaScript and Python (see the API tab).

Can I schedule it?

Yes. Use Apify Schedules to refresh your company data daily, weekly or monthly.

Is it legal to scrape LinkedIn company data?

This actor only extracts publicly available company information. Always use the data in line with applicable laws and regulations, and consult a lawyer if you are unsure.

I have a question or a feature request

Open an issue in the Issues tab — we reply quickly and love adding features our users need.

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Disclaimer: This actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. LinkedIn® is a registered trademark of LinkedIn Corporation.