LinkedIn Company Employees Scraper (No Cookies, Verified B2B Leads)

Extract verified employee rosters and decision-makers from target LinkedIn companies without login credentials, session cookies, or account ban risks.

Filter by company, exact job title, seniority level (C-Level, VP, Director, Manager, Senior), and geographic location. Automatically filters out former staff and alumni with transparent verification scoring.

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⚡ Why Use This Scraper?

Feature	This Scraper	Cookie-Based Scrapers	Apollo / PhantomBuster
Account Ban Risk	ZERO (100% No Login / No Cookies)	🚨 High (LinkedIn checkpoints & bans)	High (requires connected cookies)
Ex-Employee Filtering	Built-in Verification Engine (discards ex-staff)	❌ Included (pollutes your CRM)	Outdated databases (30%+ alumni)
Title Sanitization	CRM-Ready Clean Roles (strips AG, GmbH, noise)	❌ Raw messy headlines	Varies by provider
Pricing Model	Pay-Per-Result (~$0.006 / lead)	Expensive monthly fee + proxy costs	$49 – $149 / month subscription
Discarded / Ex-Employees	100% FREE ($0.00 charge)	Charged full credits	Consumes export credits
Speed & Concurrency	Lightning fast (Public index routing)	Slow browser delays (10s/profile)	Rate-limited by account safety caps

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🚀 Key Capabilities

• 100% Cookie-Free & Zero Account Risk: Never supply your li_at session cookie or risk your personal or team LinkedIn accounts.
• Built-In Current Employment Verification: Evaluates each profile's headline, title, and search snippet to distinguish active team members from ex-employees and alumni.
• Transparent Confidence Scoring: Every lead is tagged with a transparent verification level (HIGH, MEDIUM, LOW) and a human-readable reason (confidenceReason).
• Precision Job Title Cleaning: Strips corporate prefixes, legal suffixes (AG, GmbH, Inc, LLC, Ltd, SE), and Google truncation artifacts (..., Read more). Recovers real roles from snippets even when headlines only list the company name.
• Seniority & Role Targeting: Filter decision-makers by exact title (e.g. VP of Sales, Chief Technology Officer) or expand automatically across seniority levels (c_level, vp, director, manager, senior).
• International Location Matching: Supports cities, metropolitan areas, states, and Unicode regional spellings (Raaba, Steiermark, Österreich, München, Zürich, San Francisco).

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📖 How to Extract Verified Leads in 3 Steps

1. Add Target Companies: Enter company names (e.g. Stripe), slugs (anthropic), or LinkedIn URLs (https://www.linkedin.com/company/cancom-austria/).
2. Set Filters (Optional): Filter by seniority level, target job titles (e.g. Sales Leader, Engineer), and geographic location.
3. Run & Export: Click Start. Download clean, CRM-ready leads in CSV, Excel, or JSON, or stream directly into HubSpot, Salesforce, Clay, or n8n via webhook.

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📥 Input Configuration Reference

Option	Type	Default	Description
companies	Array	Required	Target companies. Accepts names (OpenAI), slugs (anthropic), or full URLs (linkedin.com/company/stripe/).
maxEmployeesPerCompany	Integer	50	Maximum number of verified employees to return per company.
jobTitles	Array	[]	Specific job titles to match (e.g. ["CEO", "Software Engineer", "VP Sales"]).
seniority	Array	[]	Seniority levels: c_level, founder_owner, vp, director, manager, senior, entry_intern.
location	String	""	Geographic filter (e.g. "San Francisco", "London", "Austria").
verifyCurrentOnly	Boolean	true	When enabled, automatically discards former employees and alumni.
maxResults	Integer	250	Maximum total profiles across all companies in a single run.
proxyConfiguration	Object	Residential	High-reputation residential proxy rotation configured out of the box.

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📊 Sample Output

Every verified employee record is returned with clean, structured CRM fields:

{
  "fullName": "Bernd Eder",
  "firstName": "Bernd",
  "lastName": "Eder",
  "currentTitle": "Executive Board Member",
  "headline": "Executive Board Member CANCOM Austria AG",
  "company": "Cancom Austria",
  "companySlug": "cancom-austria",
  "companyLinkedinUrl": "https://www.linkedin.com/company/cancom-austria/",
  "profileUrl": "https://www.linkedin.com/in/berndeder/",
  "publicIdentifier": "berndeder",
  "location": "Raaba",
  "isCurrentEmployee": true,
  "confidence": "HIGH",
  "confidenceReason": "Headline confirms active employment at Cancom Austria",
  "matchedTitleFilter": "Executive Board Member",
  "scrapedAt": "2026-09-07T00:00:00.000Z"
}

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🎯 Verification & Confidence Explained

Tier	Meaning	Action Taken
HIGH	Headline explicitly indicates current role at target company (e.g., VP Engineering at Stripe, Executive Board Member).	Included in dataset.
MEDIUM	Active employment confirmed via search snippet context or verified company association.	Included in dataset.
LOW	Former employee indicators detected (Ex-Stripe, Former Google, Alumni) or ambiguous context.	Automatically discarded when verifyCurrentOnly is true.

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💰 Transparent Pay-Per-Event (PPE) Pricing

You only pay for successful, verified employee leads. There are no recurring monthly software subscriptions:

Event	Rate	When Charged
verified-lead (Default dataset item)	$0.006 / lead	Charged only when a verified current employee is delivered.
Ex-Employees / Alumni	$0.00 (FREE)	Automatically discarded. Zero charge.
Unmatched / Blocked	$0.00 (FREE)	Zero charge.

Pricing Examples:

• 100 Verified Decision-Makers: 100 × $0.006 = $0.60
• 500 Enterprise Leads across 10 Companies: 500 × $0.006 = $3.00

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💻 Developer API & Integrations

Python (apify-client)

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run = client.actor("t0b0t/linkedin-company-employees-scraper").call(
    run_input={
        "companies": ["https://www.linkedin.com/company/anthropic/", "Stripe"],
        "jobTitles": ["Software Engineer", "Engineering Manager"],
        "seniority": ["senior", "manager"],
        "location": "San Francisco",
        "maxEmployeesPerCompany": 50,
        "verifyCurrentOnly": True,
    }
)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['fullName']} - {item['currentTitle']} ({item['confidence']})")

JavaScript / Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('t0b0t/linkedin-company-employees-scraper').call({
    companies: ['Anthropic', 'OpenAI'],
    seniority: ['c_level', 'vp', 'director'],
    maxEmployeesPerCompany: 25,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Extracted ${items.length} verified decision-makers!`);

cURL

curl -X POST "https://api.apify.com/v2/acts/t0b0t~linkedin-company-employees-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "companies": ["Stripe"],
    "seniority": ["c_level", "director"],
    "maxEmployeesPerCompany": 25
  }'

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❓ Frequently Asked Questions (FAQ)

Do I need to provide LinkedIn cookies or credentials?

No. This scraper operates 100% without login credentials or li_at session cookies. Your LinkedIn account is never exposed to rate limits, security checkpoints, or suspensions.

How does ex-employee filtering work?

The scraper's multi-tier verification engine analyzes profile headlines and search snippet context. If negative signals (such as ex-, former, alumni, past:, or dates ending in the past) are detected, the lead is classified as LOW confidence and automatically discarded.

How are job titles cleaned?

Raw LinkedIn search headlines often contain company names and corporate suffixes (e.g. Vertriebsassistentin CANCOM Austria AG). Our sanitization engine strips legal entities (AG, GmbH, Inc, LLC), company names, and Google truncation symbols (... Read more) so your CRM receives clean, ready-to-use job titles.

Can I filter by both seniority and department?

Yes. You can combine seniority (e.g. ["director", "vp"]) with specific keywords in jobTitles (e.g. ["Marketing", "Sales", "Engineering"]) to pinpoint the exact leadership roster of target accounts.

Is scraping public LinkedIn employee data legal?

Yes. The scraper indexes publicly available information without bypassing authentication or paywalls, in accordance with US Ninth Circuit legal precedents (hiQ Labs v. LinkedIn).

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💬 Support & Feature Requests

Have questions, need custom features, or want to report an issue? Check the Issues tab on the Actor page or reach out via Apify Console. We respond quickly!