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LinkedIn Company Employees Scraper — B2B Prospect List Builder

Build B2B prospect lists from any company on LinkedIn — by company name or LinkedIn URL. No login, no cookies, no Sales Navigator seat. Two modes: Basic for fast name/headline/URL lookups, or Full for deep profile enrichment with work history, education, skills, certifications, and languages.

Works inside Claude, ChatGPT, and any MCP-compatible agent via the Apify connector — agents can call this directly without managing cookies or sessions.

What data can you extract?

Basic mode (fast, $3 per 1,000 results)

Full mode (enriched, $3 per 1,000 results)

Everything in Basic, plus:

Filter by job title and location

Zero in on the exact employees you need. Filters work in both modes and cost nothing extra — they narrow the search before results are returned.

Title filter examples:

• Software Engineer — find all SWEs at a company
• VP of Sales — isolate sales leadership
• Product Manager — map the PM org

Location filter examples:

• San Francisco — Bay Area employees only
• London — UK team
• India — offshore teams

Combine both: find every "Data Scientist" at Google in "New York".

Input

Example input

{
"queries":["https://www.linkedin.com/company/anthropic/","Stripe"],
"mode":"full",
"jobTitle":"Software Engineer",
"location":"San Francisco",
"maxResults":100
}

Example output (Full mode)

{
"fullName":"Jane Smith",
"headline":"Senior Software Engineer at Anthropic",
"url":"https://www.linkedin.com/in/janesmith/",
"publicIdentifier":"janesmith",
"location":"San Francisco, California, United States",
"about":"Building safe AI systems. Previously at Google Brain and DeepMind.",
"profilePhoto":"https://media.licdn.com/dms/image/...",
"followersCount":2450,
"experience":[
{
"position":"Senior Software Engineer",
"companyName":"Anthropic",
"startDate":{"year":2023},
"duration":"3 yrs",
"location":"San Francisco, CA"
},
{
"position":"Software Engineer",
"companyName":"Google",
"startDate":{"year":2019},
"endDate":{"year":2023},
"duration":"4 yrs"
}
],
"education":[
{
"schoolName":"Stanford University",
"degreeName":"Master of Science",
"fieldOfStudy":"Computer Science",
"startDate":{"year":2017},
"endDate":{"year":2019}
}
],
"skills":["Python","Machine Learning","PyTorch","Distributed Systems"],
"certifications":[],
"languages":["English","Mandarin"],
"sourceCompany":"anthropic"
}

Use cases

ABM and account-based sales

Map every decision-maker at your target accounts. Feed 200 company names, filter by "VP" or "Director" or "Head of", and get a ready-to-sequence prospect list in minutes. No ZoomInfo contract, no Sales Navigator seat.

Recruiting and talent sourcing

Find every engineer, designer, or PM at a competitor. Use the title filter to isolate "Staff Engineer" or "Principal Designer", then enrich with Full mode for education and tenure. Build targeted sourcing pipelines without LinkedIn Recruiter.

Competitive team intelligence

Track how competitors staff their teams. Run monthly to detect headcount growth, new hires in key functions, and org structure changes. Compare engineering-to-sales ratios across your competitive set.

Market research and investor due diligence

Profile portfolio companies' leadership teams. Track C-suite changes, average tenure, educational backgrounds. Cross-reference with job posting data to identify hiring surges or contractions.

CRM enrichment

Bulk-refresh contact records at named accounts. Detect who left (profiles no longer show the company), who joined (new matches), and who got promoted (title changes). Schedule weekly runs to keep your CRM current.

Compared to alternatives

vs. ZoomInfo / Apollo / Cognism / Lusha ($5K–$50K/year) Same "every employee at this account" data, live from public LinkedIn, at $3/1K results with Full enrichment. No annual contract, no seat license, no minimums. Raw JSON you own.

vs. LinkedIn Sales Navigator (~$99/seat/month) Sales Navigator caps daily searches and profile views, ties lists to a personal account, and charges per seat. This actor needs no LinkedIn account at all and returns structured JSON at API scale.

vs. HarvestAPI LinkedIn Company Employees ($1.50–$12/1K) We match their Full mode data depth (work history, education, skills, certifications, languages) at $3/1K — cheaper than their $8/1K Full tier. Basic mode at $3/1K includes headline parsing. No login or cookies required by either.

Limitations

• Returns profiles that appear in public search results — not an exhaustive org chart. LinkedIn caps public visibility.
• Full mode adds ~3-5 seconds per profile for enrichment. A 100-employee Full mode run takes ~5-8 minutes.
• Very common company names (e.g., "Apple") may include false positives. Use the LinkedIn company URL for maximum precision.
• Title and location filters use Google search operators — they're good but not exact-match. Occasional false positives.

Tips for best results

1. Use LinkedIn company URLs for precision — https://www.linkedin.com/company/stripe/ beats "Stripe".
2. Combine title + location filters to narrow results before they're returned (saves credits).
3. Start with Basic mode to validate your query returns the right people, then switch to Full for enrichment.
4. Batch companies in one run — the actor handles multiple companies efficiently with rate limiting between each.

Pairs well with LinkedIn Profile Scraper (for ad-hoc profile lookups) and Career Sites Scraper (cross-reference open roles at target companies).

Last verified: 2026-05

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