API reference · LinkedIn

linkedin/bulk/company-employees

Integrate this model through SandBase's unified API, with production-ready schemas and examples.

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OpenAI-compatible endpoint with unified authentication and usage tracking.

POSThttps://api.sandbase.ai/v1/run

Model IDlinkedin/bulk/company-employees

Input Schema

26 parameters · 0 required · 26 optional

Parameter	Type	Required	Description
`maxItems`	integer	Optional	Maximum number of profiles to scrape. The actor will stop scraping when this limit is reached. · Min: -9007199254740991 · Max: 9007199254740991
`companies`	array	Optional	Search employees of these companies. Provide full LinkedIn URLs. Example: `https://www.linkedin.com/company/google`
`jobTitles`	array	Optional	Filter Profiles by these LinkedIn job titles. Example: `Software Engineer`.
`locations`	array	Optional	Filter employees by these LinkedIn locations. Example: `San Francisco`. LinkedIn does not always understand your text queries. For example for "UK" query it will apply "Ukraine" location, so you should use "United Kingdom" in this case. Try this out first in the location filter input of LinkedIn search at `https://www.linkedin.com/search/results/people/?geoUrn=%5B%22103644278%22%5D` - we will use the first suggestion from the autocomplete popup when you type your location
`startPage`	integer	Optional	The page number to start scraping from. Starts from 1. · Min: 0 · Max: 100
`takePages`	integer	Optional	The number of search pages to scrape. Each page contains 25 profiles. · Min: 0 · Max: 100
`functionIds`	string[]	Optional	Filter Profiles by these LinkedIn function IDs. Example: `8` for 'Engineering'. Full list: { "1": "Accounting", "2": "Administrative", "3": "Arts and Design", "4": "Business Development", "5": "Community and Social Services", "6": "Consulting", "7": "Education", "8": "Engineering", "9": "Entrepreneurship", "10": "Finance", "11": "Healthcare Services", "12": "Human Resources", "13": "Information Technology", "14": "Legal", "15": "Marketing", "16": "Media and Communication", "17": "Military and Protective Services", "18": "Operations", "19": "Product Management", "20": "Program and Project Management", "21": "Purchasing", "22": "Quality Assurance", "23": "Real Estate", "24": "Research", "25": "Sales", "26": "Customer Success and Support" }
`industryIds`	array	Optional	Filter Profiles by these LinkedIn industry IDs. Example: `4` for 'Software Development'. Full list: `https://github.com/HarvestAPI/linkedin-industry-codes-v2/blob/main/linkedin_industry_code_v2_all_eng_with_header.csv`
`searchQuery`	string	Optional	Query to search LinkedIn profiles. · Max length: 300
`pastJobTitles`	array	Optional	Filter Profiles by these LinkedIn past job titles. Example: `Software Engineer`.
`excludeSchools`	array	Optional	Exclude Profiles by these LinkedIn schools. Example: `Stanford University`.
`companyBatchMode`	string	Optional	Choose how to process the companies. 'All at once' will search employees from all companies in one query, while 'One by one' will process each make a query for each company separately. The start fee will apply for each query. · Options: all_at_once, one_by_one · Default: "all_at_once" all_at_onceone_by_one
`companyHeadcount`	string[]	Optional	Filter Profiles by their current company's headcount.
`excludeLocations`	array	Optional	Exclude Profiles by these LinkedIn locations. Example: `San Francisco`. LinkedIn does not always understand your text queries. For example for "UK" query it will apply "Ukraine" location, so you should use "United Kingdom" in this case. Try this out first in the location filter input of LinkedIn search at `https://www.linkedin.com/search/results/people/?geoUrn=%5B%22103644278%22%5D` - we will use the first suggestion from the autocomplete popup when you type your location
`seniorityLevelIds`	string[]	Optional	Filter Profiles by these LinkedIn seniority level IDs. Example: `120` for 'Senior'. Full list: { "100": "In Training", "110": "Entry Level", "120": "Senior", "130": "Strategic", "200": "Entry Level Manager", "210": "Experienced Manager", "220": "Director", "300": "Vice President", "310": "CXO", "320": "Owner / Partner" }
`excludeFunctionIds`	string[]	Optional	Filter Profiles by these LinkedIn function IDs. Example: `8` for 'Engineering'.
`excludeIndustryIds`	array	Optional	Exclude Profiles by these LinkedIn industry IDs. Example: `4` for 'Software Development'. Full list: `https://github.com/HarvestAPI/linkedin-industry-codes-v2/blob/main/linkedin_industry_code_v2_all_eng_with_header.csv`
`maxItemsPerCompany`	integer	Optional	Maximum number of profiles to scrape. The actor will stop scraping when this limit is reached. · Min: -9007199254740991 · Max: 9007199254740991
`profileScraperMode`	string	Optional	Choose the mode for scraping LinkedIn profiles. The Short mode provides basic information, while the Full mode includes full detailed profile data. · Options: Short ($4 per 1k), Full ($8 per 1k), Full + email search ($12 per 1k) · Default: "Full ($8 per 1k)" Short ($4 per 1k)Full ($8 per 1k)Full + email search ($12 per 1k)
`recentlyChangedJobs`	boolean	Optional	If enabled, only Profiles of people who have recently changed jobs will be returned.
`excludePastCompanies`	array	Optional	Exclude Profiles by these LinkedIn past companies. Provide full LinkedIn URLs
`excludePastJobTitles`	array	Optional	Exclude Profiles by these LinkedIn past job titles. Example: `Software Engineer`.
`yearsOfExperienceIds`	string[]	Optional	Filter Profiles by these LinkedIn years of experience IDs. Example: `3` for '3 to 5 years'. Full list: { "1": "Less than 1 year", "2": "1 to 2 years", "3": "3 to 5 years", "4": "6 to 10 years", "5": "More than 10 years" }
`excludeCurrentJobTitles`	array	Optional	Exclude Profiles by these LinkedIn current job titles. Example: `Software Engineer`.
`excludeSeniorityLevelIds`	string[]	Optional	Filter Profiles by these LinkedIn seniority level IDs. Example: `120` for 'Senior'.
`yearsAtCurrentCompanyIds`	string[]	Optional	Filter Profiles by these LinkedIn years at current company IDs. Example: `3` for '3 to 5 years'. Full list: { "1": "Less than 1 year", "2": "1 to 2 years", "3": "3 to 5 years", "4": "6 to 10 years", "5": "More than 10 years" }

Output Schema

Field	Type	Description
`id`	string	Unique identifier for the generation task
`status`	string	Task status: pending, running, completed, failed, timeout
`model`	string	Model used for the generation
`outputs`	array	Array of output items
`outputs[].url`	string	URL of the generated artifact
`outputs[].content_type`	string	MIME type (e.g. image/png, video/mp4)
`error`	object \| null	Error details if failed, null on success
`error.type`	string	Machine-readable error type code
`error.message`	string	Human-readable error description

Async Workflow

This model uses asynchronous execution. Submit a request and poll for the result.

Submit — POST to /v1/run, receive an id
Poll — GET /v1/run/{id} until status is completed, failed, or timeout
Retrieve — Read outputs from the completed response

Code Examples

Ready-to-run snippets

# Step 1: Submit
curl -X POST https://api.sandbase.ai/v1/run \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
  "model": "linkedin/bulk/company-employees",
  "companyBatchMode": "all_at_once",
  "profileScraperMode": "Full ($8 per 1k)",
  "prompt": "a beautiful sunset over mountains"
}'

# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
  -H "Authorization: Bearer YOUR_API_KEY"

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