{ "openapi": "3.0.1", "info": { "title": "Bulk LinkedIn Profile Enrichment | No Cookies | from $2.996/1k", "description": "Bulk LinkedIn profile enrichment: give profile URLs or paste a CSV, get one fresh row per person: name, headline, title, company, seniority, location. No login or cookies. Pay per profile found. Does not search by name or company; use linkedin-people-search. Free plan: 100 per run.", "version": "0.1", "x-build-id": "Hn2yAKpKULKN5TuXA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/b2bdata~bulk-linkedin-profile-enrichment/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-b2bdata-bulk-linkedin-profile-enrichment", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/b2bdata~bulk-linkedin-profile-enrichment/runs": { "post": { "operationId": "runs-sync-b2bdata-bulk-linkedin-profile-enrichment", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/b2bdata~bulk-linkedin-profile-enrichment/run-sync": { "post": { "operationId": "run-sync-b2bdata-bulk-linkedin-profile-enrichment", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "items": { "title": "LinkedIn profile URLs (one per line)", "type": "array", "description": "Step 1. Accepted forms: https://www.linkedin.com/in/slug, linkedin.com/in/slug, or just the slug. Example: https://www.linkedin.com/in/satyanadella. Duplicates are collapsed and results keep input order. Leave empty if you paste a CSV below.", "items": { "type": "string" } }, "csvText": { "title": "Or paste a CSV (profile links in any column)", "type": "string", "description": "Step 1, alternative. Paste CSV text. Every LinkedIn profile link in any column is used; other columns are ignored. Links here are added after the list above. Omit if you use the list." }, "limit": { "title": "Max profiles to look up", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Step 2. How many profiles from your list to look up. 0 means all of them, up to 10,000 per run. A value above 10,000 is rejected. Omit for 100.", "default": 100 }, "depth": { "title": "Depth: compact (fast) or deep (most data)", "enum": [ "compact", "deep" ], "type": "string", "description": "Step 2b, optional. compact (default) = fast bulk route, 25 profiles per upstream call, about 1,500 profiles/min (estimate from upstream rate limits, unverified). deep = one upstream call per profile, about 60 profiles/min (estimate, unverified), and the richest rows: more sections such as education and related profiles. Same price per profile in both. Use compact for big CRM refreshes, deep for smaller lists where you want everything. Independent of `include`: include picks the field groups, depth picks the route; deep with include [\"all\"] returns the most. A profile that does not exist is a free miss in both modes.", "default": "compact" }, "include": { "title": "Richer data groups (optional)", "type": "array", "description": "Step 3, optional. Pick the extra groups to add to each row; the price per profile does not change. Format: a list of group names, for example [\"career\",\"details\"]. career = experience[] (work history), volunteerExperience[], education[], skills[]. details = about, industry, followersCount, profileImageUrl, backgroundImageUrl (image links expire, download them soon). credentials = certifications[], languages, honors, projects, courses, testScores, publications, patents. social = recommendations[], interests, articles[], groups[]. location = city, state, stateFullName, countryFullName, countryIso3. links = linkedinUrl, githubUrl, twitterUrl, facebookUrl, websiteUrl (URLs only) and hasPhone (true/false; no phone numbers, no email addresses are ever returned). currentJob = the current role as flat fields: currentCompanyLinkedinId, currentCompanyLogoUrl (expiring link), currentJobStartDate, currentJobDescription, currentJobLocation, currentEmploymentType, currentJobFunction, currentSeniority, jobTitleNormalized. analytics = seniorityLevel, isDecisionMaker, averageTenureYears, and counts (skillsCount, educationCount, experienceCount, certificationsCount, languagesCount, companiesCount) plus highestDegree. network = relatedProfiles (up to 10), similarNames (up to 10), activities. quality = dataQualityPublicExperienceAvailable, sectionsIncluded. career also adds organizations. companyDetails = fields about the person's CURRENT employer, one company lookup per distinct employer per run, prefixed company: companyName, companyWebsite, companyIndustry, companyType, companyDescription, companyTagline, companySpecialities, companyEmployeeRange, companyEmployeesOnLinkedin, companyFollowers, companyFoundedYear, companyHq* (line, city, state, country, postal code), companyLocationsCount, companyLogoUrl (expiring link), companyLinkedinUrl, companyCrunchbaseUrl, companyTotalFundingUsd, companyFundingRounds, companyInvestors, companyStockSymbol, companyIpoStatus, companyFundingData, companyAcquisitions. A company that cannot be found is skipped, the profile row is still delivered and charged. For the most data per row combine include [\"all\"] with depth deep. all = every group at once (use [\\\"all\\\"]). Only fields the profile actually has are added; empty ones are left out. Omit or leave empty for the default compact row (name, headline, title, company, location, tenure): it is the fastest and smallest. Any other value fails the run and nothing is charged.", "items": { "type": "string", "enum": [ "career", "details", "credentials", "social", "location", "links", "currentJob", "analytics", "network", "quality", "companyDetails", "all" ], "enumTitles": [ "Career: experience, education, skills", "Details: about, industry, followers, images", "Credentials: certifications, languages, honors, projects, patents ...", "Social: recommendations, interests, articles, groups", "Location: city, state, country names, ISO3", "Links: LinkedIn, GitHub, Twitter, Facebook, website URLs, hasPhone", "Current job: normalized title, start date, description, location, function, seniority", "Analytics: seniority level, decision maker, tenure average, counts, highest degree", "Network: related profiles, similar names, activities", "Quality: data-quality flag, sections returned", "Company details: current employer name, industry, size, HQ, funding, website", "All: every group above" ] }, "default": [] }, "includeAudit": { "title": "Include audit fields", "type": "boolean", "description": "Adds an audit object to each row: requestId, batchUnitsCharged, latencyMs, inputRaw, inputCanonical. Omit for a clean row.", "default": false }, "maxChargeUsd": { "title": "Spend cap for this run (USD)", "minimum": 0, "type": "number", "description": "Stops the run once this much has been charged. Omit for no cap." }, "sourceTag": { "title": "Source tag", "type": "string", "description": "Free text echoed in every row and in the run summary, to tag where a run came from." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 }, "PROXY_UNBLOCKER_UNITS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 }, "PROXY_UNBLOCKER_UNITS": { "type": "integer", "example": 0 } } } } } } } } } }