---
updatedAt: 2026-04-24T07:17:22.000Z
agentTools:
projectIndex: https://apidocs.pearch.ai/llms.txt
---
# Search people profiles (asynchronous)
Submit a search query to be processed asynchronously in the background. This endpoint returns immediately with a task ID and thread ID that can be used to check the status, retrieve results when ready, and paginate through search results.
This is useful for long-running searches that may take several minutes to complete. The search will continue processing in the background while you can use the task ID to monitor progress and retrieve results. The thread ID can be used only to paginate the existing result set through `/v2/search` or `/v2/search/submit`.
Initial searches support the same parameters as synchronous `/v2/search`. For pagination with `thread_id`, send only `limit` and optionally `offset`; search or filter parameters return HTTP 400.
**Cost: (number of profiles returned) × (credits for `type` + `insights` + `high_freshness` + `reveal_emails` + `reveal_phones`).**
**Rate limit: 60 actual search requests per user per 60 seconds.** `/v2/search`, `/v2/search/submit`, and `/v2/search/count` share this limit. Fully cached thread reloads that do not run a new search use a separate higher limit of 120 cached requests per user per 60 seconds. When the rate limit is exceeded, the API returns HTTP 429 with details about the triggered window, current value, and limit.
_Check out official [Python client](https://github.com/Pearch-ai/pearch-client)_
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# OpenAPI definition
```json
{
"openapi": "3.0.4",
"info": {
"title": "Pearch.AI API",
"description": "Pearch.AI API. You need to pass API key as 'Authorization: Bearer ' header.",
"version": "2.0"
},
"x-readme": {
"explorer-enabled": true,
"samples-languages": [
"shell"
],
"proxy-enabled": false
},
"servers": [
{
"url": "https://api.pearch.ai/",
"description": "Main server"
}
],
"paths": {
"/v2/search/submit": {
"post": {
"operationId": "post_v2-search-submit",
"summary": "Search people profiles (asynchronous)",
"tags": [
"Search"
],
"description": "Submit a search query to be processed asynchronously in the background. This endpoint returns immediately with a task ID and thread ID that can be used to check the status, retrieve results when ready, and paginate through search results.\n\nThis is useful for long-running searches that may take several minutes to complete. The search will continue processing in the background while you can use the task ID to monitor progress and retrieve results. The thread ID can be used only to paginate the existing result set through `/v2/search` or `/v2/search/submit`.\n\nInitial searches support the same parameters as synchronous `/v2/search`. For pagination with `thread_id`, send only `limit` and optionally `offset`; search or filter parameters return HTTP 400.\n\n**Cost: (number of profiles returned) × (credits for `type` + `insights` + `high_freshness` + `reveal_emails` + `reveal_phones`).**\n\n**Rate limit: 60 actual search requests per user per 60 seconds.** `/v2/search`, `/v2/search/submit`, and `/v2/search/count` share this limit. Fully cached thread reloads that do not run a new search use a separate higher limit of 120 cached requests per user per 60 seconds. When the rate limit is exceeded, the API returns HTTP 429 with details about the triggered window, current value, and limit.\n\n_Check out official [Python client](https://github.com/Pearch-ai/pearch-client)_\n",
"security": [
{
"bearerAuth": []
}
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The human readable search query string. The query can be a simple search query like \"software engineer from Ohio\" or a more complex query like \"Find me engineers in California speaking at least basic english working in software industry with experience at FAANG with 2+ years of experience and at least 500 followers and at least BS degree\". Query parameter can handle full job descriptions, but passing specific subset of important requirements normally works better. Provide `query`, `search_requirements`, or non-empty `custom_filters` when `thread_id` is omitted. A request with only `custom_filters` uses exact filter retrieval without semantic query ranking. If both `query` and `search_requirements` are provided, `search_requirements` takes precedence for search execution.",
"example": "Software engineer with Python experience from Florida who is interested in science",
"default": "Software engineer with Python experience from Florida who is interested in science"
},
"search_requirements": {
"type": "array",
"description": "Structured search requirements. Use this when you already have a list of requirement texts and whether each one is mandatory. Each item supports only requirement text and `must_have`. If this parameter is provided, it overrides `query` for search execution.",
"items": {
"$ref": "#/components/schemas/SearchRequirement"
},
"example": [
{
"search_requirement": "software engineer",
"must_have": true
},
{
"search_requirement": "located in Dallas",
"must_have": true
},
{
"search_requirement": "has a sense of humor",
"must_have": false
}
]
},
"thread_id": {
"type": "string",
"description": "Unique identifier returned by every `/v2/search` and `/v2/search/submit` call. Reuse it only for pagination by sending `thread_id` with `limit` and optionally `offset`; omit `query` and all search/filter parameters. Adding or changing search/filter parameters, including `query`, `search_requirements`, `custom_filters`, `docid_blacklist`, or `docid_whitelist`, returns HTTP 400. Running a search with the same `thread_id` and same `limit` returns the same results without additional charges.",
"example": "ec191bf9-99ff-4989-8383-c97c71fafb6d"
},
"type": {
"type": "string",
"enum": [
"fast",
"pro"
],
"default": "pro",
"description": "The type of search to perform. \n* \"pro\" is slower and more costly, but has higher quality and recall. **Cost: 5 credits per candidate**\n* \"fast\" is faster but may have less recall. **Cost: 1 credit per candidate**\n"
},
"time_budget": {
"type": "integer",
"minimum": 1,
"default": 200,
"description": "Target search time budget in seconds. Defaults to 30 for fast search and 200 for pro search."
},
"insights": {
"type": "boolean",
"default": true,
"description": "Enable detailed insights and analysis for search results. This includes scores for each of query requirements along with quotes from profiles that match subqueries. Check out `insights` output fields for details. This may be helpful if you share search results with users and want to provide deeper explanations of why profiles are relevant. If your product only needs highly relevant profiles without explanations, use `{\"insights\": false, \"profile_scoring\": true}` **Cost: 1 credit per candidate**"
},
"insights_items": {
"type": "array",
"items": {
"type": "string",
"enum": [
"overall_summary",
"short_quotes",
"rationale",
"short_rationale"
]
},
"description": "When insights is true, optionally restrict which insight fields to include. If omitted, all insight types are included."
},
"high_freshness": {
"type": "boolean",
"default": false,
"description": "Enable real-time profile updates for fresher data. This downloads the most recent copies of profiles directly from source websites in realtime (e.g. Linkedin). If you are ok with profiles that may be a few months outdated, and want to save ~30 seconds, turn off high_freshness. Refreshed roles include `employment_type` when the source provides it. **Cost: 2 credits per candidate**"
},
"fill_with_low_confidence_results": {
"type": "boolean",
"default": false,
"description": "Fill below-limit responses with low confidence results when profile scoring exhausts candidates before reaching the requested limit. These fallback profiles are marked with their score and remain free for search and scoring. When contact reveal is requested, fallback profiles are enriched like regular results and credits_charged includes only contact data actually returned."
},
"custom_filters": {
"$ref": "#/components/schemas/CustomFilters"
},
"custom_filters_mode": {
"type": "string",
"enum": [
"exact",
"smart"
],
"description": "Mode for handling custom filters. 'exact' - only use the passed custom_filters, no LLM-generated filters. 'smart' - merge custom_filters with LLM-generated filters."
},
"strict_filters": {
"type": "boolean",
"default": false,
"description": "Be stricter when filtering. If true, titles must match exactly after expanding abbreviations (e.g., \"CEO\" → \"Chief Executive Officer\") or translating (e.g., \"Ingeniero de software\" → \"Software Engineer\"). If false, fuzzy matching is also used. All other filters are always applied strictly. Enabling strict_filters improves quality but can greatly reduce the number of results. This setting only affects Pearch's implicit filtering. Custom filters are not affected and are always applied strictly."
},
"filter_out_no_emails": {
"type": "boolean",
"default": false,
"description": "Only return profiles with at least one email address. Profiles will have additional `has_email` field set to true. **Cost: 1 credit per candidate**. Deprecated name: `require_emails`"
},
"reveal_emails": {
"type": "boolean",
"default": false,
"description": "Include email addresses in search results if available. This returns all available emails including personal and work emails. **Cost: 6 credits per candidate**. Deprecated name: `show_emails`"
},
"filter_out_no_phones": {
"type": "boolean",
"default": false,
"description": "Only return profiles with at least one phone number. Profiles will have additional `has_phone_numbers` field set to true. **Cost: 1 credit per candidate**. Deprecated name: `require_phone_numbers`"
},
"filter_out_no_phones_or_emails": {
"type": "boolean",
"default": false,
"description": "Only return profiles with at least one phone number OR at least one email address. Useful when you need contact information but either email or phone is acceptable. **Cost: 1 credit per candidate**. Deprecated name: `require_phones_or_emails`"
},
"reveal_phones": {
"type": "boolean",
"default": false,
"description": "Include phone numbers in search results if available. This returns all available phone numbers including personal and work numbers. **Cost: 6 credits per candidate**. Deprecated name: `show_phone_numbers`"
},
"limit": {
"type": "integer",
"minimum": 1,
"maximum": 1000,
"default": 10,
"description": "The maximum number of search results to return."
},
"offset": {
"type": "integer",
"minimum": 0,
"default": 0,
"description": "The number of search results to skip before returning results. Used for pagination in combination with limit."
},
"docid_blacklist": {
"type": "array",
"items": {
"type": "string"
},
"description": "List of profile docids to exclude from search results. Use this to filter out profiles that have already been seen or contacted.",
"example": [
"johndoe",
"janedoe"
]
},
"docid_whitelist": {
"type": "array",
"items": {
"type": "string"
},
"description": "List of profile docids to limit search results to. Only profiles with these docids will be returned.",
"example": [
"johndoe",
"janedoe"
]
},
"webhook_url": {
"type": "string",
"format": "uri",
"description": "An HTTP or HTTPS URL that will receive a POST after the search completes successfully. The JSON request body has exactly the same format as a successful synchronous `/v2/search` response.",
"example": "https://client.example.com/pearch/results"
}
}
}
}
}
},
"responses": {
"202": {
"description": "Search task submitted successfully",
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"task_id": {
"type": "string",
"description": "Unique identifier for the submitted search task.",
"example": "ec191bf9-99ff-4989-8383-c97c71fafb6d"
},
"thread_id": {
"type": "string",
"description": "Thread ID for pagination through `/v2/search` or `/v2/search/submit`. If the search is still in progress, using this `thread_id` returns HTTP 202. Search or filter parameters supplied with `thread_id` return HTTP 400.",
"example": "550e8400-e29b-41d4-a716-446655440000"
},
"status": {
"type": "string",
"description": "The current status of the submitted task. Upon submission, the status is always `pending`.",
"example": "pending"
},
"message": {
"type": "string",
"description": "Human-readable message about the task submission.",
"example": "Search task submitted successfully"
}
}
}
}
}
},
"400": {
"description": "Invalid parameter values. A request that combines `thread_id` with search or filter parameters is rejected with status: `thread_id only supports pagination parameters for this client. Unsupported with thread_id: `."
},
"401": {
"description": "Invalid API key"
},
"429": {
"description": "Rate limit exceeded. JSON body contains the triggered window, current value, and limit."
}
}
}
}
},
"components": {
"schemas": {
"SearchRequirement": {
"type": "object",
"description": "A structured search requirement with text and whether it is mandatory.",
"additionalProperties": false,
"required": [
"search_requirement"
],
"properties": {
"search_requirement": {
"type": "string",
"description": "Requirement text to match against candidate profiles.",
"example": "software engineer"
},
"must_have": {
"type": "boolean",
"default": false,
"description": "Whether this requirement is mandatory. If false, the requirement is treated as a nice-to-have. Use `must_have` sparingly: too many mandatory requirements can make the search overly restrictive and result in fewer returned profiles.",
"example": true
}
}
},
"LocationCoordinateFilter": {
"type": "object",
"additionalProperties": false,
"required": [
"lat",
"lng",
"radius_miles"
],
"properties": {
"lat": {
"type": "number",
"format": "double",
"minimum": -90,
"maximum": 90,
"description": "Latitude of the search-radius center."
},
"lng": {
"type": "number",
"format": "double",
"minimum": -180,
"maximum": 180,
"description": "Longitude of the search-radius center."
},
"radius_miles": {
"type": "number",
"format": "double",
"minimum": 0,
"exclusiveMinimum": true,
"maximum": 500,
"description": "Search radius in miles, greater than 0 and at most 500."
}
}
},
"Industry": {
"type": "string",
"description": "Canonical industry name for custom search filters",
"enum": [
"Archiving Service",
"Call Center",
"Collection Agency",
"College Recruiting",
"Courier Service",
"Debt Collections",
"Delivery",
"Document Preparation",
"Employee Benefits",
"Extermination Service",
"Facilities Support Services",
"Housekeeping Service",
"Human Resources",
"Knowledge Management",
"Office Administration",
"Packaging Services",
"Physical Security",
"Project Management",
"Staffing Agency",
"Trade Shows",
"Virtual Workforce",
"Ad Exchange",
"Ad Network",
"Ad Retargeting",
"Ad Server",
"Ad Targeting",
"Advertising",
"Advertising Platforms",
"Affiliate Marketing",
"Local Advertising",
"Mobile Advertising",
"Native Advertising",
"Outdoor Advertising",
"SEM",
"Social Media Advertising",
"Video Advertising",
"Agriculture",
"AgTech",
"Animal Feed",
"Aquaculture",
"Equestrian",
"Farming",
"Forestry",
"Horticulture",
"Hydroponics",
"Livestock",
"App Discovery",
"Apps",
"Consumer Applications",
"Enterprise Applications",
"Mobile Apps",
"Reading Apps",
"Web Apps",
"Artificial Intelligence (AI)",
"Generative AI",
"Intelligent Systems",
"Machine Learning",
"Natural Language Processing",
"Predictive Analytics",
"Robotic Process Automation (RPA)",
"Bioinformatics",
"Biometrics",
"Biopharma",
"Biotechnology",
"Genetics",
"Life Science",
"Neuroscience",
"Quantified Self",
"Bitcoin",
"Blockchain",
"Cryptocurrency",
"Decentralized Finance (DeFi)",
"Ethereum",
"Non-Fungible Token (NFT)",
"Smart Contracts",
"Web3",
"Apparel",
"Fashion",
"Laundry and Dry-cleaning",
"Lingerie",
"Shoes",
"Auctions",
"Classifieds",
"Collectibles",
"Consumer Reviews",
"Coupons",
"E-Commerce",
"E-Commerce Platforms",
"Flash Sale",
"Gift",
"Gift Card",
"Gift Exchange",
"Gift Registry",
"Group Buying",
"Local Shopping",
"Made to Order",
"Marketplace",
"Office Supplies",
"Online Auctions",
"Personalization",
"Point of Sale",
"Price Comparison",
"Rental",
"Retail",
"Retail Technology",
"Secondhand Goods",
"Shopping",
"Shopping Mall",
"Social Shopping",
"Sporting Goods",
"Vending and Concessions",
"Virtual Goods",
"Wholesale",
"Adult",
"Baby",
"Cannabis",
"Children",
"Communities",
"Dating",
"Elderly",
"Family",
"Funerals",
"Humanitarian",
"Leisure",
"LGBT",
"Lifestyle",
"Men's",
"Online Forums",
"Parenting",
"Pet",
"Private Social Networking",
"Professional Networking",
"Q&A",
"Religion",
"Retirement",
"Sex Industry",
"Sex Tech",
"Social",
"Social Entrepreneurship",
"Teenagers",
"Virtual World",
"Wedding",
"Women's",
"Young Adults",
"Computer",
"Consumer Electronics",
"Drones",
"Electronics",
"Google Glass",
"Mobile Devices",
"Nintendo",
"Playstation",
"Roku",
"Smart Home",
"Wearables",
"Windows Phone",
"Xbox",
"Beauty",
"Card and Board Games",
"Cleaning Products",
"Comics",
"Consumer Goods",
"Cosmetics",
"DIY",
"Eyewear",
"Fast-Moving Consumer Goods",
"Flowers",
"Furniture",
"Green Consumer Goods",
"Handmade",
"Home Appliances",
"Jewelry",
"Personal Care and Hygiene",
"Tobacco",
"Toys",
"Blogging Platforms",
"Books",
"Content Delivery Network",
"Content Discovery",
"Content Syndication",
"Copywriting",
"Creative Agency",
"DRM",
"EBooks",
"Journalism",
"News",
"Photo Editing",
"Photo Sharing",
"Photography",
"Printing",
"Publishing",
"Social Bookmarking",
"Video Editing",
"Video Streaming",
"A/B Testing",
"Analytics",
"Application Performance Management",
"Big Data",
"Business Intelligence",
"Consumer Research",
"Data Collection and Labeling",
"Data Governance",
"Data Integration",
"Data Management",
"Data Mining",
"Data Visualization",
"Database",
"Facial Recognition",
"Geospatial",
"Image Recognition",
"Location Based Services",
"Market Research",
"Product Research",
"Speech Recognition",
"Test and Measurement",
"Text Analytics",
"Usability Testing",
"CAD",
"Graphic Design",
"Human Computer Interaction",
"Industrial Design",
"Interior Design",
"Mechanical Design",
"Product Design",
"UX Design",
"Web Design",
"Alumni",
"Charter Schools",
"Continuing Education",
"Corporate Training",
"E-Learning",
"EdTech",
"Education",
"Edutainment",
"Higher Education",
"Language Learning",
"MOOC",
"Music Education",
"Personal Development",
"Primary Education",
"Secondary Education",
"Skill Assessment",
"Special Education",
"STEM Education",
"Textbook",
"Training",
"Tutoring",
"Vocational Education",
"Battery",
"Biofuel",
"Biomass Energy",
"Clean Energy",
"Electrical Distribution",
"Energy",
"Energy Efficiency",
"Energy Management",
"Energy Storage",
"Fossil Fuels",
"Fuel",
"Fuel Cell",
"Geothermal Energy",
"Hydroelectric",
"Oil and Gas",
"Power Grid",
"Renewable Energy",
"Solar",
"Wind Energy",
"Concerts",
"Event Management",
"Event Promotion",
"Events",
"Nightclubs",
"Nightlife",
"Reservations",
"Ticketing",
"Accounting",
"Angel Investment",
"Asset Management",
"Auto Insurance",
"Banking",
"Bookkeeping and Payroll",
"Commercial Insurance",
"Commercial Lending",
"Consumer Lending",
"Credit",
"Credit Bureau",
"Credit Cards",
"Crowdfunding",
"Debit Cards",
"Finance",
"Financial Exchanges",
"Financial Services",
"FinTech",
"Foreign Exchange Trading",
"Fraud Detection",
"Funding Platform",
"Health Insurance",
"Hedge Funds",
"Impact Investing",
"Incubators",
"Insurance",
"InsurTech",
"Leasing",
"Lending",
"Life Insurance",
"Micro Lending",
"Mobile Payments",
"Payments",
"Personal Finance",
"Prediction Markets",
"Prepaid Cards",
"Property Insurance",
"Real Estate Investment",
"Stock Exchanges",
"Tax Consulting",
"Tax Preparation",
"Trading Platform",
"Transaction Processing",
"Venture Capital",
"Virtual Currency",
"Wealth Management",
"Alternative Protein",
"Bakery",
"Brewing",
"Catering",
"Coffee",
"Confectionery",
"Cooking",
"Craft Beer",
"Dairy",
"Dietary Supplements",
"Distillery",
"Farmers Market",
"Food and Beverage",
"Food Delivery",
"Food Processing",
"Food Trucks",
"Fruit",
"Grocery",
"Herbs and Spices",
"Meat and Poultry",
"Nutrition",
"Organic Food",
"Plant-Based Foods",
"Recipes",
"Restaurants",
"Seafood",
"Snack Food",
"Tea",
"Wine And Spirits",
"Winery",
"Casual Games",
"Console Games",
"Contests",
"Fantasy Sports",
"Gambling",
"Gamification",
"Gaming",
"MMO Games",
"Online Games",
"PC Games",
"Serious Games",
"Video Games",
"CivicTech",
"Government",
"GovTech",
"Law Enforcement",
"Military",
"National Security",
"Politics",
"Public Safety",
"Social Assistance",
"3D Technology",
"Application Specific Integrated Circuit (ASIC)",
"Audio/Visual Equipment",
"Augmented Reality",
"Cloud Infrastructure",
"Communication Hardware",
"Communications Infrastructure",
"Computer Vision",
"Data Center",
"Data Center Automation",
"Data Storage",
"Drone Management",
"DSP",
"Electronic Design Automation (EDA)",
"Embedded Systems",
"Field-Programmable Gate Array (FPGA)",
"Flash Storage",
"GPS",
"GPU",
"Hardware",
"Laser",
"Lighting",
"Network Hardware",
"NFC",
"Optical Communication",
"Private Cloud",
"Remote Sensing",
"RFID",
"RISC",
"Robotics",
"Satellite Communication",
"Semiconductor",
"Sensor",
"Telecommunications",
"Video Conferencing",
"Virtual Reality",
"Virtualization",
"Wireless",
"Addiction Treatment",
"Alternative Medicine",
"Assisted Living",
"Assistive Technology",
"Child Care",
"Clinical Trials",
"Cosmetic Surgery",
"Dental",
"Diabetes",
"Elder Care",
"Electronic Health Record (EHR)",
"Emergency Medicine",
"Fertility",
"First Aid",
"Health Care",
"Health Diagnostics",
"Home Health Care",
"Hospital",
"Medical",
"Medical Device",
"Mental Health",
"mHealth",
"Nursing and Residential Care",
"Nutraceutical",
"Oncology",
"Outpatient Care",
"Personal Health",
"Pharmaceutical",
"Precision Medicine",
"Primary and Urgent Care",
"Psychology",
"Rehabilitation",
"Telehealth",
"Therapeutics",
"Veterinary",
"Wellness",
"Business Information Systems",
"Cloud Data Services",
"Cloud Management",
"Cloud Security",
"CMS",
"Contact Management",
"CRM",
"Cyber Security",
"DevOps",
"Document Management",
"E-Signature",
"Email",
"Identity Management",
"Information and Communications Technology (ICT)",
"Information Services",
"Information Technology",
"Intrusion Detection",
"IT Infrastructure",
"IT Management",
"Management Information Systems",
"Messaging",
"Network Security",
"Penetration Testing",
"Reputation",
"Sales Automation",
"Scheduling",
"Social CRM",
"Spam Filtering",
"Technical Support",
"Unified Communications",
"Video Chat",
"VoIP",
"Cloud Computing",
"Cloud Storage",
"Darknet",
"Domain Registrar",
"Ediscovery",
"Internet",
"Internet of Things",
"ISP",
"Music Streaming",
"Online Portals",
"Product Search",
"Search Engine",
"Semantic Search",
"Semantic Web",
"SEO",
"SMS",
"Social Media",
"Social Media Management",
"Social Network",
"Vertical Search",
"Visual Search",
"Web Browsers",
"Web Hosting",
"3D Printing",
"Advanced Materials",
"Foundries",
"Industrial",
"Industrial Automation",
"Industrial Engineering",
"Industrial Manufacturing",
"Machinery Manufacturing",
"Manufacturing",
"Paper Manufacturing",
"Plastics and Rubber Manufacturing",
"Textiles",
"Wood Processing",
"Advice",
"Animation",
"Art",
"Audio",
"Audiobooks",
"Broadcasting",
"Celebrity",
"Content",
"Content Creators",
"Digital Entertainment",
"Digital Media",
"Film",
"Film Distribution",
"Film Production",
"Guides",
"In-Flight Entertainment",
"Independent Music",
"Internet Radio",
"Media and Entertainment",
"Metaverse",
"Motion Capture",
"Music",
"Music Label",
"Music Venues",
"Musical Instruments",
"Performing Arts",
"Podcast",
"Social News",
"Theatre",
"TV",
"TV Production",
"Video",
"Video on Demand",
"Meeting Software",
"Wired Telecommunications",
"Android",
"iOS",
"Mobile",
"Audio Recording and Production",
"Mineral",
"Mining",
"Mining Technology",
"Natural Resources",
"Precious Metals",
"Timber",
"Water",
"Indoor Positioning",
"Mapping Services",
"Navigation",
"Association",
"B2B",
"B2C",
"Charity",
"Collaboration",
"Collaborative Consumption",
"Commercial",
"Consumer",
"Crowdsourcing",
"Customer Service",
"Desktop Apps",
"Emerging Markets",
"Enterprise",
"Franchise",
"Freemium",
"Generation Y",
"Generation Z",
"Homeless Shelter",
"Infrastructure",
"LGBT Millennials",
"Non Profit",
"Peer to Peer",
"Professional Services",
"Real Time",
"Service Industry",
"Sharing Economy",
"Small and Medium Businesses",
"Social Impact",
"Subscription Service",
"Underserved Children",
"Universities",
"Billing",
"Facebook",
"Google",
"Linux",
"macOS",
"Operating Systems",
"Tizen",
"Twitter",
"WebOS",
"Windows",
"Corrections Facilities",
"Homeland Security",
"Privacy",
"Security",
"Advocacy",
"Business Development",
"Career Planning",
"Compliance",
"Consulting",
"Employment",
"Environmental Consulting",
"Field Support",
"Freelance",
"Innovation Management",
"Intellectual Property",
"Legal",
"Legal Tech",
"Management Consulting",
"Outsourcing",
"Quality Assurance",
"Recruiting",
"Risk Management",
"Social Recruiting",
"Translation Service",
"Architecture",
"Building Maintenance",
"Building Material",
"Commercial Real Estate",
"Construction",
"Coworking",
"Facility Management",
"Green Building",
"Heating",
"Ventilation",
"and Air Conditioning (HVAC)",
"Home and Garden",
"Home Decor",
"Home Improvement",
"Home Renovation",
"Home Services",
"Janitorial Service",
"Landscaping",
"Mortgage",
"Property Development",
"Property Management",
"PropTech",
"Real Estate",
"Real Estate Brokerage",
"Rental Property",
"Residential",
"Self-Storage",
"Smart Building",
"Smart Cities",
"Timeshare",
"Vacation Rental",
"App Marketing",
"Brand Marketing",
"Cause Marketing",
"Content Marketing",
"Digital Marketing",
"Digital Signage",
"Direct Marketing",
"Direct Sales",
"Email Marketing",
"Lead Generation",
"Lead Management",
"Local",
"Local Business",
"Loyalty Programs",
"Marketing",
"Marketing Automation",
"Multi-level Marketing",
"Personal Branding",
"Public Relations",
"Sales",
"Sales Enablement",
"Social Media Marketing",
"Sponsorship",
"Aerospace",
"Chemical",
"Chemical Engineering",
"Civil Engineering",
"Environmental Engineering",
"Marine Technology",
"Mechanical Engineering",
"Nanotechnology",
"Nuclear",
"Quantum Computing",
"Software Engineering",
"Browser Extensions",
"Business Process Automation (BPA)",
"Chatbot",
"Consumer Software",
"Developer APIs",
"Developer Platform",
"Developer Tools",
"Embedded Software",
"Enterprise Resource Planning (ERP)",
"Enterprise Software",
"File Sharing",
"IaaS",
"Open Source",
"PaaS",
"Presentation Software",
"Presentations",
"Productivity Tools",
"QR Codes",
"SaaS",
"Simulation",
"SNS",
"Software",
"Task Management",
"Virtual Assistant",
"Virtual Desktop",
"Web Development",
"American Football",
"Baseball",
"Basketball",
"Boating",
"Cricket",
"Cycling",
"Diving",
"eSports",
"Fitness",
"Golf",
"Hockey",
"Hunting",
"Motorsports",
"Outdoors",
"Racing",
"Recreation",
"Rugby",
"Sailing",
"Skiing",
"Soccer",
"Sports",
"Sports Leagues and Teams",
"Surfing",
"Swimming",
"Table Tennis",
"Tennis",
"Ultimate Frisbee",
"Volley Ball",
"Carbon Capture",
"CleanTech",
"GreenTech",
"Organic",
"Pollution Control",
"Recycling",
"Sustainability",
"Waste Management",
"Water Purification",
"Wildlife Conservation",
"Air Transportation",
"Automotive",
"Autonomous Vehicles",
"Car Sharing",
"Charging Infrastructure",
"Delivery Service",
"Electric Vehicle",
"Ferry Service",
"Fleet Management",
"Freight Service",
"Last Mile Transportation",
"Limousine Service",
"Logistics",
"Marine Transportation",
"Parking",
"Ports and Harbors",
"Procurement",
"Public Transportation",
"Railroad",
"Recreational Vehicles",
"Ride Sharing",
"Same Day Delivery",
"Shipping",
"Shipping Broker",
"Space Travel",
"Supply Chain Management",
"Taxi Service",
"Transportation",
"Warehouse Automation",
"Warehousing",
"Water Transportation",
"Adventure Travel",
"Amusement Park and Arcade",
"Business Travel",
"Casino",
"Hospitality",
"Hotel",
"Museums and Historical Sites",
"Parks",
"Resorts",
"Tour Operator",
"Tourism",
"Travel",
"Travel Accommodations",
"Travel Agency"
]
},
"CustomFilters": {
"type": "object",
"description": "Custom filters in JSON format for advanced filtering. Omit the parameter to use default filtering logic.\nFormat: `{\"filter_name1\": [\"value1\", \"value2\"], \"filter_name2\": [\"value3\", \"value4\"], ...}`. \n\nFiltering logic: Conditions between different keys are joined with \"AND\", so all conditions must pass. Within each condition, we always use \"OR\". For example, `{\"titles\": [\"swe\", \"mle\"]}` means the profile must have either \"swe\" OR \"mle\" as a title. If you specify multiple keys like `{\"titles\": [\"swe\", \"mle\"], \"locations\": [\"San Francisco\"]}`, the profile must match at least one title (swe OR mle) AND be in San Francisco.\n\n`industries` and `not_industries` take canonical industry names listed under `Industry`; matching is case-insensitive. In `fast` and `superfast` search and in `/v2/search/count`, an unknown industry returns HTTP 400. In `pro` search, other strings are mapped semantically to canonical industries. An industry matches any employer in the person's career history, not only the current one.\nIf you want to force no filtering at all (`custom_filters` or default filters), pass empty object `\"custom_filters\": {}`. This will speed up search, increase recall at some relevancy cost.\n",
"properties": {
"locations": {
"type": "array",
"maxItems": 50,
"items": {
"type": "string"
},
"description": "Filter by location (e.g., \"San Francisco\", \"New York\", \"California\", \"United States\")",
"example": [
"San Francisco",
"New York"
]
},
"location_coordinates": {
"type": "array",
"maxItems": 50,
"items": {
"$ref": "#/components/schemas/LocationCoordinateFilter"
},
"description": "Filter by one or more latitude/longitude radius areas. Areas within this field are combined with OR.",
"example": [
{
"lat": 37.7749,
"lng": -122.4194,
"radius_miles": 25
}
]
},
"not_locations": {
"type": "array",
"maxItems": 50,
"items": {
"type": "string"
},
"description": "Exclude profiles by location (same format as locations)",
"example": [
"Austin",
"Boston"
]
},
"languages": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Language"
},
"description": "Filter by languages with optional proficiency (e.g. object with language and proficiency)",
"example": [
{
"language": "English",
"proficiency": "C1"
}
]
},
"not_languages": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Language"
},
"description": "Exclude profiles by languages (same Language object format as languages)",
"example": [
{
"language": "Spanish",
"proficiency": "B2"
}
]
},
"titles": {
"type": "array",
"items": {
"type": "string"
},
"description": "Filter by job titles (e.g., \"Software Engineer\", \"Data Scientist\", \"CEO\")",
"example": [
"software engineer",
"data scientist"
]
},
"not_titles": {
"type": "array",
"items": {
"type": "string"
},
"description": "Exclude profiles by job titles (e.g., \"Intern\", \"Volunteer\")",
"example": [
"intern",
"volunteer"
]
},
"current_titles": {
"type": "array",
"items": {
"type": "string"
},
"description": "Filter by current job title only",
"example": [
"software engineer",
"tech lead"
]
},
"not_current_titles": {
"type": "array",
"items": {
"type": "string"
},
"description": "Exclude profiles by current job title (same format as current_titles)",
"example": [
"retired",
"student"
]
},
"industries": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Industry"
},
"description": "Filter by canonical industry names listed under Industry; case-insensitive. Matches any employer in the career history.",
"example": [
"Health Care",
"Pharmaceutical"
]
},
"not_industries": {
"type": "array",
"items": {
"$ref": "#/components/schemas/Industry"
},
"description": "Exclude profiles by canonical industry names listed under Industry",
"example": [
"Retail",
"Gaming"
]
},
"companies": {
"type": "array",
"items": {
"type": "string"
},
"description": "Filter by company names (e.g., \"Google\", \"Microsoft\", \"Amazon\")",
"example": [
"Google",
"Microsoft"
]
},
"not_companies": {
"type": "array",
"items": {
"type": "string"
},
"description": "Exclude profiles by company (any experience; same format as companies)",
"example": [
"Acme Corp",
"Former Employer Inc"
]
},
"current_experience_companies": {
"type": "array",
"items": {
"type": "string"
},
"description": "Filter by current employer only",
"example": [
"Google",
"Meta"
]
},
"not_current_experience_companies": {
"type": "array",
"items": {
"type": "string"
},
"description": "Exclude profiles by current employer (same format as current_experience_companies)",
"example": [
"Company X",
"Competitor Inc"
]
},
"universities": {
"type": "array",
"items": {
"type": "string"
},
"description": "Filter by universities attended (e.g., \"Stanford University\", \"MIT\", \"Harvard\")",
"example": [
"Stanford University",
"MIT"
]
},
"not_universities": {
"type": "array",
"items": {
"type": "string"
},
"description": "Exclude profiles by university (same format as universities)",
"example": [
"Unknown College",
"Online University"
]
},
"keywords": {
"type": "array",
"items": {
"type": "string"
},
"description": "Filter by keywords in full profile description",
"example": [
"machine learning",
"python",
"leadership"
]
},
"keywords_blacklist": {
"type": "array",
"items": {
"type": "string"
},
"description": "Exclude profiles containing these keywords",
"example": [
"retired",
"student only"
]
},
"min_linkedin_followers": {
"type": "integer",
"description": "Minimum number of LinkedIn followers",
"example": 500
},
"max_linkedin_followers": {
"type": "integer",
"description": "Maximum number of LinkedIn followers",
"example": 10000
},
"min_total_experience_years": {
"type": "number",
"description": "Minimum total years of professional experience",
"example": 5.5
},
"max_total_experience_years": {
"type": "number",
"description": "Maximum total years of professional experience",
"example": 15.5
},
"min_estimated_age": {
"type": "number",
"description": "Minimum estimated age",
"example": 25
},
"max_estimated_age": {
"type": "number",
"description": "Maximum estimated age",
"example": 45
},
"studied_at_top_universities": {
"type": "boolean",
"description": "Filter for candidates who attended top-tier universities",
"example": true
},
"first_name": {
"type": "string",
"description": "Filter by first name (exact match)",
"example": "John"
},
"middle_name": {
"type": "string",
"description": "Filter by middle name (exact match)",
"example": "Michael"
},
"last_name": {
"type": "string",
"description": "Filter by last name (exact match)",
"example": "Smith"
},
"gender": {
"type": "string",
"enum": [
"male",
"female"
],
"description": "Filter by gender",
"example": "male"
},
"has_startup_experience": {
"type": "boolean",
"description": "Filter for candidates who have worked at startups",
"example": true
},
"has_saas_experience": {
"type": "boolean",
"description": "Filter for candidates who have worked at SaaS companies",
"example": true
},
"has_b2b_experience": {
"type": "boolean",
"description": "Filter for candidates who have worked at B2B companies",
"example": true
},
"has_b2c_experience": {
"type": "boolean",
"description": "Filter for candidates who have worked at B2C companies",
"example": true
},
"min_current_experience_years": {
"type": "number",
"description": "Minimum years in current role",
"example": 1
},
"max_current_experience_years": {
"type": "number",
"description": "Maximum years in current role",
"example": 5
},
"degrees": {
"type": "array",
"items": {
"type": "string",
"enum": [
"bachelor",
"master",
"MBA",
"doctor",
"postdoc"
]
},
"description": "Filter by degree types",
"example": [
"bachelor",
"master"
]
},
"not_degrees": {
"type": "array",
"items": {
"type": "string",
"enum": [
"bachelor",
"master",
"MBA",
"doctor",
"postdoc"
]
},
"description": "Exclude profiles by degree types (same enum as degrees)",
"example": [
"bachelor"
]
},
"specialization_categories": {
"type": "array",
"items": {
"type": "string",
"enum": [
"Business & Management",
"Finance",
"Engineering",
"Computer Science & IT",
"Health & Medicine",
"Social Sciences",
"Natural Sciences",
"Mathematics",
"Education",
"Communication & Media",
"Arts, Design & Architecture",
"Humanities & Liberal Arts",
"Law & Criminal Justice"
]
},
"description": "Filter by specialization categories. Allowed values include: Business & Management, Finance, Engineering, Computer Science & IT, Health & Medicine, Social Sciences, Natural Sciences, Mathematics, Education, Communication & Media, Arts, Design & Architecture, Humanities & Liberal Arts, Law & Criminal Justice.",
"example": [
"Computer Science & IT",
"Engineering"
]
},
"not_specialization_categories": {
"type": "array",
"items": {
"type": "string",
"enum": [
"Business & Management",
"Finance",
"Engineering",
"Computer Science & IT",
"Health & Medicine",
"Social Sciences",
"Natural Sciences",
"Mathematics",
"Education",
"Communication & Media",
"Arts, Design & Architecture",
"Humanities & Liberal Arts",
"Law & Criminal Justice"
]
},
"description": "Exclude profiles by specialization category (same enum as specialization_categories)",
"example": [
"Arts, Design & Architecture"
]
}
},
"additionalProperties": false,
"example": {
"industries": [
"Health Care",
"Pharmaceutical"
],
"locations": [
"San Francisco",
"New York"
],
"titles": [
"software engineer",
"data scientist"
],
"min_total_experience_years": 5.5,
"studied_at_top_universities": true
}
},
"Language": {
"type": "object",
"description": "Language with proficiency level",
"properties": {
"language": {
"type": "string",
"description": "Language name",
"example": "English"
},
"proficiency": {
"type": "string",
"description": "Proficiency level: A1, A2, B1, B2, C1, C2",
"enum": [
"A1",
"A2",
"B1",
"B2",
"C1",
"C2",
"unknown"
],
"example": "C1"
}
}
}
},
"securitySchemes": {
"bearerAuth": {
"type": "http",
"scheme": "bearer",
"bearerFormat": "JWT"
}
}
},
"security": [
{
"bearerAuth": []
}
]
}
```