Smart Job Titles

POST/v2/search/smart-job-titles

AI-suggested job titles that reach more of the people your titles are meant to find: other ways the same role is written (synonyms, abbreviations, plurals, translations into the languages of your locations), closely related roles, and broader roles in the same function. Each title carries the narrowest smart_level that includes it (SAME_ROLE, SIMILAR, RELATED) and new_people: how many people it adds to the search you describe in filters. Titles that add nobody - a variant your own titles already match, or a title nobody in your search holds - are left out, and so are titles adding fewer than 0.1% of your search (at most 100 people). Search the titles you keep with CONTAINS; person_job_title.match_mode: SMART does the same server-side but, having no counts, keeps every AI title, so it can find a few more people. Free: costs no credits. A new answer uses one of the workspace's daily AI suggestions (by plan); the same titles and filters again are answered from cache for free. Counts against the per-second window of the search rate limit (0 units). Authenticate with your API key in the x-api-key header.

How are credits spent?

Smart Job Titles is free and consumes no credits. A new AI answer uses one of your workspace's daily AI suggestions (see Daily AI allowance below); asking again for the same titles and filters is answered from cache and uses nothing.

What it does

Send the job titles you would search with, and the AI suggests the other titles the same people hold on their profiles, so a People Search reaches more of the right people:

other ways to write the same role: synonyms, abbreviations, plurals and translations into the languages of your locations (Germany brings Leiter Einkauf for "Head of Procurement");
closely related roles of the same function and level;
broader roles in the same function.

Pass the People Search filters you will search with. Locations decide which languages the suggestions come in; industry, seniority and department sharpen what the AI reads into your titles; and every filter scopes the counts. person_job_title inside filters is ignored apart from its exclude, which is used when exclude_job_titles is absent.

You can use the answer two ways:

show the titles to a user, let them pick, and search the picked ones with person_job_title.match_mode: "CONTAINS";
or skip this call and send match_mode: "SMART" to People Search, which adds the titles itself (see Smart match mode in People Search below).

Three levels

Every title carries level, the narrowest level that includes it. The levels are nested: SAME_ROLE < SIMILAR < RELATED.

Level	In the App	Adds	Example
`SAME_ROLE`	Same role	Other ways to write the same role: synonyms, abbreviations, plurals, translations	VP of Sales -> Sales VP
`SIMILAR` (default)	Similar	Also closely related roles of the same function and level	Head of Sales -> Sales Director
`RELATED`	Related	Also broader roles in the same function	SDR -> Account Executive

One call answers all three levels. To show a level, keep the titles whose level is at or below it; switching levels needs no new request.

Reading the counts

new_people - how many people the title adds on top of your own titles, under your filters and after every exclusion. Each title is counted on its own, so the numbers overlap and do not add up to the total. null when the count could not be taken.
Titles that add nobody are left out. A variant your own titles already match (CONTAINS matches every word in any order, so "Founder & CEO" adds no one when "CEO" is listed), or a title too few people in your search hold, is not returned. titles can be empty: that is still a 200.
titles is ordered by level, then by new_people, most first.

Exclusions

exclude_titles lists other spellings of the roles you exclude ("Intern" -> "Trainee", "Praktikant"), each with removed_people: how many people excluding it takes out of your search. They are same-role spellings only, whatever the level, and are empty without exclusions of your own.

An exclusion can show removed_people: 0 and still be worth keeping. Job title filters apply per position: a person matches when one of their positions has an included title and no excluded one. A spelling of a role you did not include rarely removes anyone from today's search, but it keeps that role out once your include list widens. That is why every spelling is returned, even at 0.

Nothing your exclusions reject is ever suggested in titles.

Smart match mode in People Search

People Search does the same work when you send match_mode: "SMART":

Response

POST /v2/people/search
{
  "filters": {
    "person_job_title": {
      "include": ["Head of Sales"],
      "exclude": ["Intern"],
      "match_mode": "SMART",
      "smart_level": "SIMILAR"
    }
  }
}

The AI titles at or below smart_level are added to include, the other spellings of the excluded roles to exclude, and the filter then runs as CONTAINS. Search, count, save, enrich and export all match the same people. metadata.smart_job_titles lists what was added, without counts. See People Search (Smart job-title match) for the response shape.

Caching

An AI answer is cached for 30 days and shared by every workspace: the same titles, exclusions and context (locations, industries, seniorities, departments) are answered from cache. Case and order do not matter.
The counts are cached for an hour per workspace.
metadata.cached is true when the answer came from cache. A cached answer is free and does not use your daily allowance.

Daily AI allowance

Only a new AI answer (one not in the cache) uses the workspace's daily allowance. It resets at 00:00 UTC, and a call that fails is not counted. The allowance follows the same plan tiers as Rate limits:

Plan	New AI answers per day
Free	30
Starter	200
Growth 5K	500
Growth 20K	1,000
Growth 50K and above	2,000

When it is used up, a request that needs a new answer gets 429 with the error name RATE_LIMIT and payload.code: "ai_daily_limit". Cached answers keep working, and People Search with match_mode: "SMART" answers the same 429 when it needs a new answer. Search with match_mode: "CONTAINS" until the reset.

The endpoint also counts against the per-second window of the search rate limit, at 0 units: it never spends your per-minute or per-day search units.

Errors

Status	Error	When
`400`	`VALIDATION_ERROR`	`job_titles` is empty or has more than 20 items, a title is shorter than 2 or longer than 100 characters, or `filters` that People Search itself would refuse.
`429`	`RATE_LIMIT` with `payload.code: "ai_daily_limit"`	The daily AI allowance is used up.
`429`	`RATE_LIMIT`	The per-second window of the `search` rate limit; wait `Retry-After` seconds.
`503`	`UNAVAILABLE`	The AI could not answer right now. Retry shortly, or search with `match_mode: "CONTAINS"`.

In People Search, the AI being unavailable never fails the search: it runs on your own titles and metadata.smart_job_titles.error is "unavailable".

Body parameters

job_titlesstring[]required
Your own job-title terms (what you would send as person_job_title.include). 1-20 items, 2-100 characters each.
Example
```
{
  "job_titles": [
    "Head of Sales"
  ]
}
```
exclude_job_titlesstring[]optional
Your own excluded job-title terms (person_job_title.exclude). Nothing they reject is suggested, and exclude_titles answers their other spellings ("Intern" -> "Trainee", "Praktikant"). Up to 20 items, 2-100 characters each. Absent: the exclude inside filters.
Example
```
{
  "job_titles": [
    "Head of Sales"
  ],
  "exclude_job_titles": [
    "Intern"
  ]
}
```

filtersobjectoptional

The People Search filter set, also taken by the whole-search save, enrich and credits preview.

Child attributes

personobjectoptional

Filter on the person themselves for People Search: by GetProspect person id, by name, or a lookup of specific profiles by LinkedIn URL.

Child attributes

idobjectoptional

Filter on GetProspect person ids for People Search: only these people, or reject them (up to 100 ids each).

Field	Type	Description
`include`	string[]	Only these people. Use the `id` values returned by People Search results, People Enrich, or Search Suggestions with `type: "person"`. Max 100 ids.
`exclude`	string[]	Reject these people (same `id` values). Max 100 ids.

nameobjectoptional

Filter on the person's name for People Search: include or exclude names, each term matching when all its words appear in the name.

Field	Type	Description
`include`	string[]	Names to match. Every word of a term must appear somewhere in the name, in any order, so "Dmytro Shulha" matches "Dmytro Shulha, PhD" and "Helena Calero" matches "Helena Montoya-Calero". Case-insensitive; diacritics are significant ("Jose" does not match "José"). Any single term qualifies. Max 500 items.
`exclude`	string[]	Names to reject, matched the same way. Max 500 items.

linkedin_urlobjectoptional

Lookup of specific people for People Search by LinkedIn profile URL (1-50); the other filters narrow the result.

Field	Type	Description
`include`	string[]	Look up specific profiles by LinkedIn URL. The URLs pick the people and every other filter narrows them - except `company.name.include`, which here only picks which position is returned as `primary_position`. Cannot be combined with `person.id` or `person.name`. Results keep the order of the URLs (`sort_by` does not apply) and each carries the `matched_url` it was found by. 1-50 urls. Example: `["https://www.linkedin.com/in/emily-carter-sample/"]`

Example

{
  "filters": {
    "person": {
      "name": {
        "include": [
          "Dmytro Shulha"
        ]
      }
    }
  }
}

person_locationobjectoptional

Include/exclude filter on unified location strings (country, state, city or region), used by People Search person_location.

Field	Type	Description
`include`	string[]	Match these locations (any of). Unified strings like "United States", "Texas, United States", "San Francisco, California, United States" - or a region like "EMEA", "APAC", "Europe", "Latin America", which expands to its member countries (full list with member countries: GET /v2/enums/regions). Max 100 items, each 2-200 chars. If none of the values resolve to a known location, the request fails with 400.
`exclude`	string[]	Reject these locations (same unified-string format). Max 100 items, each 2-200 chars. Values that do not resolve are skipped.

Example

{
  "filters": {
    "person_location": {
      "include": [
        "California, United States",
        "Austin, Texas, United States"
      ],
      "exclude": [
        "San Francisco, California, United States"
      ]
    }
  }
}

company_keywordsobjectoptional

Phrase filter on company keyword fields (Keyword sources), shared by company_keywords in People Search and Company Search.

Field	Type	Description
`include`	string[]required	Phrases to search for. 1-20 items, 3-100 chars each. Matched as phrases: a multi-word entry like "email finder" requires those words adjacent and in order within one of the selected source fields, not merely present somewhere in it.
`exclude`	string[]	Phrases that disqualify a company. 0-20 items. Matched as phrases, same as `include`.
`include_all`	boolean	When true, every phrase in `include` must match; otherwise any single match qualifies. default: false.
`sources`	enum[]	Restrict matching to these source fields (see Keyword sources). Omit to use the default source set - see this `company_keywords` filter's own description above for what that is.

Example

{
  "filters": {
    "company_keywords": {
      "include": [
        "email marketing"
      ],
      "sources": [
        "specialties"
      ]
    }
  }
}

person_job_titleobjectoptional

Filter on the person's job title for People Search: include or exclude titles matched per match_mode, or one boolean_search expression instead.

Field	Type	Description
`include`	string[]	Job titles to match. Max 100 items, each 2-100 chars. Combined per match_mode. Known abbreviations also match their canonical spelling and vice versa (e.g. "CEO" matches "Chief Executive Officer"), however you spell them - "VP of Marketing", "VP, Marketing" and "Marketing VP" all match what "VP Marketing" matches. Under CONTAINS, terms match any of the roles a position carries - including the secondary roles of combined titles like "Founder & CEO" and the original title text.
`exclude`	string[]	Job titles to reject. Max 100 items, each 2-100 chars.
`match_mode`	enum	CONTAINS = the title contains every word of the term, in any order; connector words (of, and, the, ...) are ignored, so "Director of Sales Enablement" also matches "Director, Sales Enablement". EXACT = the person's LinkedIn title is exactly the term, so "founder" does not match "Founder & CEO", "Founder of Acme LLC" or "Fondateur" - use CONTAINS for those. SMART = CONTAINS plus AI-suggested titles the same people hold (synonyms, translations for your locations, related roles - see smart_level), and `exclude` widened with the other spellings of the excluded roles ("Intern" also excludes "Trainee", "Praktikant"); what was added is listed in `metadata.smart_job_titles`, and POST /v2/search/smart-job-titles previews them with how many people each adds. Applies to include/exclude; ignored when boolean_search is set. Allowed values: `CONTAINS` `EXACT` `SMART`
`smart_level`	enum	How far match_mode SMART reaches. SAME_ROLE = other ways to write the same role (synonyms, abbreviations, plurals, translations): "VP of Sales" -> "Sales VP". SIMILAR (default) = also closely related roles of the same function and level: "Head of Sales" -> "Sales Director". RELATED = also broader roles in the same function: "SDR" -> "Account Executive". Ignored unless match_mode is SMART. Allowed values: `SAME_ROLE` `SIMILAR` `RELATED`
`boolean_search`	string	Boolean / Cartesian title query, e.g. "(CEO OR CTO) AND !Intern". Syntax: bareword=contains; 'single quotes'=contains too, and the way to write a title with a space in it - 'vp marketing' matches exactly what include: ["vp marketing"] matches; "double quotes"=exact; `backticks`=words in order with connectors bridged, so `vp marketing` finds "VP of Marketing" but not "VP Sales and Marketing" or "Marketing VP"; !=exclude, AND/OR, ()=grouping. Max 500 terms, depth 5, each term 2-100 chars. AND and OR cannot be mixed at the same nesting level - use parentheses to group. Mutually exclusive with include/exclude. max length: 20000.

Example

{
  "filters": {
    "person_job_title": {
      "include": [
        "Product Marketing Manager",
        "Growth Marketing Manager"
      ],
      "exclude": [
        "Assistant"
      ],
      "match_mode": "CONTAINS"
    }
  }
}

person_seniorityobjectoptional
Filter on the seniority level of the person's position for People Search: include or exclude values from Seniorities. Casing and spacing do not matter, and common synonyms are accepted as their level: Founder and Co-Founder (Owner), Board and Board Member (Partner), C-Level, CXO and CEO (C-Suite), Vice President (VP), Individual Contributor (Mid-level), Junior and Entry Level (Entry), Trainee (Intern), and the retired Chief Officer (C-Suite).
Field Type Description
include enum[] Seniority levels to match (any of). See Seniorities.
exclude enum[] Seniority levels to reject. See Seniorities.
Example
```
{
  "filters": {
    "person_seniority": {
      "include": [
        "C-Suite",
        "VP",
        "Director"
      ]
    }
  }
}
```

Field	Type	Description
`include`	enum[]	Seniority levels to match (any of). See Seniorities.
`exclude`	enum[]	Seniority levels to reject. See Seniorities.

person_departmentobjectoptional

Filter on the department of the person's position for People Search: include or exclude department groups or sub-departments. Casing does not matter. The names of the previous department list are still accepted as the sub-department that replaced them (for example Web Design as Graphic, Web & Brand Design, Sourcing & Procurement as Procurement & Purchasing).

Field	Type	Description
`include`	enum[]	Departments to match (any of). Accepts a department group ("Sales", "Legal") or a specific sub-department ("Sales Operations", "Founder"). A group matches everyone in it, including people with no specific sub-department; a sub-department matches only that sub-department. See Departments.
`exclude`	enum[]	Departments to reject. A group rejects everyone in it, including people with no specific sub-department; a sub-department rejects only that sub-department. See Departments.

Example

{
  "filters": {
    "person_department": {
      "include": [
        "Marketing",
        "Sales"
      ],
      "exclude": [
        "Accounting"
      ]
    }
  }
}

person_months_in_current_roleobjectoptional
An inclusive range of whole months (0-600), used by the People Search tenure filters for the current role and the current company.
Field Type Description
min integer Minimum whole months (inclusive), 0-600. Optional. min: 0, max: 600.
max integer Maximum whole months (inclusive), 0-600, must be >= min. Optional. min: 0, max: 600.
Example
```
{
  "filters": {
    "person_months_in_current_role": {
      "min": 6,
      "max": 24
    }
  }
}
```
person_months_in_current_companyobjectoptional
An inclusive range of whole months (0-600), used by the People Search tenure filters for the current role and the current company.
Field Type Description
min integer Minimum whole months (inclusive), 0-600. Optional. min: 0, max: 600.
max integer Maximum whole months (inclusive), 0-600, must be >= min. Optional. min: 0, max: 600.
Example
```
{
  "filters": {
    "person_months_in_current_company": {
      "min": 12
    }
  }
}
```

Field	Type	Description
`min`	integer	Minimum whole months (inclusive), 0-600. Optional. min: 0, max: 600.
`max`	integer	Maximum whole months (inclusive), 0-600, must be >= min. Optional. min: 0, max: 600.

Field	Type	Description
`min`	integer	Minimum whole months (inclusive), 0-600. Optional. min: 0, max: 600.
`max`	integer	Maximum whole months (inclusive), 0-600, must be >= min. Optional. min: 0, max: 600.

person_job_changeobjectoptional

Filter for People Search on a recent job change: the current role started within timeframe_months, optionally narrowed by change_type.

Field	Type	Description
`timeframe_months`	integerrequired	Months since the current role started, counted in CALENDAR months the way LinkedIn counts them: a role is "N months" if it spans N calendar months inclusive, so a role begun any time in August is 2 months old on 1 September. `timeframe_months: 1` therefore matches only roles begun in the current month. Any whole number from 1 to 1000. Replaces the former `timeframe_days`, which accepted only 30, 60, 90, 180, 270 or 365. min: 1, max: 1000. Example: `3`
`change_type`	enum	any = any recent role change; new_company = also changed company; promotion = changed role at the same company (approximation, includes lateral moves). Allowed values: `any` `promotion` `new_company`

Example

{
  "filters": {
    "person_job_change": {
      "timeframe_months": 3,
      "change_type": "new_company"
    }
  }
}

companyobjectoptional

Filter on the person's company for People Search: by company id, website domain, name or LinkedIn company id.

Child attributes

idobjectoptional

Filter on the person's company for People Search by GetProspect company id: include or exclude companies.

Field	Type	Description
`include`	string[]	Only people who work at one of these companies. Use the `id` values returned by Company Search or in People Search results. Combines with an exact `company.name` as OR (a person at any listed id or any listed name); `company.domain`, `company_keywords` and a CONTAINS `company.name` still narrow it. Max 20000 ids.
`exclude`	string[]	Reject people who work at any of these companies (same `id` values). Max 20000 ids.

domainobjectoptional

Filter on the person's company for People Search by website domain: include or exclude domains, with match_mode for which company pages count.

Field	Type	Description
`include`	string[]	Only people who work at the organization that owns one of these domains, e.g. "stripe.com" - see `match_mode` for which of its company pages count. Scheme, "www." and any path are stripped. Max 100 items.
`exclude`	string[]	Reject people whose company is on one of these domains.
`match_mode`	enum	Which company pages an `include` domain stands for. ORGANIZATION (default) = every company page that belongs to the organization owning the domain: its main page, its regional, brand and subsidiary pages. A small page that only links to the domain - a business hosted on a platform, a same-named company - is left out. PRIMARY = only the one main company page of the domain, leaving out the organization's other pages. LINKEDIN_WEBSITE = only the organization's pages whose own LinkedIn website is on the domain, so the domain is never inferred: "stripe.com", "stripe.com/jobs" and "jobs.stripe.com" all match "stripe.com"; a page that lists another site, or no website, does not. `exclude` is not affected: it always rejects every company on the domain. Allowed values: `ORGANIZATION` `PRIMARY` `LINKEDIN_WEBSITE`

Example

{
  "filters": {
    "company": {
      "domain": {
        "include": [
          "stripe.com"
        ]
      }
    }
  }
}

nameobjectoptional

Filter on the person's company for People Search by name: include or exclude names, matched exactly or, with match_mode: CONTAINS, as a term within the name.

Field	Type	Description
`include`	string[]	Company names to match. Combined per match_mode. With EXACT, a value shaped like a website ("stripe.com", "https://www.stripe.com/about") also matches the company on that domain. Max 500 items.
`exclude`	string[]	Company names to reject. With EXACT, a website-shaped value also rejects the company on that domain.
`match_mode`	enum	EXACT (default) = the whole company name equals the term, case-insensitive. CONTAINS = the name contains the term as written, case-insensitive, starting at a word ("Haven Health" matches "Haven Health Management" and "New Haven Healthcare"). A match inside a longer word ("nails" in "AllNailSpa") comes back only for a term that matches no name at a word start, and reliably only for a single-word term. A multi-word term that matches no name as written falls back to names holding all of its words in any order ("Oak Park River Forest High School" matches "Oak Park and River Forest High School"). An `exclude` term matches anywhere in the name ("soft" also rejects "Microsoft"). Resolved against the company index and capped; narrow the term if the request is rejected. Allowed values: `EXACT` `CONTAINS`

linkedin_idobjectoptional

Include/exclude filter on LinkedIn's numeric company id, shared by the company.linkedin_id filter of People Search and Company Search.

Field	Type	Description
`include`	integer[]	Match these LinkedIn companies. LinkedIn's numeric company id. Company URLs are not accepted here - enrich the company by `linkedin_url` first, then filter by the `id` that comes back. Max 500 items. Example: `[162479]`
`exclude`	integer[]	Reject these LinkedIn companies. LinkedIn's numeric company id. Company URLs are not accepted here - enrich the company by `linkedin_url` first, then filter by the `id` that comes back. Max 500 items.

Example

{
  "filters": {
    "company": {
      "name": {
        "include": [
          "Intercom",
          "Stripe"
        ]
      }
    }
  }
}

company_industryobjectoptional

Filter on the industry of the person's company for People Search: include or exclude industries or whole industry groups.

Field	Type	Description
`include`	string[]	Industries or industry GROUPS to match (any of). A group name matches every industry in that category. See Industries for both. Example: `["Agriculture & Mining","Software Development"]`
`exclude`	string[]	Industries or industry GROUPS to reject. A group name rejects every industry in that category. See Industries for both.

Example

{
  "filters": {
    "company_industry": {
      "include": [
        "Software Development",
        "IT Services & IT Consulting"
      ],
      "exclude": [
        "Staffing & Recruiting"
      ]
    }
  }
}

company_headcount_rangeenum[]optional

Bucketed headcount range of the company (see Employee ranges).

Example

{
  "filters": {
    "company_headcount_range": [
      "51-200",
      "201-500"
    ]
  }
}

company_countryobjectoptional

Filter on the country of the person's company for People Search: include or exclude ISO alpha-2 codes, optionally headquarters only.

Field	Type	Description
`include`	string[]	Match values in this list - any single value qualifies (exact, case-insensitive). Optional - provide include and/or exclude.
`exclude`	string[]	Reject values in this list. 0-500 items.
`headquarters_only`	boolean	When true, match the company headquarters country only. When false (default), any office country we have resolved counts, headquarters included: includes widen (a company with an office there matches) and excludes tighten symmetrically (a company with an office there is rejected). default: false.

Example

{
  "filters": {
    "company_country": {
      "include": [
        "US",
        "CA",
        "GB"
      ],
      "headquarters_only": true
    }
  }
}

company_typeobjectoptional

Include/exclude filter on company type (Company types), shared by company_type in People Search and Company Search.

Field	Type	Description
`include`	enum[]	Company types to match (any of). Allowed values: `Privately Held` `Public Company` `Non Profit` `Self Owned` `Self Employed` `Partnership` `Educational` `Government Agency` `Unknown`
`exclude`	enum[]	Company types to reject. Allowed values: `Privately Held` `Public Company` `Non Profit` `Self Owned` `Self Employed` `Partnership` `Educational` `Government Agency` `Unknown`

Example

{
  "filters": {
    "company_type": {
      "include": [
        "Privately Held",
        "Public Company"
      ]
    }
  }
}

company_business_typeobjectoptional
Include/exclude filter on business type (Business types), shared by company_business_type in People Search and Company Search.
Field Type Description
include enum[] Business types to match (any of).
Allowed values: B2B B2C Nonprofit Unknown
exclude enum[] Business types to reject.
Allowed values: B2B B2C Nonprofit Unknown
Example
```
{
  "filters": {
    "company_business_type": {
      "include": [
        "B2B"
      ]
    }
  }
}
```

Field	Type	Description
`include`	enum[]	Business types to match (any of). Allowed values: `B2B` `B2C` `Nonprofit` `Unknown`
`exclude`	enum[]	Business types to reject. Allowed values: `B2B` `B2C` `Nonprofit` `Unknown`

company_revenue_streamobjectoptional

Include/exclude filter on revenue stream (Revenue streams), shared by company_revenue_stream in People Search and Company Search.

Field	Type	Description
`include`	enum[]	Revenue streams to match (any of). Allowed values: `Professional Services` `Product Sales` `Grants / Donations` `Subscriptions / Recurring` `Project / Contract Work` `Event / Experience Revenue` `Transaction Fees` `Rental / Leasing` `Advertising` `Financial Services` `Licensing / IP` `Unknown`
`exclude`	enum[]	Revenue streams to reject. Allowed values: `Professional Services` `Product Sales` `Grants / Donations` `Subscriptions / Recurring` `Project / Contract Work` `Event / Experience Revenue` `Transaction Fees` `Rental / Leasing` `Advertising` `Financial Services` `Licensing / IP` `Unknown`

Example

{
  "filters": {
    "company_revenue_stream": {
      "include": [
        "Subscriptions / Recurring",
        "Product Sales"
      ]
    }
  }
}

company_ai_industryobjectoptional

Include/exclude filter on the company AI industry (AI Industries), shared by company_ai_industry in People Search and Company Search. Takes an industry group ("Finance and Insurance") or a sub-industry ("Banking and Lending"): a group matches every company in any of its sub-industries. Casing does not matter, and "&" is read as "and".

Field	Type	Description
`include`	enum[]	AI industries to match (any of). A group matches all its sub-industries; a sub-industry matches only itself. Allowed values: `Software and IT` `Healthcare and Life Sciences` `Finance and Insurance` `Energy, Utilities and Environmental Services` `Industrial Manufacturing and Materials` `Real Estate and Construction` `Retail and Consumer Channels` `Transportation and Logistics` `Professional, Business and Legal Services` `Education and Training` `Media, Entertainment and Culture` `Hospitality, Food and Travel Services` `Personal and Home Services` `Agriculture, Forestry and Fisheries` `Automotive, Aerospace and Defense Manufacturing` `Non-Profit, Public Sector and Education (Non-Commercial)` `AI and ML Platforms` `Agriculture and Forestry Software` `Blockchain and Web3` `Carriers and ISPs` `Cloud and Infrastructure Software` `Consumer Software` `Data and Analytics Software` `Developer Tools and Platforms` `Enterprise Software Solutions` `Financial Services Software` `Government and Public Sector Software` `Hardware and Networking` `Healthcare Software` `IoT and Embedded Systems Software` `IT Services and Cybersecurity` `Manufacturing Software` `Metaverse, AR/VR and Other Emerging Platforms` `Quantum Computing Software` `Real Estate and PropTech Software` `Retail and Ecommerce Software` `Security and Identity Software` `Biotechnology and Pharmaceuticals` `Digital Health and Telemedicine` `Hospitals, Clinics and Outpatient Care` `Medical Devices and Diagnostic Equipment` `Medical Testing and Clinical Laboratories` `Mental Health and Rehabilitation Services` `Pharma Distribution and CRO Services` `Banking and Lending` `Capital Markets and Cryptocurrency` `Cryptocurrency and Blockchain Services` `Financial Services Platforms` `Insurance and InsurTech` `Investment Management and WealthTech` `Venture Capital and Private Equity` `Electric Power and Grid Management` `Nuclear and Advanced Generation` `Oil and Gas Exploration, Production and Services` `Renewable Energy and Clean Tech` `Sustainability Tech and Environmental Consulting` `Water, Waste and Environmental Management` `3D Printing and Advanced Manufacturing` `Building Materials and Chemicals` `Consumer Goods and Appliances` `Electronics and Computer Equipment` `Food, Beverage and Tobacco Production` `Industrial Machinery and Equipment` `Mining, Metals and Natural Resources` `Architecture, Urban Planning and Green Building` `Commercial Real Estate Development and Leasing` `Construction and Civil Engineering Services` `Property and Facility Management` `Residential Real Estate Development and Brokerage` `Specialty Construction Products` `Automotive Service and Collision Repair` `Brick-and-Mortar Retail` `Media and Entertainment Retail` `Online Commerce and Marketplaces` `Retail Technology` `Specialty Auctions and Collectibles` `Wholesale and Distribution` `Autonomous Vehicles and Drone Delivery` `Car and Truck Rental` `Freight and Cargo` `Logistics Technology` `Passenger Transit and Mobility` `Warehousing, Fulfillment and 3PL Services` `Accounting, Audit and Financial Advisory` `Advertising, Marketing and Multimedia Design` `Defense and Government Services` `Facilities Management and Commercial Cleaning` `Human Resources, Staffing and Recruitment` `Legal Services and Regulatory Compliance` `Management Consulting and Strategy Consulting` `Translation, Document and Information Management` `Corporate Training and Learning and Development` `E-Learning Platforms and EdTech` `K-12 and Higher Education Institutions` `Test Prep, Tutoring and After-School Services` `Vocational Training and Certification Programs` `Digital Publishing and Streaming Platforms` `Film, Television and Broadcasting` `Gaming, Esports and Interactive Entertainment` `Live Events, Experiences and Ticketed Attractions` `Museums, Art Galleries and Cultural Preservation` `Music, Audio and Podcast Services` `Sports and Recreation` `Food and Beverage Services` `Hospitality and Lodging` `Travel Agencies and Leisure Services` `Funeral Homes and Related Services` `Home Services` `Personal Care and Wellness` `Veterinary Care and Pet Services` `AgriTech and Precision Farming` `Aquaculture and Fisheries` `Crop Farming and Livestock Production` `Farming Equipment and Supplies` `Forestry, Logging and Wood Products` `Mining and Extraction` `Aviation and Aerospace Component Manufacturing` `Automotive and Rental Retail` `Commercial Space Innovation` `Defense Systems and Marine Manufacturing` `Motor Vehicle and Parts Manufacturing` `Government Administration and Municipal Services` `NGOs, Charities and Community Organizations` `Public Healthcare and Social Services` `Public/Private Research Institutions and Educational Foundations` `Student Organizations and Campus Services`
`exclude`	enum[]	AI industries to reject. A group rejects all its sub-industries; a sub-industry rejects only itself. Allowed values: `Software and IT` `Healthcare and Life Sciences` `Finance and Insurance` `Energy, Utilities and Environmental Services` `Industrial Manufacturing and Materials` `Real Estate and Construction` `Retail and Consumer Channels` `Transportation and Logistics` `Professional, Business and Legal Services` `Education and Training` `Media, Entertainment and Culture` `Hospitality, Food and Travel Services` `Personal and Home Services` `Agriculture, Forestry and Fisheries` `Automotive, Aerospace and Defense Manufacturing` `Non-Profit, Public Sector and Education (Non-Commercial)` `AI and ML Platforms` `Agriculture and Forestry Software` `Blockchain and Web3` `Carriers and ISPs` `Cloud and Infrastructure Software` `Consumer Software` `Data and Analytics Software` `Developer Tools and Platforms` `Enterprise Software Solutions` `Financial Services Software` `Government and Public Sector Software` `Hardware and Networking` `Healthcare Software` `IoT and Embedded Systems Software` `IT Services and Cybersecurity` `Manufacturing Software` `Metaverse, AR/VR and Other Emerging Platforms` `Quantum Computing Software` `Real Estate and PropTech Software` `Retail and Ecommerce Software` `Security and Identity Software` `Biotechnology and Pharmaceuticals` `Digital Health and Telemedicine` `Hospitals, Clinics and Outpatient Care` `Medical Devices and Diagnostic Equipment` `Medical Testing and Clinical Laboratories` `Mental Health and Rehabilitation Services` `Pharma Distribution and CRO Services` `Banking and Lending` `Capital Markets and Cryptocurrency` `Cryptocurrency and Blockchain Services` `Financial Services Platforms` `Insurance and InsurTech` `Investment Management and WealthTech` `Venture Capital and Private Equity` `Electric Power and Grid Management` `Nuclear and Advanced Generation` `Oil and Gas Exploration, Production and Services` `Renewable Energy and Clean Tech` `Sustainability Tech and Environmental Consulting` `Water, Waste and Environmental Management` `3D Printing and Advanced Manufacturing` `Building Materials and Chemicals` `Consumer Goods and Appliances` `Electronics and Computer Equipment` `Food, Beverage and Tobacco Production` `Industrial Machinery and Equipment` `Mining, Metals and Natural Resources` `Architecture, Urban Planning and Green Building` `Commercial Real Estate Development and Leasing` `Construction and Civil Engineering Services` `Property and Facility Management` `Residential Real Estate Development and Brokerage` `Specialty Construction Products` `Automotive Service and Collision Repair` `Brick-and-Mortar Retail` `Media and Entertainment Retail` `Online Commerce and Marketplaces` `Retail Technology` `Specialty Auctions and Collectibles` `Wholesale and Distribution` `Autonomous Vehicles and Drone Delivery` `Car and Truck Rental` `Freight and Cargo` `Logistics Technology` `Passenger Transit and Mobility` `Warehousing, Fulfillment and 3PL Services` `Accounting, Audit and Financial Advisory` `Advertising, Marketing and Multimedia Design` `Defense and Government Services` `Facilities Management and Commercial Cleaning` `Human Resources, Staffing and Recruitment` `Legal Services and Regulatory Compliance` `Management Consulting and Strategy Consulting` `Translation, Document and Information Management` `Corporate Training and Learning and Development` `E-Learning Platforms and EdTech` `K-12 and Higher Education Institutions` `Test Prep, Tutoring and After-School Services` `Vocational Training and Certification Programs` `Digital Publishing and Streaming Platforms` `Film, Television and Broadcasting` `Gaming, Esports and Interactive Entertainment` `Live Events, Experiences and Ticketed Attractions` `Museums, Art Galleries and Cultural Preservation` `Music, Audio and Podcast Services` `Sports and Recreation` `Food and Beverage Services` `Hospitality and Lodging` `Travel Agencies and Leisure Services` `Funeral Homes and Related Services` `Home Services` `Personal Care and Wellness` `Veterinary Care and Pet Services` `AgriTech and Precision Farming` `Aquaculture and Fisheries` `Crop Farming and Livestock Production` `Farming Equipment and Supplies` `Forestry, Logging and Wood Products` `Mining and Extraction` `Aviation and Aerospace Component Manufacturing` `Automotive and Rental Retail` `Commercial Space Innovation` `Defense Systems and Marine Manufacturing` `Motor Vehicle and Parts Manufacturing` `Government Administration and Municipal Services` `NGOs, Charities and Community Organizations` `Public Healthcare and Social Services` `Public/Private Research Institutions and Educational Foundations` `Student Organizations and Campus Services`

Example

{
  "filters": {
    "company_ai_industry": {
      "include": [
        "Finance and Insurance"
      ],
      "exclude": [
        "Banking and Lending"
      ]
    }
  }
}

company_foundedobjectoptional
An inclusive numeric range (min / max, either optional), used by the People Search company founded-year and headcount filters.
Field Type Description
min number Lower bound (inclusive). Optional.
max number Upper bound (inclusive). Must be >= min. Optional.
Example
```
{
  "filters": {
    "company_founded": {
      "min": 2015,
      "max": 2023
    }
  }
}
```
company_headcount_customobjectoptional
An inclusive numeric range (min / max, either optional), used by the People Search company founded-year and headcount filters.
Field Type Description
min number Lower bound (inclusive). Optional.
max number Upper bound (inclusive). Must be >= min. Optional.
Example
```
{
  "filters": {
    "company_headcount_custom": {
      "min": 50,
      "max": 1000
    }
  }
}
```

Field	Type	Description
`min`	number	Lower bound (inclusive). Optional.
`max`	number	Upper bound (inclusive). Must be >= min. Optional.

Field	Type	Description
`min`	number	Lower bound (inclusive). Optional.
`max`	number	Upper bound (inclusive). Must be >= min. Optional.

company_naicsobjectoptional

Include or exclude a list of numeric values, used by the People Search company_naics filter.

Field	Type	Description
`include`	number[]	Match numeric values in this list - any single value qualifies. Optional - provide include and/or exclude.
`exclude`	number[]	Reject numeric values in this list. 0-500 items.

Example

{
  "filters": {
    "company_naics": {
      "include": [
        541511,
        541512
      ]
    }
  }
}

company_locationobjectoptional

Company location filter on unified location strings plus headquarters_only, shared by company_location in People Search and Company Search.

Field	Type	Description
`include`	string[]	Match these locations (any of). Unified strings like "United States", "Texas, United States", "San Francisco, California, United States" - or a region like "EMEA", "APAC", "Europe", "Latin America", which expands to its member countries (full list with member countries: GET /v2/enums/regions). Max 100 items, each 2-200 chars. If none of the values resolve to a known location, the request fails with 400.
`exclude`	string[]	Reject these locations (same unified-string format). Max 100 items, each 2-200 chars. Values that do not resolve are skipped.
`headquarters_only`	boolean	When true, match the company headquarters location only. When false (default), any office location we have resolved counts, headquarters included: includes widen (a company with an office there matches) and excludes tighten symmetrically (a company with an office there is rejected). default: false.

Example

{
  "filters": {
    "company_location": {
      "include": [
        "San Francisco, California, United States"
      ],
      "headquarters_only": true
    }
  }
}

company_technologiesobjectoptional

Filter on technologies detected on the company website, by suggest id, shared by company_technologies in People Search and Company Search.

Field	Type	Description
`include`	string[]	Technology ids to match. `match_mode: ANY` (default): a company using any of them qualifies; `ALL`: it must use every one. Max 500. Example: `["3421"]`
`exclude`	string[]	Reject companies using any of these technology ids. Max 500.
`match_mode`	enum	How `include` combines: `ANY` (default) - at least one; `ALL` - every one, on the same company. Allowed values: `ANY` `ALL`

Example

{
  "filters": {
    "company_technologies": {
      "include": [
        "3421"
      ]
    }
  }
}

company_technology_categoriesobjectoptional
Filter on technology categories, by suggest id, shared by company_technology_categories in People Search and Company Search.
Field Type Description
include string[] Category ids to match (any of). Max 200.
Example: ["1"]
exclude string[] Reject companies using any technology in these category ids. Max 200.
Example
```
{
  "filters": {
    "company_technology_categories": {
      "include": [
        "1"
      ]
    }
  }
}
```

Field	Type	Description
`include`	string[]	Category ids to match (any of). Max 200. Example: `["1"]`
`exclude`	string[]	Reject companies using any technology in these category ids. Max 200.

contact_detailsobjectoptional

Filter for People Search on contact data: email and phone status, and whether your workspace already revealed them.

Child attributes

emailobjectoptional

Email part of the People Search contact_details filter: the email status to match and whether your workspace revealed it.

Field	Type	Description
`status`	enum[]	Contact-level email status (best stored email; valid wins). Match-any: valid (>=1 valid email, or an email your workspace entered for the person), invalid, accept_all, not_found (no stored email and none entered by your workspace). Allowed values: `valid` `invalid` `accept_all` `not_found`
`revealed`	boolean	true = only contacts whose email your workspace already revealed; false = only those NOT revealed. Requires an authenticated workspace.

phoneobjectoptional

Phone part of the People Search contact_details filter: the phone status to match and whether your workspace revealed it.

Field	Type	Description
`status`	enum[]	Contact-level phone status from our lookup store. Match-any: found (number on file), not_found (looked up, none), unknown (never looked up). Allowed values: `found` `not_found` `unknown`
`revealed`	boolean	true = only contacts whose phone your workspace already revealed; false = only those NOT revealed. Requires an authenticated workspace.

Example

{
  "filters": {
    "contact_details": {
      "email": {
        "status": [
          "valid",
          "accept_all"
        ],
        "revealed": false
      },
      "phone": {
        "status": [
          "found"
        ]
      }
    }
  }
}

listsobjectoptional
Filter for People Search on your workspace's saved people: list membership, saved or not, and when they were saved.
Child attributes
- includestring[]optional
  Only contacts your workspace saved into these list ids. Max 100 ids, each 1-64 chars.
- excludestring[]optional
  Hide contacts your workspace saved into these list ids. Max 1000 ids, each 1-64 chars.
- savedenumoptional
  any = only contacts your workspace saved, in a list or not; none = only contacts your workspace has not saved; without_list = only contacts your workspace saved but did not file into any list.
  Allowed values: any none without_list
- saved_atobjectoptional
  An inclusive date range (ISO 8601 from / to) for when a person was saved, used by the People Search lists.saved_at filter.
  Field Type Description
  from string Saved on/after this date (ISO 8601). Optional.
  to string Saved on/before this date (ISO 8601). Optional.
Example
```
{
  "filters": {
    "person_job_title": {
      "include": [
        "Product Marketing Manager"
      ]
    },
    "lists": {
      "saved": "none"
    }
  }
}
```

Field	Type	Description
`from`	string	Saved on/after this date (ISO 8601). Optional.
`to`	string	Saved on/before this date (ISO 8601). Optional.

duplicatesobjectoptional

Filter for People Search that hides people your workspace already exported through POST /v2/people/export.

Field	Type	Description
`exclude_exported`	boolean	true = hide people your workspace already exported through POST /v2/people/export. Exclude-only: it removes rows and never counts as an include condition. Requires an authenticated workspace.

Example

{
  "filters": {
    "duplicates": {
      "exclude_exported": true
    }
  }
}

max_person_per_companyintegeroptionalmin: 1max: 100
Cap the number of people returned per company across the whole result set (1-100). A person is counted against the company of the position that matched your company filters, or their current/primary position when no company filter is set. Of the colleagues competing for a company slot, one we hold a valid email for is kept, and your sort decides between them (and picks the representative outright when none of them has one). Results stay in your sort order either way. For result sets above 25000 matches the representative is simply whoever leads your sort, and total_count is a rounded PRE-cap estimate (pagination.total_is_estimate=true) - an upper bound, so an export of that selection returns fewer people. At or below it both are exact.
Example
```
{
  "filters": {
    "person_job_title": {
      "include": [
        "Product Marketing Manager"
      ]
    },
    "max_person_per_company": 2
  }
}
```

Responses

200 The suggested titles; an empty titles when there is nothing to add (still a 200).
400 Invalid request (VALIDATION_ERROR, payload.code says which kind): job_titles empty or too long, or filters that People Search itself would refuse.
401 Missing, unknown or inactive credentials (UNAUTHORIZED).
429 Either the per-second window of the search rate limit (RATE_LIMIT; this route spends no units), or the workspace used today's allowance of new AI suggestions (RATE_LIMIT with payload.code: ai_daily_limit, resets at 00:00 UTC; cached answers stay free).
500 Unexpected server error.
503 The AI could not answer right now (UNAVAILABLE); retry shortly, or search with match_mode CONTAINS.

For error handling see Errors. Response objects are described in Person object and Company object.

curl --request POST \
  --url https://api.getprospect.com/v2/search/smart-job-titles \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: YOUR_API_KEY' \
  --data '
{
  "job_titles": [
    "Head of Procurement"
  ],
  "exclude_job_titles": [
    "Intern"
  ],
  "filters": {
    "person_location": {
      "include": [
        "Germany"
      ]
    }
  }
}
'

Response

{
  "success": true,
  "data": {
    "intent": "Senior procurement leaders in Germany",
    "titles": [
      {
        "title": "Leiter Einkauf",
        "level": "SAME_ROLE",
        "new_people": 2615
      },
      {
        "title": "Head of Purchasing",
        "level": "SAME_ROLE",
        "new_people": 2093
      },
      {
        "title": "Purchasing Director",
        "level": "SIMILAR",
        "new_people": 1635
      },
      {
        "title": "Chief Procurement Officer",
        "level": "SIMILAR",
        "new_people": 161
      },
      {
        "title": "Purchasing Manager",
        "level": "RELATED",
        "new_people": 9827
      }
    ],
    "exclude_titles": [
      {
        "title": "Praktikant",
        "removed_people": 41
      },
      {
        "title": "Praktikantin",
        "removed_people": 12
      },
      {
        "title": "Trainee",
        "removed_people": 0
      }
    ]
  },
  "metadata": {
    "timestamp": "2026-11-04T09:30:00.000Z",
    "cached": false
  }
}