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POST
/
companies
/
search
Search for companies
curl --request POST \
  --url https://api.pubrio.com/companies/search \
  --header 'Content-Type: application/json' \
  --header 'pubrio-api-key: <api-key>' \
  --data '
{
  "company_name": "pubrio",
  "companies": [
    "3c90c3cc-0d44-4b50-8888-8dd25736052a"
  ],
  "domains": [
    "pubrio.com"
  ],
  "linkedin_urls": [
    "https://www.linkedin.com/company/pubrio"
  ],
  "locations": [
    "US",
    "SG",
    "CN"
  ],
  "exclude_locations": [
    "CN",
    "US",
    "RU",
    "CA"
  ],
  "places": [
    "Tokyo"
  ],
  "exclude_places": [
    "Tokyo"
  ],
  "job_locations": [
    "US",
    "SG",
    "CN"
  ],
  "job_exclude_locations": [
    "CN",
    "US",
    "RU",
    "CA"
  ],
  "job_posted_dates": [
    "2025-01-01",
    "2025-01-10"
  ],
  "job_titles": [
    "sales manager",
    "marketing manager"
  ],
  "verticals": [
    123
  ],
  "vertical_categories": [
    123
  ],
  "vertical_sub_categories": [
    123
  ],
  "categories": [
    123
  ],
  "technologies": [
    123
  ],
  "employees": [
    [
      1,
      10
    ],
    [
      11,
      20
    ],
    [
      10001
    ]
  ],
  "revenues": [
    0,
    100000
  ],
  "founded_dates": [
    2018,
    2024
  ],
  "keywords": [
    "ecommerce",
    "ai",
    "fintech"
  ],
  "news_categories": [
    "launches"
  ],
  "news_published_dates": [
    "2025-01-01",
    "2025-01-10"
  ],
  "advertisement_search_terms": [
    "asus"
  ],
  "advertisement_target_locations": [
    "TW",
    "AE",
    "NO"
  ],
  "advertisement_exclude_target_locations": [
    "IS",
    "GB",
    "FR",
    "IE",
    "ES"
  ],
  "advertisement_start_dates": [
    "2025-12-25",
    "2025-12-25"
  ],
  "advertisement_end_dates": [
    "2025-12-25",
    "2025-12-25"
  ],
  "filter_conditions": [
    {
      "key": "keywords",
      "operator": "or"
    }
  ],
  "is_enable_similarity_search": true,
  "similarity_score": 0.7,
  "exclude_fields": [
    "emails",
    "phones",
    "contacts"
  ],
  "is_parameter_metadata_available": true,
  "is_profile_metadata_available": true,
  "per_page": 25,
  "page": 1,
  "profile_id": 123
}
'
{
  "data": {
    "pagination": {
      "page": 1,
      "per_page": 25,
      "total_entries": 45234700,
      "total_pages": 1809388
    },
    "companies": [
      {
        "logo_url": "https://buckets.pubrio.com/company-logo/MjI0NDc1OTMxaWxqOXNzbmoxdHdpdHRlci5jb20=.jpg",
        "company_name": "Twitter",
        "emails": [
          "..."
        ],
        "phones": [
          "..."
        ],
        "contacts": [
          "..."
        ],
        "founded_year": 2006,
        "specialties": [
          "Software Development"
        ],
        "industry": "Software Development",
        "domain": "twitter.com",
        "domain_search_id": "61a73da7-2efc-41a5-a252-a8a8df29925a",
        "domain_id": 224475931,
        "linkedin_company_id": 44005587,
        "linkedin_name": "twitter",
        "is_company_url_active": true,
        "domain_ids": [
          224475931,
          1758889566,
          368242865
        ],
        "company_keywords": [
          "realtime information",
          "social commerce",
          "online shopping",
          "classifieds",
          "craigslist killers",
          "e-commerce",
          "killers",
          "consumer internet",
          "internet",
          "information technology",
          "edp services",
          "technology",
          "software development",
          "microblogging",
          "social networking",
          "public conversation",
          "user engagement",
          "content sharing",
          "advertising solutions",
          "monetization",
          "community building",
          "digital wallet",
          "ai integration",
          "user safety"
        ],
        "company_size": 1500,
        "youtube_url": null,
        "crunchbase_url": null,
        "linkedin_url": "http://www.linkedin.com/company/twitter",
        "instagram_url": null,
        "facebook_url": "http://facebook.com/twitterinc",
        "twitter_url": "https://twitter.com/x",
        "github_url": null,
        "x_url": null,
        "location": "United States",
        "company_ranking": null,
        "company_url": "http://twitter.com",
        "saved_lists": null,
        "company_size_printed": "1,500"
      },
      "..."
    ]
  }
}

Authorizations

​
pubrio-api-key
string
header
required

A unique API token that represents the actions you perform through the API and the corresponding permissions and operations. You can create it through the Settings section.

Body

application/json
​
company_name
string

Filter search results to include a specific company name.

If the value you enter for this parameter does not match with a company's name, the company will not appear in search results, even if it matches other parameters. Partial matches are accepted.

Example:

"pubrio"

​
companies
string<uuid>[]

A list of unique identifiers (domain_search_id) used for company and people search operations.

​
domains
string[]

List of company domains used for company and people search operations. If we receive a URL such as www.pubrio.com or https://docs.pubrio.com/, the system will convert it to pubrio.com for processing.

Example:
["pubrio.com"]
​
linkedin_urls
string[]

The fully formed URL of the LinkedIn company profile. URL begin with http and contain linkedin.com/company/

Example:
["https://www.linkedin.com/company/pubrio"]
​
locations
string[]

ISO 3166-1 alpha-2 (cca2) is used for filtering locations. Check out location endpoints under the Filters tab for more information.

Example:
["US", "SG", "CN"]
​
exclude_locations
string[]

ISO 3166-1 alpha-2 (cca2) is used to filter out locations that does not need to be returned. Check out location endpoints under the Filters tab for more information.

Example:
["CN", "US", "RU", "CA"]
​
places
string[]

Place names (city, region) used to filter results. Accepts localized or English place names.

Example:
["Tokyo"]
​
exclude_places
string[]

Place names (city, region) to exclude from results. Accepts localized or English place names.

Example:
["Tokyo"]
​
job_locations
string[]

ISO 3166-1 alpha-2 (cca2) is used for filtering locations. Check out location endpoints under the Filters tab for more information.

Example:
["US", "SG", "CN"]
​
job_exclude_locations
string[]

Geographic locations to exclude from job posting results.

Example:
["CN", "US", "RU", "CA"]
​
job_posted_dates
string[]

Date range of the posted date. The maximum value is the current day.

Example:
["2025-01-01", "2025-01-10"]
​
job_titles
string[]

Job titles associated with the individuals you aim to locate.

The results will also encompass job titles that include similar terminology, even if they do not match exactly. For instance, searching for software engineer may yield results for individuals with the title senior software engineer.

Example:
["sales manager", "marketing manager"]
​
verticals
integer[]

A list of vertical_id used to search for companies in a specific vertical or industry. To find the ID, call the vertical endpoint under the Filters tab.

This filter supports is_enable_similarity_search, once enabled you can enter any free text, e.g. ["AI"].

​
vertical_categories
integer[]

A list of vertical_category_id used to search for companies in a specific vertical category. To find the ID, call the vertical category endpoint under the Filters tab.

This filter supports is_enable_similarity_search, once enabled you can enter any free text, e.g. ["Information Technology"].

​
vertical_sub_categories
integer[]

A list of vertical_sub_category_id used to search for companies in a specific vertical sub-category. To find the ID, call the vertical sub category endpoint under the Filters tab.

This filter supports is_enable_similarity_search, once enabled you can enter any free text, e.g. ["Software"].

​
categories
integer[]

A list of category_id used to search for specific categories of technology used by companies. To find the ID, call the category endpoint under the Filters tab.

This filter supports is_enable_similarity_search, once enabled you can enter any free text, e.g. ["CDN"].

​
technologies
integer[]

A list of tag_id used to search for specific technologies used by companies. To find the ID, call the technology endpoint under the Filters tab.

This filter supports is_enable_similarity_search, once enabled you can enter any free text, e.g. ["Shopify"].

​
employees
string[][]

The number range of employees working for the company. This enables you to find companies based on headcount. You can add multiple ranges to expand your search results.

Check out company size endpoints under the Filters tab for more information.

Example:
[[1, 10], [11, 20], [10001]]
​
revenues
integer[]

Minimum and maximum range of company revenue.

Example:
[0, 100000]
​
founded_dates
integer[]

Years of company founded range. The maximum value founded is the current year.

Example:
[2018, 2024]
​
keywords
string[]

A list of keywords to filter companies by relevance, specialties, or descriptions.

Example:
["ecommerce", "ai", "fintech"]
​
news_categories
string[]

List of category slugs for searching for specific news categories. To find a slug, call the news categories endpoint under the Filters tab.

Example:
["launches"]
​
news_published_dates
string[]

Date range of the published date. The maximum value is the current day.

Example:
["2025-01-01", "2025-01-10"]
​
advertisement_search_terms
string[]

Keywords used to search within advertisement content or titles.

Example:
["asus"]
​
advertisement_target_locations
string[]

Target geographic locations for advertisements.

Example:
["TW", "AE", "NO"]
​
advertisement_exclude_target_locations
string[]

Geographic locations to exclude from advertisement targeting.

Example:
["IS", "GB", "FR", "IE", "ES"]
​
advertisement_start_dates
string<date>[]

Start date range for advertisement filtering.

Example:
["2025-12-25", "2025-12-25"]
​
advertisement_end_dates
string<date>[]

End date range for advertisement filtering.

Example:
["2025-12-25", "2025-12-25"]
​
filter_conditions
object[]

Advanced filtering options for company searches. Specify conditions combining keys and logical operators to refine search results.

​
is_enable_similarity_search
boolean

When enabled, the filters listed above that support similarity searches can be filled with free text for specific IDs.

​
similarity_score
number<float>

It is used in conjunction with is_enable_similarity_search. This number is used to analyze whether a specific slug (e.g. vertical industry, technology) is similar to the user input, and the higher the number, the more stringent it is.

Example:

0.7

​
exclude_fields
string[]

List of fields to exclude from the response payload.

Example:
["emails", "phones", "contacts"]
​
is_parameter_metadata_available
boolean

Indicates whether parameter metadata is available for the request.

​
is_profile_metadata_available
boolean

Indicates whether profile metadata is available for the request.

​
per_page
integer

The number of search results that should be returned for each page. Limited the number of results per page improves the endpoint's performance.

Example:

25

​
page
integer

The page number of the Pubrio data that you want to retrieve.

Example:

1

​
profile_id
integer

Optional. An identifier for the user profile (workspace) making the request. This is no longer required as the API key already includes your workspace information. If provided, it helps in associating the lookup with a specific user, allowing for data retrieval and credit tracking.

Check out user details endpoints under the Profile tab for more information.

Response

Successful response containing company search details.

​
data
object

Response info depends on specific endpoint.