Search Company

curl -X POST https://api.dataforb2b.ai/search/companies \
  -H "api_key: YOUR_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "filters": {
      "op": "and",
      "conditions": [
        {"column": "industry", "type": "like", "value": "Technology"},
        {"column": "country_iso_code", "type": "=", "value": "US"}
      ]
    },
    "count": 10
  }'

import requests

response = requests.post(
    "https://api.dataforb2b.ai/search/companies",
    headers={
        "api_key": "YOUR_api_key",
        "Content-Type": "application/json"
    },
    json={
        "filters": {
            "op": "and",
            "conditions": [
                {"column": "industry", "type": "like", "value": "Technology"},
                {"column": "country_iso_code", "type": "=", "value": "US"}
            ]
        },
        "count": 10
    }
)

data = response.json()
print(f"Found {data['total']} companies")

const response = await fetch('https://api.dataforb2b.ai/search/companies', {
  method: 'POST',
  headers: {
    'api_key': 'YOUR_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    filters: {
      op: 'and',
      conditions: [
        { column: 'industry', type: 'like', value: 'Technology' },
        { column: 'country_iso_code', type: '=', value: 'US' }
      ]
    },
    count: 10
  })
});

const data = await response.json();
console.log(`Found ${data.total} companies`);

{
  "total": 10000,
  "offset": 0,
  "count": 2,
  "credits_used": 2,
  "results": [
    {
      "id": "org_ABC123xyz",
      "name": "TechCorp Solutions",
      "tagline": "Innovating Tomorrow's Technology Today",
      "description": "TechCorp Solutions is a leading technology company specializing in cloud infrastructure and enterprise software solutions. We help businesses transform digitally through cutting-edge technology and innovative approaches. Our team of 500+ engineers delivers scalable solutions to Fortune 500 companies worldwide.",
      "industry": "software development",
      "headquarters": {
        "country": "US",
        "city": "San Francisco",
        "region": "California"
      },
      "founded_year": 2015,
      "company_type": "PRIVATELY_HELD",
      "logo_url": "https://media.licdn.com/dms/image/...",
      "links": {
        "website": "https://www.techcorp.com",
        "instagram": "https://instagram.com/techcorp",
        "facebook": "https://facebook.com/techcorp",
        "twitter": "https://twitter.com/techcorp",
        "youtube": "https://youtube.com/techcorp",
        "tiktok": null,
        "github": "https://github.com/techcorp",
        "behance": null,
        "spotify": null,
        "whatsapp": null,
        "telegram": null,
        "linktree": null,
        "other": null,
        "linkedin": "https://www.linkedin.com/company/techcorp-solutions"
      },
      "size": {
        "employees": 520,
        "range_min": 501,
        "range_max": 1000
      },
      "metrics": {
        "followers": 25000,
        "active_jobs": 45
      },
      "signals": {
        "verified": true
      },
      "categories": [
        "software",
        "cloud computing",
        "enterprise software"
      ],
      "locations": [
        {
          "country": "US",
          "city": "San Francisco",
          "region": "California",
          "is_headquarters": true
        },
        {
          "country": "US",
          "city": "New York",
          "region": "New York",
          "is_headquarters": false
        },
        {
          "country": "GB",
          "city": "London",
          "region": "England",
          "is_headquarters": false
        }
      ],
      "funding": {
        "last_round_amount_usd": 45000000,
        "last_round_date": "2023-06-15",
        "total_raised_usd": 85000000
      },
      "growth": {
        "percent_1m": 3.2,
        "percent_6m": 18.5,
        "percent_12m": 45.8,
        "recent_hires": 28
      }
    },
    {
      "id": "org_DEF456abc",
      "name": "DataAnalytics Pro",
      "tagline": "Empowering Data-Driven Decisions",
      "description": "DataAnalytics Pro provides advanced analytics and business intelligence solutions for mid-market companies. Our platform helps organizations unlock insights from their data through AI-powered analytics, real-time dashboards, and predictive modeling.",
      "industry": "software development",
      "headquarters": {
        "country": "US",
        "city": "Austin",
        "region": "Texas"
      },
      "founded_year": 2019,
      "company_type": "PRIVATELY_HELD",
      "logo_url": "https://media.licdn.com/dms/image/...",
      "links": {
        "website": "https://www.dataanalyticspro.com",
        "instagram": null,
        "facebook": null,
        "twitter": "https://twitter.com/dataanalyticspro",
        "youtube": null,
        "tiktok": null,
        "github": null,
        "behance": null,
        "spotify": null,
        "whatsapp": null,
        "telegram": null,
        "linktree": null,
        "other": null,
        "linkedin": "https://www.linkedin.com/company/dataanalytics-pro"
      },
      "size": {
        "employees": 85,
        "range_min": 51,
        "range_max": 200
      },
      "metrics": {
        "followers": 4200,
        "active_jobs": 12
      },
      "signals": {
        "verified": false
      },
      "categories": [
        "Analytics",
        "Business Intelligence",
        "Data Science"
      ],
      "locations": [
        {
          "country": "US",
          "city": "Austin",
          "region": "Texas",
          "is_headquarters": true
        }
      ],
      "funding": {
        "last_round_amount_usd": 12000000,
        "last_round_date": "2022-09-12",
        "total_raised_usd": 15000000
      },
      "growth": {
        "percent_1m": 5.6,
        "percent_6m": 25.0,
        "percent_12m": 70.0,
        "recent_hires": 15
      }
    }
  ]
}

POST

companies

curl -X POST https://api.dataforb2b.ai/search/companies \
  -H "api_key: YOUR_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "filters": {
      "op": "and",
      "conditions": [
        {"column": "industry", "type": "like", "value": "Technology"},
        {"column": "country_iso_code", "type": "=", "value": "US"}
      ]
    },
    "count": 10
  }'

import requests

response = requests.post(
    "https://api.dataforb2b.ai/search/companies",
    headers={
        "api_key": "YOUR_api_key",
        "Content-Type": "application/json"
    },
    json={
        "filters": {
            "op": "and",
            "conditions": [
                {"column": "industry", "type": "like", "value": "Technology"},
                {"column": "country_iso_code", "type": "=", "value": "US"}
            ]
        },
        "count": 10
    }
)

data = response.json()
print(f"Found {data['total']} companies")

const response = await fetch('https://api.dataforb2b.ai/search/companies', {
  method: 'POST',
  headers: {
    'api_key': 'YOUR_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    filters: {
      op: 'and',
      conditions: [
        { column: 'industry', type: 'like', value: 'Technology' },
        { column: 'country_iso_code', type: '=', value: 'US' }
      ]
    },
    count: 10
  })
});

const data = await response.json();
console.log(`Found ${data.total} companies`);

{
  "total": 10000,
  "offset": 0,
  "count": 2,
  "credits_used": 2,
  "results": [
    {
      "id": "org_ABC123xyz",
      "name": "TechCorp Solutions",
      "tagline": "Innovating Tomorrow's Technology Today",
      "description": "TechCorp Solutions is a leading technology company specializing in cloud infrastructure and enterprise software solutions. We help businesses transform digitally through cutting-edge technology and innovative approaches. Our team of 500+ engineers delivers scalable solutions to Fortune 500 companies worldwide.",
      "industry": "software development",
      "headquarters": {
        "country": "US",
        "city": "San Francisco",
        "region": "California"
      },
      "founded_year": 2015,
      "company_type": "PRIVATELY_HELD",
      "logo_url": "https://media.licdn.com/dms/image/...",
      "links": {
        "website": "https://www.techcorp.com",
        "instagram": "https://instagram.com/techcorp",
        "facebook": "https://facebook.com/techcorp",
        "twitter": "https://twitter.com/techcorp",
        "youtube": "https://youtube.com/techcorp",
        "tiktok": null,
        "github": "https://github.com/techcorp",
        "behance": null,
        "spotify": null,
        "whatsapp": null,
        "telegram": null,
        "linktree": null,
        "other": null,
        "linkedin": "https://www.linkedin.com/company/techcorp-solutions"
      },
      "size": {
        "employees": 520,
        "range_min": 501,
        "range_max": 1000
      },
      "metrics": {
        "followers": 25000,
        "active_jobs": 45
      },
      "signals": {
        "verified": true
      },
      "categories": [
        "software",
        "cloud computing",
        "enterprise software"
      ],
      "locations": [
        {
          "country": "US",
          "city": "San Francisco",
          "region": "California",
          "is_headquarters": true
        },
        {
          "country": "US",
          "city": "New York",
          "region": "New York",
          "is_headquarters": false
        },
        {
          "country": "GB",
          "city": "London",
          "region": "England",
          "is_headquarters": false
        }
      ],
      "funding": {
        "last_round_amount_usd": 45000000,
        "last_round_date": "2023-06-15",
        "total_raised_usd": 85000000
      },
      "growth": {
        "percent_1m": 3.2,
        "percent_6m": 18.5,
        "percent_12m": 45.8,
        "recent_hires": 28
      }
    },
    {
      "id": "org_DEF456abc",
      "name": "DataAnalytics Pro",
      "tagline": "Empowering Data-Driven Decisions",
      "description": "DataAnalytics Pro provides advanced analytics and business intelligence solutions for mid-market companies. Our platform helps organizations unlock insights from their data through AI-powered analytics, real-time dashboards, and predictive modeling.",
      "industry": "software development",
      "headquarters": {
        "country": "US",
        "city": "Austin",
        "region": "Texas"
      },
      "founded_year": 2019,
      "company_type": "PRIVATELY_HELD",
      "logo_url": "https://media.licdn.com/dms/image/...",
      "links": {
        "website": "https://www.dataanalyticspro.com",
        "instagram": null,
        "facebook": null,
        "twitter": "https://twitter.com/dataanalyticspro",
        "youtube": null,
        "tiktok": null,
        "github": null,
        "behance": null,
        "spotify": null,
        "whatsapp": null,
        "telegram": null,
        "linktree": null,
        "other": null,
        "linkedin": "https://www.linkedin.com/company/dataanalytics-pro"
      },
      "size": {
        "employees": 85,
        "range_min": 51,
        "range_max": 200
      },
      "metrics": {
        "followers": 4200,
        "active_jobs": 12
      },
      "signals": {
        "verified": false
      },
      "categories": [
        "Analytics",
        "Business Intelligence",
        "Data Science"
      ],
      "locations": [
        {
          "country": "US",
          "city": "Austin",
          "region": "Texas",
          "is_headquarters": true
        }
      ],
      "funding": {
        "last_round_amount_usd": 12000000,
        "last_round_date": "2022-09-12",
        "total_raised_usd": 15000000
      },
      "growth": {
        "percent_1m": 5.6,
        "percent_6m": 25.0,
        "percent_12m": 70.0,
        "recent_hires": 15
      }
    }
  ]
}

Credit Cost

Mode	Credits per Result
`enrich_live: true`	1.5 credits
`enrich_live: false`	0.75 credits

Request Body

object

Filter group to apply to the search. See Filters section below.

string

required

Logical operator to combine conditions.

and - All conditions must match
or - At least one condition must match

array

required

Array of filter conditions or nested filter groups.

string

required

Column name to filter on. See Available Columns section below for complete list with data types and recommended operators.Basic Info: name, tagline, description, domain, universal_name, keyword, industrySize: employee_count (ranges: 1-10, 11-50, 51-200, 201-500, 501-1000, 1001-5000, 5001-10000, 10001+)Headquarters: country_iso_code (ISO 2 letters like “US”, “FR”, “GB”), city, regionOffices: office_country, office_city, office_regionGrowth: employee_growth_1m, employee_growth_6m, employee_growth_12m, recent_hires_countMetadata: founded_year, company_type, follower_count, page_verified, categoryFunding: last_funding_amount_usd, last_funding_date, funding_stage_normalized, has_funding

string

required

Comparison operator to use. Available operators:

= - Exact match
> - Greater than
>= - Greater than or equal
< - Less than
<= - Less than or equal
between - Between two values (requires value2)
in - Value is in a list
like - Text search (pattern matching)

any

Filter value to compare against.

any

Second value (only used with between operator).

integer

default:"0"

Number of results to skip for pagination.

integer

default:"25"

Number of results to return. Maximum: 1000.

boolean

default:"true"

Whether to enrich companies with live data.

true - Returns fresh, up-to-date data (1.5 credits per result)
false - Returns cached data (0.75 credits per result)

Filters System

A FilterGroup combines multiple conditions with a logical operator:

{
  "op": "and",
  "conditions": [...]
}

Field	Type	Description
`op`	string	Logical operator: `"and"` or `"or"`
`conditions`	array	List of `FilterCondition` or nested `FilterGroup` (recursive)

FilterCondition Structure

{
  "column": "name",
  "type": "like",
  "value": "Tech",
  "value2": null
}

Field	Type	Description
`column`	string	Column name to filter on
`type`	string	Operator type (see below)
`value`	any	Filter value
`value2`	any	Second value (only for `between` operator)

Available Operators

Operator	Description	Example
`=`	Exact match	`{"column": "name", "type": "=", "value": "Google"}`
`>`	Greater than	`{"column": "follower_count", "type": ">", "value": 10000}`
`>=`	Greater than or equal	`{"column": "employee_count", "type": ">=", "value": 100}`
`<`	Less than	`{"column": "founded_year", "type": "<", "value": 2020}`
`<=`	Less than or equal	`{"column": "employee_count", "type": "<=", "value": 50}`
`between`	Between two values	`{"column": "founded_year", "type": "between", "value": 2010, "value2": 2020}`
`in`	In a list	`{"column": "country_iso_code", "type": "in", "value": ["US", "UK", "CA"]}`
`like`	Text search	`{"column": "name", "type": "like", "value": "Tech"}`

How text matching works

The operator controls how text is matched — there are no separator characters (comma, pipe, etc.):

= matches the exact value, case-insensitive. On multi-word fields it matches the full phrase, in order — name = "OpenAI" is exact.
like matches records where all the words appear, in any order — the best choice for partial or keyword search. keyword like "artificial intelligence" matches any company whose name, tagline or description contains both words.
in takes a JSON array and matches any value in it (OR): "value": ["FR", "US"]. A comma-separated string like "FR,US" is treated as a single literal value and returns nothing — always pass an array.

Available Columns

Basic Info

Column	Type	Operators	Description
`name`	text	`=`, `like`, `in`	Company name (e.g., “Google”, “Microsoft”)
`tagline`	text	`=`, `like`	Company tagline/slogan
`description`	text	`=`, `like`	Company description
`domain`	text	`=`, `like`, `in`	Domain name (e.g., “google.com”, “microsoft.com”)
`universal_name`	text	`=`, `like`, `in`	Universal slug identifier (e.g., “google”, “microsoft”)
`keyword`	text	`like`	Full-text search in name/tagline/description
`industry`	text	`=`, `like`, `in`	Industry, lowercase (e.g., `software development`, `it services and it consulting`, `financial services`, `business consulting and services`, `advertising services`, `hospitals and health care`)

Size

Column	Type	Operators	Description
`employee_count`	text/int	`=`, `>`, `>=`, `<`, `<=`, `between`, `in`	Number of employees or range (`1-10`, `11-50`, `51-200`, `201-500`, `501-1000`, `1001-5000`, `5001-10000`, `10001+`)

Headquarters

Column	Type	Operators	Description
`country_iso_code`	text	`=`, `in`	Country code ISO 2 letters (e.g., “US”, “FR”, “GB”, “DE”, “CA”)
`city`	text	`=`, `like`, `in`	City name (e.g., “Paris”, “San Francisco”, “London”)
`region`	text	`=`, `like`, `in`	Region/State (e.g., “California”, “Île-de-France”, “New York”)

Offices

Column	Type	Operators	Description
`office_country`	text	`=`, `in`	Office country code ISO 2 letters
`office_city`	text	`=`, `like`, `in`	Office city name
`office_region`	text	`=`, `like`, `in`	Office region/state

Growth

Column	Type	Operators	Description
`employee_growth_1m`	float	`=`, `>`, `>=`, `<`, `<=`, `between`	Employee growth percentage over last 1 month
`employee_growth_6m`	float	`=`, `>`, `>=`, `<`, `<=`, `between`	Employee growth percentage over last 6 months
`employee_growth_12m`	float	`=`, `>`, `>=`, `<`, `<=`, `between`	Employee growth percentage over last 12 months
`recent_hires_count`	int	`=`, `>`, `>=`, `<`, `<=`, `between`	Number of recent hires

Metadata

Column	Type	Operators	Description
`founded_year`	int	`=`, `>`, `>=`, `<`, `<=`, `between`	Year founded (e.g., 1998, 2010, 2020)
`company_type`	text	`=`, `in`	Company type. Values (uppercase, snake_case): `PRIVATELY_HELD`, `PUBLIC_COMPANY`, `NON_PROFIT`, `PARTNERSHIP`, `SELF_OWNED`, `EDUCATIONAL`, `SELF_EMPLOYED`, `GOVERNMENT_AGENCY`
`follower_count`	int	`=`, `>`, `>=`, `<`, `<=`, `between`	Number of followers
`page_verified`	bool	`=`	Whether company profile is verified (true/false)
`category`	text	`=`, `like`, `in`	Company category, lowercase (e.g., `software`, `consulting`, `financial services`, `e-commerce`, `health care`, `manufacturing`, `marketing`, `advertising`)

Funding

Column	Type	Operators	Description
`last_funding_amount_usd`	int	`=`, `>`, `>=`, `<`, `<=`, `between`	Last funding round amount in USD
`last_funding_date`	date	`=`, `>`, `>=`, `<`, `<=`	Last funding round date (e.g., “2023-06-15”)
`funding_stage_normalized`	text	`=`, `like`, `in`	Current funding stage. Values: `seed_round`, `series_a`, `series_b`, `series_c`, `series_d`, `series_e`, `series_f`, `series_g`, `series_h`, `series_unknown`, `pre_seed_round`, `angel_round`, `grant`, `private_equity_round`, `debt_financing`, `convertible_note`, `corporate_round`, `equity_crowdfunding`, `post_ipo_equity`, `post_ipo_debt`, `post_ipo_secondary`, `secondary_market`, `non_equity_assistance`, `product_crowdfunding`, `initial_coin_offering`, `undisclosed`
`has_funding`	bool	`=`	Whether the company has raised funding (true/false)

Complex Query Examples

Tech companies with 100+ employees in California

{
  "filters": {
    "op": "and",
    "conditions": [
      {"column": "industry", "type": "like", "value": "Technology"},
      {"column": "employee_count", "type": ">=", "value": 100},
      {"column": "region", "type": "=", "value": "California"}
    ]
  },
  "count": 50
}

SaaS startups founded after 2015

{
  "filters": {
    "op": "and",
    "conditions": [
      {"column": "category", "type": "like", "value": "SaaS"},
      {"column": "founded_year", "type": ">", "value": 2015},
      {"column": "employee_count", "type": "in", "value": ["11-50", "51-200"]}
    ]
  },
  "count": 100
}

Fast-growing companies (20%+ growth in 6 months)

{
  "filters": {
    "op": "and",
    "conditions": [
      {"column": "employee_growth_6m", "type": ">=", "value": 20},
      {"column": "country_iso_code", "type": "in", "value": ["US", "UK", "FR"]},
      {"column": "page_verified", "type": "=", "value": true}
    ]
  }
}

Companies with offices in multiple countries

{
  "filters": {
    "op": "and",
    "conditions": [
      {"column": "country_iso_code", "type": "=", "value": "US"},
      {
        "op": "or",
        "conditions": [
          {"column": "office_country", "type": "=", "value": "FR"},
          {"column": "office_country", "type": "=", "value": "UK"}
        ]
      }
    ]
  }
}

Response

integer

Total number of results matching the filters.

integer

Offset used for pagination.

integer

Number of results returned in this response.

array

List of companies matching the filters. Each company contains the fields specified by the search columns.

Show company item properties

string

Encoded company ID (org_xxx)

string

Company name

string

Company tagline/slogan

string

Company description

string

Company domain name

string

Universal slug identifier

string

Industry

number | string

Number of employees or range

string

Headquarters country code

string

Headquarters city

string

Headquarters region/state

number

Year founded

string

Type of company

number

Number of followers

boolean

Whether company profile is verified

string

Company category

number

Employee growth over 1 month (%)

number

Employee growth over 6 months (%)

number

Employee growth over 12 months (%)

number

Number of recent hires

array

List of office locations

curl -X POST https://api.dataforb2b.ai/search/companies \
  -H "api_key: YOUR_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "filters": {
      "op": "and",
      "conditions": [
        {"column": "industry", "type": "like", "value": "Technology"},
        {"column": "country_iso_code", "type": "=", "value": "US"}
      ]
    },
    "count": 10
  }'

import requests

response = requests.post(
    "https://api.dataforb2b.ai/search/companies",
    headers={
        "api_key": "YOUR_api_key",
        "Content-Type": "application/json"
    },
    json={
        "filters": {
            "op": "and",
            "conditions": [
                {"column": "industry", "type": "like", "value": "Technology"},
                {"column": "country_iso_code", "type": "=", "value": "US"}
            ]
        },
        "count": 10
    }
)

data = response.json()
print(f"Found {data['total']} companies")

const response = await fetch('https://api.dataforb2b.ai/search/companies', {
  method: 'POST',
  headers: {
    'api_key': 'YOUR_api_key',
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    filters: {
      op: 'and',
      conditions: [
        { column: 'industry', type: 'like', value: 'Technology' },
        { column: 'country_iso_code', type: '=', value: 'US' }
      ]
    },
    count: 10
  })
});

const data = await response.json();
console.log(`Found ${data.total} companies`);

{
  "total": 10000,
  "offset": 0,
  "count": 2,
  "credits_used": 2,
  "results": [
    {
      "id": "org_ABC123xyz",
      "name": "TechCorp Solutions",
      "tagline": "Innovating Tomorrow's Technology Today",
      "description": "TechCorp Solutions is a leading technology company specializing in cloud infrastructure and enterprise software solutions. We help businesses transform digitally through cutting-edge technology and innovative approaches. Our team of 500+ engineers delivers scalable solutions to Fortune 500 companies worldwide.",
      "industry": "software development",
      "headquarters": {
        "country": "US",
        "city": "San Francisco",
        "region": "California"
      },
      "founded_year": 2015,
      "company_type": "PRIVATELY_HELD",
      "logo_url": "https://media.licdn.com/dms/image/...",
      "links": {
        "website": "https://www.techcorp.com",
        "instagram": "https://instagram.com/techcorp",
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}

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