> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dataforb2b.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Search Company

> Search companies with advanced filters

## Credit Cost

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

***

## Request Body

<ParamField body="filters" type="object">
  Filter group to apply to the search. See [Filters](#filters-system) section below.
</ParamField>

<ParamField body="filters.op" type="string" required>
  Logical operator to combine conditions.

  * `and` - All conditions must match
  * `or` - At least one condition must match
</ParamField>

<ParamField body="filters.conditions" type="array" required>
  Array of filter conditions or nested filter groups.
</ParamField>

<ParamField body="filters.conditions[].column" type="string" required>
  Column name to filter on. See [Available Columns](#available-columns) section below for complete list with data types and recommended operators.

  **Basic Info:** `name`, `tagline`, `description`, `domain`, `universal_name`, `keyword`, `industry`

  **Size:** `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`, `region`

  **Offices:** `office_country`, `office_city`, `office_region`

  **Growth:** `employee_growth_1m`, `employee_growth_6m`, `employee_growth_12m`, `recent_hires_count`

  **Metadata:** `founded_year`, `company_type`, `follower_count`, `page_verified`, `category`

  **Funding:** `last_funding_amount_usd`, `last_funding_date`, `funding_stage_normalized`, `has_funding`
</ParamField>

<ParamField body="filters.conditions[].type" type="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)
</ParamField>

<ParamField body="filters.conditions[].value" type="any">
  Filter value to compare against.
</ParamField>

<ParamField body="filters.conditions[].value2" type="any">
  Second value (only used with `between` operator).
</ParamField>

<ParamField body="offset" type="integer" default="0">
  Number of results to skip for pagination.
</ParamField>

<ParamField body="count" type="integer" default="25">
  Number of results to return. Maximum: 1000.
</ParamField>

<ParamField body="enrich_live" type="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)
</ParamField>

***

## Filters System

### FilterGroup Structure

A FilterGroup combines multiple conditions with a logical operator:

```json theme={null}
{
  "op": "and",
  "conditions": [...]
}
```

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

### FilterCondition Structure

```json theme={null}
{
  "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"}`                          |

***

## 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

<AccordionGroup>
  <Accordion title="Tech companies with 100+ employees in California">
    ```json theme={null}
    {
      "filters": {
        "op": "and",
        "conditions": [
          {"column": "industry", "type": "like", "value": "Technology"},
          {"column": "employee_count", "type": ">=", "value": 100},
          {"column": "region", "type": "=", "value": "California"}
        ]
      },
      "count": 50
    }
    ```
  </Accordion>

  <Accordion title="SaaS startups founded after 2015">
    ```json theme={null}
    {
      "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
    }
    ```
  </Accordion>

  <Accordion title="Fast-growing companies (20%+ growth in 6 months)">
    ```json theme={null}
    {
      "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}
        ]
      }
    }
    ```
  </Accordion>

  <Accordion title="Companies with offices in multiple countries">
    ```json theme={null}
    {
      "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"}
            ]
          }
        ]
      }
    }
    ```
  </Accordion>
</AccordionGroup>

***

## Response

<ResponseField name="total" type="integer">
  Total number of results matching the filters.
</ResponseField>

<ResponseField name="offset" type="integer">
  Offset used for pagination.
</ResponseField>

<ResponseField name="count" type="integer">
  Number of results returned in this response.
</ResponseField>

<ResponseField name="results" type="array">
  List of companies matching the filters. Each company contains the fields specified by the search columns.

  <Expandable title="company item properties">
    <ResponseField name="id" type="string">
      Encoded company ID (org\_xxx)
    </ResponseField>

    <ResponseField name="name" type="string">
      Company name
    </ResponseField>

    <ResponseField name="tagline" type="string">
      Company tagline/slogan
    </ResponseField>

    <ResponseField name="description" type="string">
      Company description
    </ResponseField>

    <ResponseField name="domain" type="string">
      Company domain name
    </ResponseField>

    <ResponseField name="universal_name" type="string">
      Universal slug identifier
    </ResponseField>

    <ResponseField name="industry" type="string">
      Industry
    </ResponseField>

    <ResponseField name="employee_count" type="number | string">
      Number of employees or range
    </ResponseField>

    <ResponseField name="country_iso_code" type="string">
      Headquarters country code
    </ResponseField>

    <ResponseField name="city" type="string">
      Headquarters city
    </ResponseField>

    <ResponseField name="region" type="string">
      Headquarters region/state
    </ResponseField>

    <ResponseField name="founded_year" type="number">
      Year founded
    </ResponseField>

    <ResponseField name="company_type" type="string">
      Type of company
    </ResponseField>

    <ResponseField name="follower_count" type="number">
      Number of followers
    </ResponseField>

    <ResponseField name="page_verified" type="boolean">
      Whether company profile is verified
    </ResponseField>

    <ResponseField name="category" type="string">
      Company category
    </ResponseField>

    <ResponseField name="employee_growth_1m" type="number">
      Employee growth over 1 month (%)
    </ResponseField>

    <ResponseField name="employee_growth_6m" type="number">
      Employee growth over 6 months (%)
    </ResponseField>

    <ResponseField name="employee_growth_12m" type="number">
      Employee growth over 12 months (%)
    </ResponseField>

    <ResponseField name="recent_hires_count" type="number">
      Number of recent hires
    </ResponseField>

    <ResponseField name="offices" type="array">
      List of office locations
    </ResponseField>
  </Expandable>
</ResponseField>

***

<RequestExample>
  ```bash cURL theme={null}
  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
    }'
  ```

  ```python Python theme={null}
  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")
  ```

  ```javascript JavaScript theme={null}
  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`);
  ```
</RequestExample>

<ResponseExample>
  ```json Response theme={null}
  {
    "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
        }
      }
    ]
  }
  ```
</ResponseExample>