> ## 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 People

> Search professional profiles with advanced filters

## Credit Cost

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

<Info>
  Need access to additional filters? Contact us at [dev@dataforb2b.ai](mailto:dev@dataforb2b.ai) with your use case.
</Info>

***

## Request Body

<ParamField body="lookalike_profile" type="string">
  LinkedIn profile URL, `public_id`, or `member_identity` of a person to find similar profiles.

  Examples:

  * `"https://www.linkedin.com/in/thomas-kurian-469b6219/"`
  * `"sebonomics"`

  <Warning>
    Mutually exclusive with `filters`. You cannot use both `lookalike_profile` and `filters` in the same request.
  </Warning>
</ParamField>

<ParamField body="lookalike_use_case" type="string" default="sales">
  Use case for the lookalike search. Only used when `lookalike_profile` is provided.

  * `"sales"` — Find profiles similar from a sales/prospecting perspective
  * `"recruiter"` — Find profiles similar from a recruiting perspective
</ParamField>

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

  <Warning>
    Mutually exclusive with `lookalike_profile`. You cannot use both `filters` and `lookalike_profile` in the same request.
  </Warning>
</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.

  **Profile:** `first_name`, `last_name`, `profile_location`, `profile_country`, `profile_industry`, `follower_count`, `keyword`

  **Current Job:** `current_company`, `current_title`, `current_job_location`, `current_company_industry`, `current_company_category`, `current_company_size` (values: `2-10`, `11-50`, `51-200`, `201-500`, `501-1000`, `1001-5000`, `5001-10000`, `10001+`), `current_company_id`, `current_employment_type`, `years_in_current_position`, `years_at_current_company`, `current_company_has_funding`, `current_company_funding_stage`, `current_company_investor`

  **Past Jobs:** `past_company`, `past_title`, `past_job_location`, `past_company_industry`, `past_company_size` (same values as current\_company\_size), `past_company_id`, `past_employment_type`, `years_at_past_company`

  **Skills:** `skill` (e.g., "Python", "JavaScript", "Machine Learning")

  **Education:** `school`, `degree`, `degree_level` (e.g., "Bachelor", "Master", "PhD"), `field_of_study`

  **Languages:** `language` (full name), `language_iso` (ISO code like "en", "fr"), `language_proficiency` (e.g., "Native", "Professional", "Elementary")

  **Certifications:** `certification`, `certification_authority`

  **Experience:** `years_of_experience` (total career), `num_total_jobs` (number of positions), `is_currently_employed` (boolean)
</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 profiles 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": "first_name",
  "type": "=",
  "value": "John",
  "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": "first_name", "type": "=", "value": "John"}`                        |
| `>`       | Greater than          | `{"column": "follower_count", "type": ">", "value": 1000}`                      |
| `>=`      | Greater than or equal | `{"column": "years_of_experience", "type": ">=", "value": 5}`                   |
| `<`       | Less than             | `{"column": "years_at_current_company", "type": "<", "value": 2}`               |
| `<=`      | Less than or equal    | `{"column": "follower_count", "type": "<=", "value": 500}`                      |
| `between` | Between two values    | `{"column": "years_of_experience", "type": "between", "value": 3, "value2": 7}` |
| `in`      | In a list             | `{"column": "country", "type": "in", "value": ["US", "UK", "CA"]}`              |
| `like`    | Text search           | `{"column": "current_title", "type": "like", "value": "Engineer"}`              |

***

## Available Columns

### Profile

| Column             | Type | Recommended Operators                | Description                                                                                                              |
| ------------------ | ---- | ------------------------------------ | ------------------------------------------------------------------------------------------------------------------------ |
| `first_name`       | text | `=`, `like`, `in`                    | Person's first name                                                                                                      |
| `last_name`        | text | `=`, `like`, `in`                    | Person's last name                                                                                                       |
| `profile_location` | text | `=`, `like`                          | Current location (city, state)                                                                                           |
| `profile_country`  | text | `=`, `in`                            | Country code ISO 2 letters, uppercase (e.g., "US", "GB", "FR", "DE", "CA"). Note: use `GB` (not `UK`) for United Kingdom |
| `profile_industry` | text | `=`, `like`, `in`                    | Profile industry                                                                                                         |
| `follower_count`   | int  | `=`, `>`, `>=`, `<`, `<=`, `between` | Number of profile followers                                                                                              |
| `keyword`          | text | `like`                               | Full-text search in headline (trigram matching)                                                                          |

### Current Job

| Column                          | Type | Operators                            | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| ------------------------------- | ---- | ------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `current_company`               | text | `=`, `like`, `in`                    | Current employer name                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
| `current_title`                 | text | `=`, `like`, `in`                    | Current job title                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      |
| `current_job_location`          | text | `=`, `like`, `in`                    | Current job location (city, state)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| `current_company_industry`      | text | `=`, `like`, `in`                    | Industry of current employer, capitalized (e.g., "Information Technology & Services", "Computer Software", "Hospital & Health Care", "Financial Services", "Marketing & Advertising")                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
| `current_company_category`      | text | `=`, `like`, `in`                    | Category of current employer, lowercase (e.g., `software`, `consulting`, `financial services`, `e-commerce`, `health care`)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| `current_company_size`          | text | `=`, `in`                            | Company size range (`2-10`, `11-50`, `51-200`, `201-500`, `501-1000`, `1001-5000`, `5001-10000`, `10001+`)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             |
| `current_company_id`            | text | `=`, `in`                            | Company identifier                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
| `current_employment_type`       | text | `=`, `in`                            | Employment type. Values: "Full-time", "Part-time", "Self-employed", "Freelance", "Contract", "Permanent", "Permanent Full-time", "Permanent Part-time", "Contract Full-time", "Contract Part-time", "Internship", "Apprenticeship", "Seasonal"                                                                                                                                                                                                                                                                                                                                                                                                                         |
| `years_in_current_position`     | int  | `=`, `>`, `>=`, `<`, `<=`, `between` | Years in current role                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
| `years_at_current_company`      | int  | `=`, `>`, `>=`, `<`, `<=`, `between` | Years at current company                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
| `current_company_has_funding`   | bool | `=`                                  | Whether the current company has received funding (true/false)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| `current_company_funding_stage` | text | `=`, `in`                            | Funding stage of the current company. 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`. Note: data also contains some legacy values without `_round` suffix (`seed`, `pre_seed`, `angel`, `private_equity`) — use `in` with both forms for max coverage |
| `current_company_investor`      | text | `=`, `like`, `in`                    | Investor name of the current company. Supports partial matching with `like`                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |

### Past Jobs

| Column                  | Type | Operators                            | Description                                                       |
| ----------------------- | ---- | ------------------------------------ | ----------------------------------------------------------------- |
| `past_company`          | text | `=`, `like`, `in`                    | Former employer name                                              |
| `past_title`            | text | `=`, `like`, `in`                    | Previous job title                                                |
| `past_job_location`     | text | `=`, `like`, `in`                    | Past job location (city, state)                                   |
| `past_company_industry` | text | `=`, `like`, `in`                    | Industry of former employer                                       |
| `past_company_size`     | text | `=`, `in`                            | Former company size range (same values as current\_company\_size) |
| `past_company_id`       | text | `=`, `in`                            | Company identifier of former employer                             |
| `past_employment_type`  | text | `=`, `in`                            | Past employment type                                              |
| `years_at_past_company` | int  | `=`, `>`, `>=`, `<`, `<=`, `between` | Years spent at former company                                     |

### Skills

| Column  | Type | Operators         | Description                                                                 |
| ------- | ---- | ----------------- | --------------------------------------------------------------------------- |
| `skill` | text | `=`, `like`, `in` | Skills listed on profile (e.g., "Python", "JavaScript", "Machine Learning") |

### Education

| Column           | Type | Operators         | Description                                                   |
| ---------------- | ---- | ----------------- | ------------------------------------------------------------- |
| `school`         | text | `=`, `like`, `in` | Educational institution name                                  |
| `degree`         | text | `=`, `like`, `in` | Degree name                                                   |
| `degree_level`   | text | `=`, `in`         | Degree level (e.g., "Bachelor", "Master", "PhD", "Associate") |
| `field_of_study` | text | `=`, `like`, `in` | Major or field of study                                       |

### Languages

| Column                 | Type | Operators         | Description                                                                 |
| ---------------------- | ---- | ----------------- | --------------------------------------------------------------------------- |
| `language`             | text | `=`, `like`, `in` | Language name (e.g., "English", "French", "Spanish")                        |
| `language_iso`         | text | `=`, `in`         | ISO language code (e.g., "en", "fr", "es")                                  |
| `language_proficiency` | text | `=`, `in`         | Proficiency level (e.g., "Native", "Professional", "Limited", "Elementary") |

### Certifications

| Column                    | Type | Operators         | Description                                               |
| ------------------------- | ---- | ----------------- | --------------------------------------------------------- |
| `certification`           | text | `=`, `like`, `in` | Certification name (e.g., "AWS Certified", "PMP", "CPA")  |
| `certification_authority` | text | `=`, `like`, `in` | Issuing organization (e.g., "Amazon Web Services", "PMI") |

### Experience

| Column                  | Type | Operators                            | Description                                       |
| ----------------------- | ---- | ------------------------------------ | ------------------------------------------------- |
| `years_of_experience`   | int  | `=`, `>`, `>=`, `<`, `<=`, `between` | Total years of professional experience            |
| `num_total_jobs`        | int  | `=`, `>`, `>=`, `<`, `<=`, `between` | Total number of positions held                    |
| `is_currently_employed` | bool | `=`                                  | Whether person is currently employed (true/false) |

***

## Complex Query Examples

<AccordionGroup>
  <Accordion title="Senior developers at FAANG companies">
    ```json theme={null}
    {
      "filters": {
        "op": "and",
        "conditions": [
          {"column": "current_company", "type": "in", "value": ["Google", "Apple", "Facebook", "Amazon", "Microsoft"]},
          {"column": "current_title", "type": "like", "value": "Senior"},
          {"column": "skill", "type": "in", "value": ["Python", "Java", "Go"]},
          {"column": "years_of_experience", "type": ">=", "value": 8}
        ]
      },
      "count": 100
    }
    ```
  </Accordion>

  <Accordion title="Ex-consultants from McKinsey/BCG now at startups">
    ```json theme={null}
    {
      "filters": {
        "op": "and",
        "conditions": [
          {"column": "past_company", "type": "in", "value": ["McKinsey", "BCG", "Bain"]},
          {"column": "current_company_size", "type": "in", "value": ["2-10", "11-50"]},
          {"column": "current_title", "type": "like", "value": "%Founder%"}
        ]
      },
      "count": 50
    }
    ```
  </Accordion>

  <Accordion title="Engineers at Series A/B funded companies backed by Sequoia">
    ```json theme={null}
    {
      "filters": {
        "op": "and",
        "conditions": [
          {"column": "current_title", "type": "like", "value": "Engineer"},
          {"column": "current_company_has_funding", "type": "=", "value": true},
          {"column": "current_company_funding_stage", "type": "in", "value": ["series_a", "series_b"]},
          {"column": "current_company_investor", "type": "like", "value": "Sequoia"}
        ]
      },
      "count": 50
    }
    ```
  </Accordion>

  <Accordion title="OR search (profiles with Python OR JavaScript)">
    ```json theme={null}
    {
      "filters": {
        "op": "and",
        "conditions": [
          {"column": "profile_country", "type": "=", "value": "US"},
          {
            "op": "or",
            "conditions": [
              {"column": "skill", "type": "=", "value": "Python"},
              {"column": "skill", "type": "=", "value": "JavaScript"}
            ]
          }
        ]
      }
    }
    ```
  </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 profiles matching the filters. Each profile contains the fields specified by the search columns.

  <Expandable title="profile item properties">
    <ResponseField name="first_name" type="string">
      Person's first name
    </ResponseField>

    <ResponseField name="last_name" type="string">
      Person's last name
    </ResponseField>

    <ResponseField name="profile_headline" type="string">
      Professional headline
    </ResponseField>

    <ResponseField name="summary" type="string">
      Profile summary/bio
    </ResponseField>

    <ResponseField name="profile_location" type="string">
      Current location (city, state)
    </ResponseField>

    <ResponseField name="profile_country" type="string">
      Country code (e.g., "US", "UK", "FR")
    </ResponseField>

    <ResponseField name="profile_industry" type="string">
      Profile industry
    </ResponseField>

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

    <ResponseField name="current_company" type="string">
      Current employer name
    </ResponseField>

    <ResponseField name="current_title" type="string">
      Current job title
    </ResponseField>

    <ResponseField name="current_job_location" type="string">
      Current job location
    </ResponseField>

    <ResponseField name="current_job_country" type="string">
      Current job country code
    </ResponseField>

    <ResponseField name="current_company_industry" type="string">
      Industry of current employer
    </ResponseField>

    <ResponseField name="current_company_size" type="string">
      Company size range
    </ResponseField>

    <ResponseField name="years_of_experience" type="number">
      Total years of professional experience
    </ResponseField>

    <ResponseField name="years_in_current_position" type="number">
      Years in current role
    </ResponseField>

    <ResponseField name="years_at_current_company" type="number">
      Years at current company
    </ResponseField>

    <ResponseField name="experiences" type="array">
      Work experience history
    </ResponseField>

    <ResponseField name="education" type="array">
      Education history
    </ResponseField>

    <ResponseField name="skills" type="array">
      Skills list
    </ResponseField>
  </Expandable>
</ResponseField>

***

<RequestExample>
  ```bash cURL theme={null}
  curl -X POST https://api.dataforb2b.ai/search/people \
    -H "api_key: YOUR_api_key" \
    -H "Content-Type: application/json" \
    -d '{
      "filters": {
        "op": "and",
        "conditions": [
          {"column": "current_title", "type": "like", "value": "Engineer"},
          {"column": "profile_country", "type": "=", "value": "US"}
        ]
      },
      "count": 10
    }'
  ```

  ```python Python theme={null}
  import requests

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

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

  ```javascript JavaScript theme={null}
  const response = await fetch('https://api.dataforb2b.ai/search/people', {
    method: 'POST',
    headers: {
      'api_key': 'YOUR_api_key',
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      filters: {
        op: 'and',
        conditions: [
          { column: 'current_title', type: 'like', value: 'Engineer' },
          { column: 'country', type: '=', value: 'US' }
        ]
      },
      count: 10
    })
  });

  const data = await response.json();
  console.log(`Found ${data.total} profiles`);
  ```
</RequestExample>

<ResponseExample>
  ```json Response theme={null}
  {
    "total": 10000,
    "offset": 0,
    "count": 2,
    "credits_used": 2,
    "results": [
      {
        "id": "prof_PVURNGJihYludzaOwFCAwNajijSHFi6H0L9R",
        "first_name": "Sarah",
        "last_name": "Martinez",
        "headline": "Senior Software Engineer at Google | Cloud Infrastructure",
        "location": "San Francisco Bay Area, California",
        "country": "US",
        "industry": "Computer Software",
        "summary": "Passionate software engineer with 8+ years of experience building scalable cloud infrastructure. Specialized in Kubernetes, distributed systems, and site reliability engineering. Led multiple teams in delivering high-impact projects for millions of users.",
        "profile_language": "en",
        "profile_picture_url": "https://media.licdn.com/dms/image/...",
        "links": {
          "linkedin": "https://www.linkedin.com/in/sarah-martinez-engineer",
          "twitter": "https://twitter.com/sarahdev",
          "github": "https://github.com/smartinez"
        },
        "experience": [
          {
            "company": {
              "id": "org_google",
              "name": "Google",
              "url": "https://linkedin.com/company/google",
              "logo_url": "https://media.licdn.com/dms/image/...",
              "size": "10001+",
              "industry": "Information Technology & Services",
              "domain": "google.com",
              "website": "https://www.google.com"
            },
            "title": "Senior Software Engineer",
            "description": "Lead engineer for Google Cloud infrastructure, managing Kubernetes clusters at scale. Reduced deployment time by 40% through automation and improved system reliability to 99.99% uptime.",
            "employment_type": "Full-time",
            "location": "Mountain View, California",
            "duration_months": 36,
            "start_date": "2021-09",
            "end_date": null,
            "is_current": true
          },
          {
            "company": {
              "id": "org_amazon",
              "name": "Amazon",
              "url": "https://linkedin.com/company/amazon",
              "logo_url": "https://media.licdn.com/dms/image/...",
              "size": "10001+",
              "industry": "Internet",
              "domain": "amazon.com",
              "website": "https://www.amazon.com"
            },
            "title": "Software Engineer II",
            "description": "Developed microservices for AWS infrastructure. Built monitoring and alerting systems processing millions of events daily.",
            "employment_type": "Full-time",
            "location": "Seattle, Washington",
            "duration_months": 30,
            "start_date": "2019-03",
            "end_date": "2021-08",
            "is_current": false
          },
          {
            "company": {
              "id": "org_microsoft",
              "name": "Microsoft",
              "url": "https://linkedin.com/company/microsoft",
              "logo_url": "https://media.licdn.com/dms/image/...",
              "size": "10001+",
              "industry": "Computer Software",
              "domain": "microsoft.com",
              "website": "https://www.microsoft.com"
            },
            "title": "Software Engineer",
            "description": "Azure infrastructure development and DevOps automation.",
            "employment_type": "Full-time",
            "location": "Redmond, Washington",
            "duration_months": 24,
            "start_date": "2017-03",
            "end_date": "2019-02",
            "is_current": false
          }
        ],
        "education": [
          {
            "school": {
              "id": "edu_0lox4Unn3pMSqjJXEFXX1n5YqgKPsQZQlAmZ",
              "name": "Stanford University",
              "url": "https://www.linkedin.com/school/stanford-university/",
              "logo_url": "https://media.licdn.com/dms/image/..."
            },
            "degree": "Master of Science - MS",
            "field_of_study": "Computer Science",
            "activities": "Teaching Assistant for CS 106A",
            "grade": "3.9 GPA",
            "description": "Focus on distributed systems and machine learning",
            "start_date": "2015",
            "end_date": "2017"
          },
          {
            "school": {
              "id": "edu_0lox4Unn3pMSqjJXEFXX1n5YqgKPsQZSAIQJ",
              "name": "UC Berkeley",
              "url": "https://www.linkedin.com/school/uc-berkeley/",
              "logo_url": "https://media.licdn.com/dms/image/..."
            },
            "degree": "Bachelor of Science - BS",
            "field_of_study": "Computer Engineering",
            "activities": "IEEE Computer Society, Hackathons",
            "grade": "3.8 GPA",
            "description": null,
            "start_date": "2011",
            "end_date": "2015"
          }
        ],
        "skills": [
          "Python",
          "Kubernetes",
          "Docker",
          "Go",
          "Terraform",
          "AWS",
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