Datagma: Find People

Find up to 10 matching people by title inside a target company.

Tool ID: datagma_find_people

Run this action

Use the TypeScript SDK for one call. Use ctx.tools.execute(...) inside a Play for durable calls, scheduled calls, or CSV processing.

import { Deepline } from 'deepline';

const deepline = await Deepline.connect();
const result = await deepline.tools.execute(
  'datagma_find_people',
  {
    "currentJobTitle": "VP of Engineering",
    "linkedinId": "https://www.linkedin.com/in/jane-doe",
    "domain": "example.com"
  },
);

console.log(result.toolResponse.raw);

CLI

deepline tools execute datagma_find_people --input '{
  "currentJobTitle": "VP of Engineering",
  "linkedinId": "https://www.linkedin.com/in/jane-doe",
  "domain": "example.com"
}' --json

Example response

The SDK returns this shape at result.toolResponse.raw. The example values illustrate the response.

{
  "data": {
    "transferData": [
      {
        "key": "example",
        "value": "example"
      }
    ],
    "listOfInvalidDataInput": [
      "example"
    ],
    "listOfValidLinkedInId": [
      "list_of_valid_linked_in_123"
    ]
  }
}

Use deepline describe datagma_find_people --json for the latest machine-readable contract.

Input reference

Allows you to identify individuals working in specific job titles within a given company. The query can return up to 10 people.

Name	Type	Required	Default	Details
`payload.currentJobTitle`	`string`	No	—	Current Job Title - You can separate different job titles using ‘OR’ (e.g., head of OR chief OR CEO).
`payload.linkedinId`	`string`	No	—	Enter the company’s LinkedIn ID if available (e.g., 1441, 2728700…). It is the most accurate input you can use.
`payload.domain`	`string`	No	—	Enter the domain name if available (e.g., algolia.com, ubisoft.com…). It is less accurate than the LinkedIn ID, but more accurate than the company name
`payload.currentCompanies`	`string`	No	—	Enter the company name (e.g., Algolia, Ubisoft…). This is less accurate compared to using the domain or LinkedIn ID
`payload.countries`	`string`	No	—	Country. Please use the country name in minimal letters (e.g., united states, france, germany…)
`payload.fuzzy`	`boolean`	No	—	When set to true, the endpoint performs a fuzzy search, which broadens the scope of the results by allowing approximate matches. This is useful for finding results that may not exactly match the search criteria. However, enabling this parameter can reduce precision, potentially returning more irrelevant results. Default is false.
`payload.debug`	`boolean`	No	—	We are working on a feature to filter out non-relevant job titles. Set this parameter to true to disable filtering and retrieve all results

Output reference

Standard tool result payload.

Name	Type	Required	Default	Details
`result.data`	`object`	Yes	—	Provider response payload.
`result.data.transferData`	`array`	No	—	—
`result.data.transferData[].key`	`string`	No	—	—
`result.data.transferData[].value`	`string`	No	—	—
`result.data.listOfInvalidDataInput`	`array`	No	—	—
`result.data.listOfValidLinkedInId`	`array`	No	—	—
`result.data.employees`	`array`	No	—	—
`result.data.employees[].name`	`string`	No	—	—
`result.data.employees[].firstname`	`string`	No	—	—
`result.data.employees[].lastName`	`string`	No	—	—
`result.data.employees[].location`	`string`	No	—	—
`result.data.employees[].jobTitle`	`string`	No	—	—
`result.data.employees[].company`	`string`	No	—	—
`result.data.employees[].linkedInUrl`	`string`	No	—	—
`result.data.employees[].extractedRole`	`string`	No	—	—
`result.data.employees[].extractedSeniority`	`string`	No	—	—
`result.data.employees[].extractedGender`	`string`	No	—	—
`result.data.employees[].person_confidence_score`	`number`	No	—	Format: `float`.
`result.data.employees[].employee_jobScore`	`number`	No	—	Format: `float`.
`result.data.employees[].employee_companyScore`	`number`	No	—	Format: `float`.
`result.data.employees[].email`	`object`	No	—	—
`result.data.employees[].email.email`	`string`	No	—	—
`result.data.employees[].email.status`	`string`	No	—	—
`result.meta`	`object`	No	—	Additional response metadata (status, paging).

Deepline cost

Pricing model: provider_usage (provider usage).
Estimated Deepline credits: 0.14 per pricing unit.

​Run this action

​CLI

​Example response

​Input reference

​Output reference

​Deepline cost

​Related documentation

Run this action

CLI

Example response

Input reference

Output reference

Deepline cost

Related documentation