Limadata: Enrich Person

Enrich a person from email, LinkedIn URL, or name plus company with profile, work history, education, social, and employer data.

Tool ID: limadata_enrich_person

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(
  'limadata_enrich_person',
  {
    "email": "jane.doe@example.com",
    "linkedin_url": "https://www.linkedin.com/in/jane-doe",
    "name": "Example"
  },
);

console.log(result.toolResponse.raw);

CLI

deepline tools execute limadata_enrich_person --input '{
  "email": "jane.doe@example.com",
  "linkedin_url": "https://www.linkedin.com/in/jane-doe",
  "name": "Example"
}' --json

Example response

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

{
  "data": {
    "person": {
      "name": "Example",
      "first_name": "Jane",
      "last_name": "Doe"
    },
    "company": {
      "name": "Example",
      "domain": "example.com",
      "website": "https://example.com"
    }
  }
}

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

Input reference

Enrich a person’s professional profile using their email, LinkedIn URL, or name with company information. Returns comprehensive profile data including work history, education, social profiles, and current company information. #### What You Get - Person Data: Full name, headline, summary, location, profile picture - Work Experience: Current job with title, company, dates, and descriptions - Education: Schools, degrees, fields of study, dates - Skills: Professional skills and endorsements - Social Profiles: LinkedIn, Twitter/X, GitHub, Facebook - Company Data: Current employer’s name, domain, website, logo, industry, employee count, locations, funding, revenue, social profiles #### Common Use Cases - CRM Enrichment: Enhance contact records with fresh professional data - Signup Flows: Personalize onboarding by pre-filling user profiles with professional See the live schema below for the complete notes.

Name	Type	Required	Default	Details
`payload.email`	`string`	No	—	Person’s email address. Example: john.doe@example.com
`payload.linkedin_url`	`string`	No	—	Person’s LinkedIn URL. Example: https://linkedin.com/in/johndoe
`payload.name`	`string`	No	—	Person’s name. Required when using company lookup. Example: John Doe
`payload.company_name`	`string`	No	—	Company name. Use with Name for identity resolution. Example: Microsoft
`payload.company_domain`	`string`	No	—	Company domain. Use with Name for identity resolution. Example: microsoft.com
`payload.include_work_email`	`boolean`	No	—	Include the person’s work email in the response. Adds 1 credit if found.
`payload.include_phone`	`boolean`	No	—	Include the person’s phone number(s) in the response. Adds 10 credits if found.

Output reference

Standard tool result payload.

Name	Type	Required	Default	Details
`result.data`	`object`	Yes	—	Provider response payload.
`result.data.person`	`object \| null`	No	—	—
`result.data.person.name`	`string \| null`	No	—	Person’s full name
`result.data.person.first_name`	`string \| null`	No	—	—
`result.data.person.last_name`	`string \| null`	No	—	—
`result.data.person.headline`	`string \| null`	No	—	—
`result.data.person.about`	`string \| null`	No	—	—
`result.data.person.gender`	`string \| null`	No	—	—
`result.data.person.age_in_years`	`integer \| null`	No	—	Format: `int32`.
`result.data.person.location`	`object \| null`	No	—	Person’s location
`result.data.person.location.city`	`string \| null`	No	—	—
`result.data.person.location.state`	`string \| null`	No	—	—
`result.data.person.location.country`	`string \| null`	No	—	—
`result.data.person.location.text`	`string \| null`	No	—	—
`result.data.person.emails`	`array \| null`	No	—	—
`result.data.person.phone_numbers`	`array \| null`	No	—	—
`result.data.person.phone_numbers[].number`	`string \| null`	No	—	—
`result.data.person.phone_numbers[].type`	`string \| null`	No	—	—
`result.data.person.linkedin`	`object \| null`	No	—	—
`result.data.person.linkedin.handle`	`string \| null`	No	—	—
`result.data.person.linkedin.url`	`string \| null`	No	—	—
`result.data.person.github`	`object \| null`	No	—	—
`result.data.person.github.handle`	`string \| null`	No	—	—
`result.data.person.github.url`	`string \| null`	No	—	—
`result.data.person.x`	`object \| null`	No	—	—
`result.data.person.x.handle`	`string \| null`	No	—	—
`result.data.person.x.url`	`string \| null`	No	—	—
`result.data.person.facebook`	`object \| null`	No	—	—
`result.data.person.facebook.handle`	`string \| null`	No	—	—
`result.data.person.facebook.url`	`string \| null`	No	—	—
`result.data.person.employment`	`object \| null`	No	—	—
`result.data.person.employment.title`	`string \| null`	No	—	—
`result.data.person.employment.company_name`	`string \| null`	No	—	—
`result.data.person.employment.company_domain`	`string \| null`	No	—	—
`result.data.person.employment.location`	`string \| null`	No	—	—
`result.data.person.employment.seniority`	`string \| null`	No	—	—
`result.data.person.employment.start_date`	`string \| null`	No	—	Format: `date-time`.
`result.data.person.employment.end_date`	`string \| null`	No	—	Format: `date-time`.
`result.data.person.education`	`object \| null`	No	—	—
`result.data.person.education.degree_name`	`string \| null`	No	—	—
`result.data.person.education.school_name`	`string \| null`	No	—	—
`result.data.person.education.start_date`	`string \| null`	No	—	Format: `date-time`.
`result.data.person.education.end_date`	`string \| null`	No	—	Format: `date-time`.
`result.data.person.profile_image_url`	`string \| null`	No	—	—
`result.data.company`	`object \| null`	No	—	—
`result.data.company.name`	`string \| null`	No	—	—
`result.data.company.domain`	`string \| null`	No	—	—
`result.data.company.website`	`string \| null`	No	—	—
`result.data.company.logo_url`	`string \| null`	No	—	—
`result.data.company.founded_year`	`integer \| null`	No	—	Format: `int32`.

The table shows the first 50 fields. Expand the raw schema below for every field.

This output schema is too large for an inline display. Read the complete live contract with deepline describe limadata_enrich_person --json.

Deepline cost

Pricing model: per_result (per result).
Estimated Deepline credits: 0.28 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