Enformion: Contact Enrich

Find personal mobile phones for SMB owners (restaurants, retail, local services) who have no LinkedIn or B2B presence.

Tool ID: enformion_contact_enrich

Run this action

Use the TypeScript SDK for a single call. Put ctx.tools.execute(...) inside a Play when the call should be durable, scheduled, or run across a CSV.

import { Deepline } from 'deepline';

const deepline = await Deepline.connect();
const result = await deepline.tools.execute(
  'enformion_contact_enrich',
  {
    "first_name": "Jane",
    "last_name": "Doe",
    "city_state": "California"
  },
);

console.log(result.toolResponse.raw);

CLI

deepline tools execute enformion_contact_enrich --input '{
  "first_name": "Jane",
  "last_name": "Doe",
  "city_state": "California"
}' --json

Example response

The SDK exposes this shape at result.toolResponse.raw. Values below are representative.

{
  "person": {
    "name": {
      "firstName": "Jane",
      "middleName": "Example",
      "lastName": "Doe"
    },
    "age": "example",
    "addresses": [
      {
        "firstReportedDate": "2026-01-15T12:00:00Z",
        "lastReportedDate": "2026-01-15T12:00:00Z",
        "street": "example",
        "unit": "example",
        "city": "San Francisco",
        "state": "California",
        "zip": "example"
      }
    ],
    "phones": [
      {
        "number": "example",
        "type": "example",
        "isConnected": true,
        "firstReportedDate": "2026-01-15T12:00:00Z",
        "lastReportedDate": "2026-01-15T12:00:00Z"
      }
    ],
    "emails": [
      "jane.doe@example.com"
    ]
  },
  "message": "Example message",
  "identityScore": 123,
  "isError": true
}

Use deepline tools get enformion_contact_enrich --json for the latest machine-readable contract.

Input reference

Consumer skip-trace via EnformionGO. Finds personal mobile phones from name + city/state (optionally narrowed by a street address). Designed for SMB restaurant/retail owners with no B2B presence. Returns typed phones (mobile/landline) with isConnected flag and identityScore (0–100). Hit rate ~53% on named rows. Do NOT pass middle initials in last_name.

Name	Type	Required	Default	Details
`payload.first_name`	`string`	Yes	—	Owner first name. Do not include middle name or initial. Minimum length: 1.
`payload.last_name`	`string`	Yes	—	Owner last name. The integration automatically strips middle initials and compound surname prefixes (e.g. ‘De La Cruz’ → ‘Cruz’) because EnformionGO returns zero results for multi-word last names. Minimum length: 1.
`payload.city_state`	`string`	Yes	—	City and state as “City, ST” (e.g. “Cleveland, OH”). Used as Address.addressLine2 in the EnformionGO request. Minimum length: 1.
`payload.address_line1`	`string`	No	—	Street address (e.g. “123 Q Street”). Used as Address.addressLine1 alongside city_state. Narrows the match when you already know the resident’s street, instead of a separate property lookup first. Minimum length: 1.

Output reference

Name	Type	Required	Default	Details
`result.person`	`object`	Yes	—	—
`result.person.name`	`object`	Yes	—	—
`result.person.name.firstName`	`string`	Yes	—	—
`result.person.name.middleName`	`string`	Yes	—	—
`result.person.name.lastName`	`string`	Yes	—	—
`result.person.age`	`string`	Yes	—	—
`result.person.addresses`	`array`	Yes	—	—
`result.person.addresses[].firstReportedDate`	`string`	Yes	—	—
`result.person.addresses[].lastReportedDate`	`string`	Yes	—	—
`result.person.addresses[].street`	`string`	Yes	—	—
`result.person.addresses[].unit`	`string`	Yes	—	—
`result.person.addresses[].city`	`string`	Yes	—	—
`result.person.addresses[].state`	`string`	Yes	—	—
`result.person.addresses[].zip`	`string`	Yes	—	—
`result.person.phones`	`array`	Yes	—	—
`result.person.phones[].number`	`string`	Yes	—	—
`result.person.phones[].type`	`string`	Yes	—	—
`result.person.phones[].isConnected`	`boolean`	Yes	—	—
`result.person.phones[].firstReportedDate`	`string`	Yes	—	—
`result.person.phones[].lastReportedDate`	`string`	Yes	—	—
`result.person.emails`	`array`	Yes	—	—
`result.message`	`string`	Yes	—	—
`result.identityScore`	`integer`	Yes	—	—
`result.isError`	`boolean`	Yes	—	—

Deepline cost

Pricing model: per_result (per result).
Estimated Deepline credits: 0.7 per pricing unit.

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Reference

Enformion: Contact Enrich

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CLI

Example response

Input reference

Output reference

Deepline cost

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​CLI

​Example response

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​Related documentation

Run this action

CLI

Example response

Input reference

Output reference

Deepline cost

Related documentation