Email Finder: Name + Company Domain to Work Email

You have a name and a company. You need the email. This Actor works it out.

It builds the candidates the way companies actually assign addresses (jane.doe@, jdoe@, janedoe@ …), reads the company's own website to learn which format they use, and checks that the domain accepts mail at all.

How to use

1. Sign up for Apify — the free plan's monthly credit is enough to try this Actor.
2. Open Email Finder, fill in the input (the form is pre-filled with a working example) and click Start.
3. Watch results stream into the dataset table while the run is going.
4. Export as JSON, CSV, Excel, XML, HTML or RSS — or pull the results from your own code with the Apify API.

How this finds work emails

Most tools hand you ten permutations and let you sort it out. This one:

1. Looks for addresses already published on the company site (contact, about, team pages)
2. Recognises the format from them — hello@ is ignored, sarah.kim@ is the signal
3. Puts the matching candidate first and marks it high confidence
4. Confirms the domain accepts mail (MX record), and tells you who runs it
5. Scores every guess 0-100 and tries nickname variants (Bob → Robert, Mike → Michael)

How to find work emails

One object per person:

[{ "fullName": "Jane Doe", "domain": "acme.com" },
 { "firstName": "Jan", "lastName": "Curn", "domain": "apify.com", "title": "CEO" }]

Field	What it does
peopleText	Or paste lines like Jane Doe, acme.com
csvUrl	Or a public CSV or Google Sheets link (columns detected by name)
datasetId	Or the dataset of another run, e.g. a LinkedIn or Google Maps scrape
findPatternFromWebsite	Learn the format from the company site (on by default)
useNicknames	Try nickname variants as lower-scored alternatives (on by default)
patterns	Limit to specific formats

Input reference

Every option at a glance. A minimal input that works as-is:

{
  "people": [
    {
      "fullName": "Patrick Collison",
      "domain": "stripe.com"
    },
    {
      "firstName": "Jan",
      "lastName": "Curn",
      "domain": "apify.com"
    }
  ],
  "findPatternFromWebsite": true,
  "useNicknames": true,
  "maxResults": 1000
}

All fields:

• people (People) — One object per person: {"fullName": "Jane Doe", "domain": "acme.com"}. You can also use firstName/lastName, and add company or title to carry them through to the output. Optional if you paste lines, a CSV link or a dataset ID below.
• peopleText (Or paste people, one per line) — One person per line: name, company domain (optionally company name and job title). Example: “Jane Doe, acme.com”.
• csvUrl (Or a CSV / Google Sheets link) — Public link to a CSV file or a Google Sheet. Columns are detected by name: full name (or first/last name), domain or website, company, title.
• datasetId (Or a dataset from another run) — Dataset ID from another Apify run (for example a LinkedIn or Google Maps scrape). Columns are detected by name, like the CSV.
• findPatternFromWebsite (Learn the pattern from the company site) — Looks for addresses already published on the company website and follows that format. This is what turns a guess into a confident answer. Default true.
• useNicknames (Try nickname variants) — Bob → Robert, Mike → Michael and back. Variants are listed as lower-scored alternatives. Default true.
• patterns (Limit to these patterns) — Leave empty to try all of them, most common first. Any of: first.last, first, flast, firstlast, first_last, firstl, f.last, last.first, lastf, last.
• maxResults (Max results) — Total limit. Default 1000.
• proxy (Proxy) — Used when reading company websites.

What the work email output looks like

{
  "fullName": "john smith",
  "firstName": "john",
  "lastName": "smith",
  "company": null,
  "domain": "gymshark.com",
  "title": null,
  "email": "john.smith@gymshark.com",
  "pattern": "first.last",
  "confidence": "medium",
  "patternSource": null,
  "patternExample": null,
  "domainHasMx": true,
  "mailProvider": "Proofpoint",
  "candidates": [
    "john.smith@gymshark.com",
    "jsmith@gymshark.com"
  ],
  "checkedAt": "2026-09-21T10:50:34.774Z",
  "reason": "most common pattern; the domain accepts mail"
}

confidenceScore (0-100) is 90 when the company's own site uses that format, and otherwise reflects how common the format is (first.last ≈ 56, first ≈ 38). alternatives lists the next guesses with their scores. mailboxVerified is always false, see below.

confidence is high when the company's own site uses that format, medium when it is the most common format and the domain accepts mail, none when the domain takes no mail at all. Every candidate tried is listed, so you can fall back if the first bounces.

Honest note

No tool can prove a specific mailbox exists without sending to it, and outbound SMTP is blocked on this platform. This gets you the right format and a live domain; your sending tool will confirm the rest.

Pricing — what you pay per person

This Actor uses pay-per-event pricing: no monthly rental, you pay for the results you get. Prices per 1,000 results by Apify plan:

Event	Free plan	Bronze	Silver	Gold+
person — One person looked up: best-guess work email with confidence and the pattern used	$2.00	$1.80	$1.70	$1.60

There is also a small start fee of $0.00005 per GB of memory ($0.00005 per run at the default 1 GB). Platform compute is included in the price — you are not billed separately for run time. Set a maximum total charge on the run if you want a hard cap, and use the input limits to control how much is fetched. The current prices are always on the Pricing tab.

Tips

• Start with a small maxResults (say 20) to check the output, then raise it — you only pay per result.
• Keep the default proxy setting — it is only used as a fallback when a direct request is blocked.
• Rows the Actor cannot read are logged and skipped, never charged — check the run log if a count looks low.

Automate & schedule

Run this Actor on autopilot and pull results into your own stack:

• Apify API — start runs, fetch datasets and manage schedules over REST.
• apify-client for JavaScript and apify-client for Python — official SDKs.
• Schedules — run it on a cron to keep your data fresh.
• Webhooks — trigger downstream actions the moment a run finishes.

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' });
const run = await client.actor('tindacloud/email-finder').call({
    "people": [
        {
            "fullName": "Patrick Collison",
            "domain": "stripe.com"
        },
        {
            "firstName": "Jan",
            "lastName": "Curn",
            "domain": "apify.com"
        }
    ],
    "findPatternFromWebsite": true,
    "useNicknames": true,
    "maxResults": 1000
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Got ${items.length} records`);

Python

from apify_client import ApifyClient

client = ApifyClient("MY_APIFY_TOKEN")
run = client.actor("tindacloud/email-finder").call(run_input={
    "people": [
        {
            "fullName": "Patrick Collison",
            "domain": "stripe.com"
        },
        {
            "firstName": "Jan",
            "lastName": "Curn",
            "domain": "apify.com"
        }
    ],
    "findPatternFromWebsite": True,
    "useNicknames": True,
    "maxResults": 1000
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

cURL — run and get the results in one request:

curl -X POST "https://api.apify.com/v2/acts/tindacloud~email-finder/run-sync-get-dataset-items?token=MY_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"people": [{"fullName": "Patrick Collison", "domain": "stripe.com"}, {"firstName": "Jan", "lastName": "Curn", "domain": "apify.com"}], "findPatternFromWebsite": true, "useNicknames": true, "maxResults": 1000}'

Integrate with any app

Connect the dataset to thousands of apps — no code required:

• Make — multi-step automation scenarios.
• Zapier — push new records straight into your CRM or sheet.
• n8n — self-hosted workflows.
• Slack — get notified when a run finishes or finds something new.
• Google Drive / Sheets — auto-export every run to a spreadsheet.
• Airbyte — pipe results into your data warehouse.
• GitHub — trigger runs from commits or releases.
• Webhooks — call your own endpoint when a run succeeds or fails.

Use with AI assistants (MCP)

The output is clean, LLM-ready JSON. Call this Actor from Claude, ChatGPT, Cursor or any agent framework through the Apify MCP server — ask your assistant to "find the work email of the head of marketing at these five companies" and let it run this Actor for you.

Agent-ready: autonomous payments (x402 & Skyfire)

This Actor is agent-ready — AI agents can discover it, run it and pay for it on their own. It uses pay-per-event pricing and limited permissions, so it qualifies for Apify's agentic payments:

• x402 — an open, HTTP-native payment protocol. Agents pay in USDC through the Apify MCP server — no Apify account needed.
• Skyfire — agent-to-service payments with pre-funded Skyfire tokens.

Building an AI agent, MCP tool or data pipeline? This Actor is ready to plug in and pay as it goes.

Ready-made examples

Open one, change the fields, press Start — nothing to configure:

• Find work email from name and company
• Email pattern finder for a company
• Find emails for a list of sales prospects

Frequently asked questions

Do I need an API key or a login?

No. Paste your input, press Start. There is nothing to connect and no account on the target site to create.

How do I export the results?

Every run produces a dataset you can download as JSON, CSV, Excel, XML or HTML, or read through the Apify API from your own code. You can also connect it to Make, Zapier or n8n.

Can I run this on a schedule?

Yes. Apify schedules run it every hour, day or week without you being there. Each run is independent, so a schedule gives you a fresh snapshot every time.

Can I call it from Python or JavaScript?

Yes — the Apify API runs any Actor and returns the dataset, and the official Python and JavaScript clients wrap it in a few lines. AI agents can call it too, through Apify's MCP server.

What does it cost?

You pay per result, not per hour. Filters are applied before anything is charged, so narrowing the input directly lowers the bill. Pages that cannot be read are reported in the log and never charged.

Is this data public?

Everything collected here is what a company domain shows to anyone without logging in. Check the target site's terms and the rules that apply to you before using the data commercially.

Related scrapers

• Email Verifier & List Cleaner — check a whole list before sending
• Lead Enrichment: Domain to Full Company Record — everything about the company
• LinkedIn Company Scraper — size, industry, HQ