Email Finder with Proof: Name + Domain → Server-Confirmed Address

Give it a person's name and their company's domain. It generates the common address patterns, asks the company's mail server which one exists, and returns the confirmed address with the pattern and a confidence score. No LinkedIn, no scraping, no guessing dressed up as data.

Three promises

1. "found" means the mail server confirmed the mailbox. Not "the pattern looked plausible".
2. Catch-all domains are called out, not faked. When a company accepts every address, we return the most likely pattern as a guess with a low confidence, and say why.
3. It learns. Once a pattern is confirmed at a company, the next person at the same company is checked against that pattern first. Lists with several people per company finish faster and come back with more "found" rows. What's remembered is one fact per domain, such as "first.last", for 90 days. Never a name or an address.

Use cases

• Fill the email column on a prospect list. Names and companies from a conference, a database export or a hiring-signals run; addresses out.
• Reach a specific person. One name, one domain, one confirmed address, with every attempt shown.
• Enrich a CRM on a schedule. Run weekly on new contacts; the learned pattern per company keeps it cheap.
• Agents. Give an agent a person and a company; read back email, status and confidence. Pairs with the Email Verifier and the Hiring Signals Actor for finding hiring managers.

Statuses

Status	Meaning	Confidence
🟢 found	Mail server confirmed this exact mailbox	95
🟡 guess	Catch-all domain, or verification off. Best pattern returned.	25–60
🔴 not_found	No mail server, or every pattern was rejected	0
⚪ unknown	The server would not answer (greylisting, policy block)	20

Input

{
  "people": [
    { "fullName": "Jan Curn", "domain": "apify.com" },
    { "firstName": "Patrick", "lastName": "Collison", "domain": "https://stripe.com" }
  ],
  "verify": true,
  "maxAttempts": 4
}

Names can include titles and accents (Dr. Jan Čurn works). Domains can be bare, a website URL, or an email address at the company.

Output (one item per person)

{
  "fullName": "Jan Curn",
  "domain": "apify.com",
  "email": "jan.curn@apify.com",
  "status": "found",
  "pattern": "first.last",
  "confidence": 95,
  "reason": "mailbox_confirmed",
  "attempts": 1,
  "candidates": [{ "pattern": "first.last", "email": "jan.curn@apify.com", "result": "accepted", "catchAll": false }]
}

candidates lists every address tried and what the server said, so you can see the work.

Patterns tried, in order

first.last, first, flast, firstlast, first_last, last, f.last, firstl, last.first, lastfirst, first-last, lastf. A pattern already confirmed for the domain always goes first.

How this compares

	Pattern-only finders	LinkedIn-based finders	Toolmill Email Finder
Returns an address for almost anyone	✅	✅	✅
Confirms it with the mail server	❌	sometimes	✅
Honest about catch-all domains	❌	❌	✅
Needs cookies, accounts or scraping	no	yes	no
Shows every candidate tried	❌	❌	✅

Pairs with

• Email Verifier re-checks a list you already have.
• Hiring Signals finds the companies that just opened roles; feed their domains here with the hiring manager's name.
• Toolmill Briefs: what each company is building, read from its hiring. Free.

Use it from an AI agent

Works as a tool through the Apify MCP integration. Pass people, get structured results with status, confidence and reason designed to be consumed by code.

Pricing

Pay per result. A confirmed address costs more than a lookup that ends in a guess or nothing, so you pay mostly for what you can use. See the Pricing tab for the exact numbers.

Notes

• Verification uses a mailbox-check provider; no email is ever sent to anyone.
• Stops spending after the first catch-all signal or the first "won't answer" reply on a domain.
• Nothing is stored beyond the run's dataset, except one fact per domain: which pattern was confirmed. No names or addresses are kept.

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