Namewhere: company name to domain & website finder

Turn a list of company names into their official website domains, with a confidence score and the evidence behind every answer. Namewhere is a drop-in replacement for Clearbit's NameToDomain / Autocomplete lookups: give it "Acme Brick Company, Inc." and it returns brick.com, tells you why (Wikidata's company record, the homepage calling itself "Acme Brick", acmebrick.com redirecting there), lists runner-up domains, and skips parked or for-sale lookalikes.

Built for CRM and lead enrichment, AI agents that need a domain before calling other tools, and data cleaning at scale. $0.0008 per confident match; misses, low-confidence and invalid names are free.

What you get (one record per company)

• domain and website: the official domain (brick.com) and the homepage URL after redirects.
• confidence (0–0.99) and confidenceLabel (high / medium / low), plus status: resolved (at or above your minimum, charged), low-confidence (best guess, free), not-found, invalid.
• evidence: the Wikidata record it matched (ID, label, description, country check), how well the domain spells the name, and what the homepage calls itself (title, og:site_name, JSON-LD organisation name) with a brand-match score.
• sources: wikidata, dns-guess, redirect-from:<domain>, input.
• companyName and description: the official name and a one-line description.
• socials: LinkedIn, X, Facebook, Instagram, YouTube, TikTok and GitHub profiles linked from the homepage (share buttons are ignored).
• alternatives: runner-up domains with their confidence (country sites, group vs. consumer sites, sister companies).
• rejected: domains it checked and threw out, and why (parked, for sale, dead).
• ambiguous: true when two different live companies share the exact name and nothing breaks the tie.

How it decides (no search-engine scraping)

1. Wikidata company records (CC0): entities whose name matches and that state an official website, preferring organisations over people or films, and your country if you give one.
2. Likely domains: name.com, the country's domains (.co.uk, .de…), .io, .co, .ai, brand TLDs (octopus.energy), shortened forms (Figma Technologies → figma.com). Only domains that exist in DNS are visited.
3. Homepage check for every candidate: is it live, parked or for sale, where does it redirect, and does the page call itself by the company's name?
4. The evidence is combined into one confidence score. A domain that merely exists scores low; a domain Wikidata names and whose homepage says the company's name scores 0.99.

Ready-made inputs (first try in one click)

Four well-known names (a few seconds, under $0.004):

{ "companies": ["Stripe", "Acme Brick Company, Inc.", "Monzo Bank | gb", "GW&K Investment Management"] }

Strict CRM write, UK companies:

{ "companies": ["Hiscox", "Octopus Energy", "Revolut Ltd."], "country": "gb", "minConfidence": 0.8 }

Watch a list and return only companies whose domain changed (pair with a weekly Schedule):

{ "companies": ["Notion", "Figma Technologies Inc", "Linear"], "monitor": true, "monitorKey": "crm-names" }

Input

{
  "companies": ["Stripe", "Acme Brick Company, Inc.", "Monzo Bank | gb", "jane@figma.com"],
  "country": "us",
  "minConfidence": 0.6
}

Field	Default	What it does
companies	required	One name per line. Legal forms (Inc, LLC, GmbH, Ltd, S.A.…) are handled. Add a country after a bar ("Monzo Bank | gb") or pass objects {"name": "Hiscox", "country": "gb"}. A domain, URL or email is just verified.
country	none	Two-letter default country for names without one: tries its domains and prefers companies registered there.
minConfidence	0.6	Threshold for resolved (charged). Use 0.8 for strict CRM writes.
maxAlternatives	3	Runner-up domains per company.
includeSocials	true	Social profile links from the homepage.
useWikidata / guessDomains	true / true	Turn either source off.
monitor / monitorKey	false / auto	Only return companies that are new or whose domain changed since the last run.
maxConcurrency	6	Companies in parallel.
timeoutSecs	8	Per request.

Output (real record from an Apify run, 24 Sep 2026)

{
  "input": "Stripe",
  "status": "resolved",
  "domain": "stripe.com",
  "website": "https://stripe.com/",
  "confidence": 0.99,
  "confidenceLabel": "high",
  "companyName": "Stripe",
  "description": "Irish-American payment technology company",
  "sources": ["dns-guess", "redirect-from:stripe.io", "redirect-from:stripe.net", "wikidata"],
  "evidence": {
    "wikidata": { "id": "Q7624104", "label": "Stripe", "nameMatch": 1, "countryMatch": null },
    "domainNameMatch": 1,
    "homepage": { "reachable": true, "title": "Stripe | Financial Infrastructure to Grow Your Revenue", "brandMatch": 1, "matchedField": "orgName" }
  },
  "socials": {
    "linkedin": "https://www.linkedin.com/company/stripe",
    "x": "https://twitter.com/stripe",
    "github": "https://github.com/stripe"
  },
  "rejected": [{ "domain": "stripe.org", "reason": "parked, for sale or redirects to a third-party page" }]
}

More real output: examples/real-run-benchmark-8.json.

Benchmark (24 Sep 2026, same 8 names, on Apify)

Names: Stripe, Acme Brick Company, Monzo Bank, Gusto, Linear, Blue Bottle Coffee, Octopus Energy, Basecamp. Correct = the company's own website.

Actor	Correct	Wrong answers	Run time	Cost for the 8
Namewhere	8/8	0	21 s	$0.0064
Top rival by users (4 GB, search-based)	6/8	2 (Monzo → a comparison site; Blue Bottle → a kids' TV site)	60 s	$0.032
Cheapest rival ($0.001/match)	6/8	1 (Gusto → gusto.co.uk, a different company), 1 not found	9 s	$0.006
Rival with evidence scores	5/8	1 (Monzo → a comparison site), 2 not found	5 s	$0.005

A harder set of 40 names (legal names like "Alphabet Inc.", "Meta Platforms, Inc.", "Nestlé S.A.", "International Business Machines Corporation", plus startups and UK/German firms): 39/40 correct in one 134 s run (abc.xyz, meta.com, nestle.com, ibm.com, notion.com, shopify.com…). The one miss, "Revolut Ltd" → revolut.io, came back flagged ambiguous: true with revolut.com as the first alternative. Browse all 40 results.

Octopus Energy: Namewhere returns the group site octopusenergy.group (Wikidata's official website) with the consumer site octopus.energy as the first alternative. Rival costs are their listed Store prices at the time. Namewhere is slower than the fastest rivals because it checks every candidate homepage; that check is what keeps parked domains and namesakes out.

Pricing

$0.0008 per company resolved at or above your minConfidence. Low-confidence guesses, not-found and invalid names are returned free. No start fee. 1,000 matched companies = $0.80.

Run it on a schedule

Companies rebrand, get acquired and move domains. Save a task with "monitor": true and a monitorKey, then add an Apify Schedule (for example weekly on Monday 06:00). Each run returns and charges only companies that are new to the list or whose domain changed, with change: "changed" and changes.domain.from/to.

{ "companies": ["...your account list..."], "monitor": true, "monitorKey": "crm-accounts", "minConfidence": 0.8 }

Integrations

Make: Apify app → "Run an Actor" (Actor cybermax/company-to-domain, input {"companies":["{{company}}"]}, run synchronously) → "Get dataset items" → update the CRM record's website field.

Zapier: Apify app → "Run Actor" with {"companies":["{{Company Name}}"],"minConfidence":0.8} on every new lead that has a company but no website.

n8n / any HTTP client:

POST https://api.apify.com/v2/acts/cybermax~company-to-domain/run-sync-get-dataset-items?token=YOUR_TOKEN
{"companies": ["Acme Brick Company", "Monzo Bank | gb"]}

Google Sheets: =IMPORTDATA("https://api.apify.com/v2/acts/cybermax~company-to-domain/runs/last/dataset/items?format=csv&fields=input,domain,confidence,status&token=YOUR_TOKEN")

Python:

from apify_client import ApifyClient
client = ApifyClient("YOUR_TOKEN")
run = client.actor("cybermax/company-to-domain").call(run_input={"companies": open("companies.txt").read().splitlines()})
for r in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(r["input"], r["domain"], r["confidence"], r["status"])

JavaScript:

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('cybermax/company-to-domain').call({ companies: ['Stripe', 'Basecamp'] });
const { items } = await client.dataset(run.defaultDatasetId).listItems();

AI agents (MCP): Namewhere is a tool on Apify's hosted MCP server, https://mcp.apify.com/?tools=cybermax/company-to-domain (header Authorization: Bearer <your Apify token>).

{ "mcpServers": { "namewhere": { "url": "https://mcp.apify.com/?tools=cybermax/company-to-domain",
  "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" } } } }

Example prompts: "What's the website of Acme Brick Company?", "Find the domains for these 300 companies from my trade-show list and flag the unsure ones.", "Get the official domain for Monzo, then find its tech stack."

Common uses

• CRM and lead enrichment: fill the website field for accounts that only have a name, before running email, tech-stack or logo tools that need a domain.
• Data cleaning: match messy company names from forms, trade-show lists or invoices to one canonical domain.
• AI agents: a reliable first step that turns "the company the user mentioned" into a domain other tools can use.
• Replacing Clearbit NameToDomain: same job, with evidence and confidence you can audit.

When NOT to use Namewhere

• You already have emails or URLs: extract the domain directly (Namewhere will just verify it).
• Tiny local businesses with no website of their own, or whose site lives on a builder subdomain (Wix, Shopify stores): expect not-found.
• You need people, emails or firmographics: use a contact or enrichment tool after this step.
• You need search-engine rankings or "who ranks for this name": Namewhere doesn't scrape search engines.

FAQ

What does a miss cost? Nothing. Only resolved rows (at or above minConfidence) are charged; low-confidence, not-found and invalid are free.

Names with "&" or initials? Handled the way companies write their domains: "GW&K Investment Management" → gwkinvest.com, "AT&T" → att.com, "Ben & Jerry's" → benjerry.com.

Do you use Google or Bing? No search-engine scraping: Wikidata (CC0), DNS and the candidate sites' own homepages only, so results are stable and cheap.

Two companies share a name. Which do I get? The one matching your country if you give one; otherwise ambiguous: true with the runner-up in alternatives.

Also from CyberMax

• Logolark — company logo API & favicon finder: the logo and brand colour for each domain you just found.
• DomainDNA — tech stack, email security & domain age: what each company runs on.
• Hollerdex — website emails, phones & socials: contact details for every resolved domain.
• HireHeat — company hiring signals by domain: who's hiring, and for what.

All tools: Boardroom Buys · Swellmeter · SnapScout · Gripeline · Keyfern · Linkheft · Printwren · Inkpluck · Pinloft · Ziplore

Data, license and attribution

Company records come from Wikidata (CC0) through its public API, rate-limited politely. Homepages are visited once per candidate with an identifying User-Agent; only public pages are read. No search engines are scraped and no personal data is collected.

© 2026 CyberMax. All rights reserved.

Changelog

• 25 Sep 2026: names with "&" between initials resolve (GW&K Investment Management → gwkinvest.com, H&M → hm.com, AT&T → att.com); regression tests added.
• 0.1 (24 Sep 2026): first release (build 0.1.6). Wikidata + verified domain candidates, confidence and evidence, parked-domain filter, brand TLDs, social links, monitor mode.