Company Team & Decision-Maker Finder: Names, Titles, Emails

Find the people behind a company from its own website. Give it company domains and Company Team & Decision-Maker Finder reads each company's public team, leadership, about, staff, attorney and partner pages. It returns every person it finds with name, job title, seniority, department, decision-maker flag, published email, LinkedIn and bio links. It also works out the company's email pattern from the emails the site publishes. Results come as Excel and CSV. Apify's free plan includes $5 of monthly platform credit, enough for about 2,500 people at $0.002 each (pricing below).

No LinkedIn scraping, no logins, no cookies, no proxies: only the company's own public pages, with robots.txt respected.

Most "employee finder" tools scrape LinkedIn, which breaks often, needs accounts and puts you at risk. Small and mid-size companies, agencies, law and accounting firms, clinics, VCs and nonprofits already list their leaders on their own site. Company Team Finder turns those pages into a clean contact sheet:

• 👥 People from company sites: name, title and bio-page link from team / leadership / about / staff pages (and schema.org Person data)
• 🎯 Decision makers: seniority (C-level, founder/owner, president, partner, VP, director, manager) and an isDecisionMaker flag
• 🏷️ Department guess: executive, sales, marketing, engineering, product, finance, operations, HR, legal, customer success, medical, research
• ✉️ Emails: published emails when the site shows them; otherwise the company's email pattern (first.last, flast, first…) learned from its own published emails, or a clearly labeled unverified first.last guess when the domain accepts email
• 🔗 LinkedIn and bio links exactly as linked from the team page
• 🧹 Testimonials filtered: "CEO of SomeClient" quotes and case-study names are skipped
• 🧮 Filters: decision makers only, title keywords, departments, max people per company
• 💸 $0.002 per person. 100 companies × 10 people cost $2. Companies with no readable team page cost nothing

Who it's for

• SDRs and founders doing outbound: get the right names and titles for an account list in minutes
• Agencies and recruiters: map the leadership of target firms (law, accounting, agencies, clinics, startups)
• Investors and M&A teams: see who runs each company in a pipeline
• RevOps and data teams: add people to CRM accounts that only have a domain
• AI agents: a reliable "who runs X and what's their title?" tool that never needs a login

How to use it

1. Click Try for free.
2. Paste company websites, one per line (domains, URLs, or a work email). If you know the exact team page, paste that URL.
3. Optionally turn on Decision makers only or add title keywords (e.g. marketing, sales).
4. Click Start. 50 companies take about 2 minutes. Download PEOPLE_XLSX or PEOPLE_CSV from Storage → Key-value store, or use the dataset via API.

Input example

{
  "companies": ["sparkbox.com", "viget.com", "https://www.fishmanhaygood.com/attorneys/"],
  "decisionMakersOnly": true,
  "maxPeoplePerCompany": 20
}

Task examples

• Account list → decision makers: your 200 target domains with decisionMakersOnly: true; import the Excel into your CRM.
• Marketing leaders only: {"companies": [...], "titleKeywords": ["marketing", "growth", "brand"]}.
• Law firm partners: paste the firms' attorney-page URLs; filter by seniority: partner.
• VC / accelerator partners: ["ycombinator.com", "a16z.com"] for the partner list with titles.
• Chain it: run Company Website Enricher for tech stack and socials, and Company Hiring Signals to see who is hiring, then find the people here.

Output example

One row per person. An illustrative row (the person and company are made up):

{
  "company": "Example Co",
  "domain": "example.com",
  "name": "Jane Example",
  "firstName": "Jane",
  "lastName": "Example",
  "title": "Vice President of Business Development",
  "seniority": "vp",
  "department": "sales",
  "isDecisionMaker": true,
  "email": null,
  "emailGuess": "jane.example@example.com",
  "emailConfidence": "unverified common pattern",
  "linkedinUrl": null,
  "profileUrl": "https://example.com/team/jane-example",
  "sourceUrl": "https://example.com/our-team",
  "foundVia": "page",
  "agentSummary": "Jane Example: Vice President of Business Development at Example Co (vp, sales); likely email jane.example@example.com (unverified common pattern); source https://example.com/our-team"
}

Fields

Field	What it is
company, domain	Company name (from the site) and domain
name, firstName, lastName, title	The person as listed on the site
seniority, department, isDecisionMaker	Guessed from the title
email, emailGuess, emailConfidence	Published email; or a pattern email with how sure we are (pattern from N published emails or unverified common pattern)
linkedinUrl, profileUrl, otherLinks	Links from the person's card on the team page
sourceUrl, foundVia	The page the person was found on; page or schema.org
agentSummary	One plain-English line per person

Files in the key-value store

Key	What it is
PEOPLE_XLSX	Excel workbook: People (decision makers highlighted), Companies (team pages found, email pattern, status), Run log, Read me
PEOPLE_CSV	People table as CSV
SUMMARY	JSON: per-company status, topPeople, a one-line takeaway and nextStep

For AI agents

Use this Actor to answer "who are the leaders / decision makers at

Minimal input:

{"companies": ["sparkbox.com"], "decisionMakersOnly": true}

Each dataset item includes:

• agentSummary: one line with name, title, company, seniority, email and source page
• seniority, isDecisionMaker, department: for filtering
• email (published) vs emailGuess + emailConfidence: never mix them up; verify guesses before sending

The run's key-value store has a SUMMARY record with every company's status (team pages found, or why none were), topPeople, a one-line takeaway and nextStep.

Pricing

Apify paid-plan discounts: Bronze members pay 10% less, Silver 20% less and Gold 30% less per person. Free-plan prices are shown below; the discount applies automatically.

$0.002 per person returned (pay-per-event), plus a tiny Actor-start fee of $0.00005. Titles, seniority, emails, links, Excel, CSV and summary are included. Companies where nobody is found, and people removed by your filters, cost nothing. Your maximum charge per run is respected.

FAQ

Does it scrape LinkedIn? No. It only reads the company's own public website. LinkedIn URLs come from links the company itself put on its team page.

Why did a company return nobody? Some sites have no team page, or load it only with JavaScript, or block crawlers in robots.txt. Those companies are listed in the Companies sheet with the reason and are free. If you know the team page URL, paste it directly.

How accurate are the emails? email is published on the site. emailGuess follows the pattern seen in the company's own published emails when there is evidence; otherwise it is the common first.last pattern, labeled unverified. Verify before you send, and follow CAN-SPAM / GDPR rules for B2B outreach.

Can it find people at very large companies? It finds whoever the company lists publicly (usually the leadership team). For full employee lists, large companies are better served by other sources.

Is this legal? It reads public business information that companies publish about their own staff, respects robots.txt and does not log in anywhere. Use the data for legitimate B2B purposes and honor opt-outs.

Can I use it from code or an AI agent? Yes, via the Apify API, the Python/JS clients, or as a tool through Apify's MCP server.

More Panda Federation tools

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• Company Hiring Signals
• Email Domain Security Checker
• Trucking Company Leads (FMCSA)
• Local Business Leads

All Panda Federation Actors on Apify

Questions or ideas? Open an issue on this Actor's Issues tab.

Changelog

• 2026-11-03: First public release: team / leadership / about / staff page discovery (robots.txt respected), people from page cards and schema.org, testimonial filter, seniority and department, decision-maker filter, title and department filters, email pattern detection, LinkedIn and bio links, Excel and CSV, agent-friendly agentSummary and takeaway, pay-per-event pricing with Bronze/Silver/Gold discounts.