Reverse Email Lookup — Name, LinkedIn, Phone & Company

Reverse Email Lookup — Name, LinkedIn & Phone ✅ Misses Free

Reverse email lookup and enrichment — find the person behind any email: name, company, job title, phone, location and full LinkedIn profile (headline, skills, work history and education). Powered by the Neuralverge API. No login or account required, and you only pay for matches — misses are free. Export to JSON, CSV or Excel.

Ideal for lead enrichment, sales prospecting, KYC/identity resolution, and feeding verified person data to AI agents.

✨ Why this Actor

• 💸 Pay per match returned — one billed row per email resolved to a person. No match → not billed.
• 🧩 Full person profile — name, emails, phones, location, company, and the complete LinkedIn profile: headline, connections, skills, full position history and education.
• 🔓 No login, cookies or account — resolution runs on the Neuralverge backend.
• ⚡ Real-time & structured — fresh data each run, one predictable JSON schema, ready for a spreadsheet, database or AI pipeline (MCP-ready).

🔧 How it works

1. Provide an email — e.g. steve@builder.io.
2. Run the Actor. Resolution and structuring happen on the Neuralverge backend.
3. Get one dataset row — the Neuralverge system output as-is. Export to CSV, JSON, or Excel, or pull it over the Apify API.

Emails that don't resolve to a person are logged and skipped without charge.

Input

One email per run.

Field	Type	Notes
email	string	The email address to look up.

{
  "email": "steve@builder.io"
}

What you'll receive

Each dataset row is { email, machine } — the source email plus the system machine output 1:1. The machine block contains:

• full_names — resolved name(s)
• emails, phones — contact points found
• locations — array of country / state / city
• company, position — current company and title (when available)
• linkedin_profile — the profile URL
• linkedin — full LinkedIn object: displayName, firstName, lastName, headline, companyName, location, photoUrl, connectionCount, skills, schools (education history) and positions (full work history)
• gender, date_of_birth, x_profile, telegram_username — when found (else null)

Example output (real run)

Exactly the dataset row the Actor writes for steve@builder.io: the Neuralverge machine output plus the source email. No wrapper fields (session_id/total_points/human are not included).

{
  "email": "steve@builder.io",
  "machine": {
    "full_names": [
      "Steve Sewell"
    ],
    "gender": null,
    "date_of_birth": null,
    "emails": [
      "steve@builder.io"
    ],
    "phones": [
      "9165058708"
    ],
    "locations": [
      {
        "country": "US",
        "state": "CA",
        "city": "San Francisco"
      },
      {
        "country": "United States",
        "state": "California",
        "city": "San Francisco"
      }
    ],
    "company": "Builder.io",
    "position": null,
    "linkedin_profile": "https://linkedin.com/in/steve8708",
    "linkedin": {
      "id": "urn:li:person:DgHPWIpJV6-oW7iTlnDNcjd0Wqt27YlMrHT4WeyOsYI",
      "displayName": "Steve Sewell",
      "firstName": "Steve",
      "lastName": "Sewell",
      "headline": "CEO @ Builder.io - visually code together",
      "summary": "",
      "companyName": "Builder.io",
      "location": "San Francisco, California, United States",
      "photoUrl": "https://media.licdn.com/dms/image/v2/D5603AQFUtnmLlbPpFw/profile-displayphoto-shrink_400_400/profile-displayphoto-shrink_400_400/0/1702096308767?e=1784660400&v=beta&t=ch7LBKZQDohus1RnwIsVW-MDppZsw8P-xU2Gazt6MiU",
      "profileUrl": "https://linkedin.com/in/steve8708",
      "reportProfileUrl": "https://linkedin.com/in/steve8708/report",
      "connectionCount": 500,
      "isConnectionCountObfuscated": true,
      "skills": [
        "Express.js",
        "Node.js",
        "SEO",
        "Product Management",
        "Adobe Creative Suite",
        "Product Design",
        "Product Development",
        "Mobile Applications",
        "CSS3",
        "Single Page Applications",
        "Startups",
        "User Interface Design",
        "HTML 5",
        "User Experience",
        "Interaction Design",
        "JavaScript",
        "jQuery",
        "Photoshop",
        "Agile Methodologies",
        "Backbone.js",
        "Angular.js",
        "Web Applications",
        "Agile Development"
      ],
      "locale": {
        "country": "us",
        "language": "en"
      },
      "schools": {
        "educationsCount": 1,
        "educationHistory": [
          {
            "startEndDate": {
              "start": {
                "year": 2008
              },
              "end": {
                "year": 2010
              }
            },
            "schoolName": "University of California, Berkeley",
            "schoolLocation": "Berkeley, California, United States",
            "schoolLogo": "https://media.licdn.com/dms/image/v2/D560BAQGwjF_5CYj_JQ/company-logo_400_400/company-logo_400_400/0/1732135669731/uc_berkeley_logo?e=1784660400&v=beta&t=Mz1ZNJjtNEx_IPDMmBm66lvET7Xm-Aya62qE7ISJxVw",
            "linkedInUrl": "https://www.linkedin.com/company/uc-berkeley"
          }
        ]
      },
      "positions": {
        "positionsCount": 4,
        "positionHistory": [
          {
            "title": "Co-Founder, CEO",
            "startEndDate": {
              "start": {
                "month": 9,
                "year": 2019
              },
              "end": {}
            },
            "description": "Convert designs to code to live pages in record time",
            "companyName": "Builder.io",
            "companyLocation": "San Francisco Bay Area",
            "companyLogo": "https://media.licdn.com/dms/image/v2/D560BAQF5e4P00Nd5IQ/company-logo_400_400/B56Z0DBIWCHoAc-/0/1773872121522/builder_io_logo?e=1784660400&v=beta&t=3Yd_ASfggYB8pGzbSKS33OKur2Grq4sPnXpN6hfvQMc",
            "linkedInUrl": "https://www.linkedin.com/company/builder-io"
          },
          {
            "title": "Engineering manager, web",
            "startEndDate": {
              "start": {
                "month": 1,
                "year": 2014
              },
              "end": {
                "month": 4,
                "year": 2016
              }
            },
            "description": "I lead our web applications engineering teams, all built on Angular + Node.js. Lead replatform + rebuild projects shopstyle.com, shopstylecollective.com, and other international ShopStyle sites",
            "companyName": "ShopStyle, Inc.",
            "companyLogo": "https://media.licdn.com/dms/image/v2/C560BAQHcphCGvisw2Q/company-logo_400_400/company-logo_400_400/0/1656741393081?e=1784660400&v=beta&t=AwwTHmehhBMBTH_loJIaUhutFnBg2f2__ZLR1GMTbDc",
            "linkedInUrl": "https://www.linkedin.com/company/shopstyle"
          },
          {
            "title": "Head of Product Development",
            "startEndDate": {
              "start": {
                "month": 7,
                "year": 2012
              },
              "end": {
                "month": 12,
                "year": 2013
              }
            },
            "description": "Designed and built PICT web and mobile apps. Acquired by ShopStyle (now Rakuten)",
            "companyName": "PICT",
            "companyLocation": "san francisco bay area",
            "linkedInUrl": "https://www.linkedin.com/search/results/companies/?keywords=PICT"
          }
        ]
      }
    },
    "x_profile": null,
    "telegram_username": null
  }
}

A real match. The dataset row is { email, machine } — machine is the Neuralverge system output 1:1. No wrapper fields (session_id/total_points/human). Fields not found come back as null.

Pricing

Pay per event — $0.005 per run, plus $0.010 per match ($10 per 1,000) returned to the dataset. A miss costs only the $0.005 lookup fee — you are never charged the per-result price.

Event	Price
Lookup (per run)	$0.005
Match returned (per dataset row)	$0.010

Emails that don't resolve are not charged the per-result price — only the $0.005 lookup fee applies. Pricing is on top of your Apify platform usage.

Free plan limits

Users on any paid Apify plan are not affected by anything in this section.

On the Apify Free plan all Neuralverge Actors share one budget, per user and per calendar month: 15 runs in total, at most 5 of them on this Actor, and 35 returned rows. A run that finds nothing still counts, because the lookup is performed either way. LinkedIn People Search is metered differently — one run there uses 25 of the 35 rows, because a full page of 25 profiles is bought upstream whether or not all of them are returned. When a limit is reached the Actor stops gracefully with a status message naming it; everything resets on the 1st of every month, and any paid Apify plan removes all of it.

Integrations & API

Results are stored in a standard Apify dataset — export as CSV, JSON, XML or Excel, or fetch on demand through the Apify API. The Actor also plugs into Apify's integrations (Make, Zapier, n8n, webhooks) and can be called from any MCP client to give an AI agent live person data.

FAQ

Do I need any account or login? No. Resolution runs on the Neuralverge backend — you never provide credentials.

What if the email doesn't resolve? You're not charged. Only matched emails are billed.

Is the full LinkedIn profile included? Yes, when found — under linkedin, with headline, skills, full positions (work history) and schools (education).

How fresh is the data? Each run resolves the email at run time.

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Disclaimer: This Actor is an independent tool. Use enriched personal data in compliance with applicable laws (GDPR, CCPA and similar). All trademarks are property of their respective owners.