# Reverse Email Lookup — Name, LinkedIn & Phone ✅ Misses Free (`neuralverge/neuralverge-email-enrichment`) Actor Reverse email lookup and enrichment — find the person behind any email: name, company, job title, phone and full LinkedIn profile. Pay only for matches; misses are free. - **URL**: https://apify.com/neuralverge/neuralverge-email-enrichment.md - **Developed by:** [NeuralVerge](https://apify.com/neuralverge) (community) - **Categories:** Lead generation, Automation, Social media - **Stats:** 10 total users, 8 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $10.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ### Reverse Email Lookup — Name, LinkedIn & Phone ✅ Misses Free Reverse email lookup and enrichment in one call — find the person behind an email address. Give it one email and get back **full name, company, job title, location and phone** — plus, when available, the person's **full LinkedIn profile** (headline, work history, education and skills) — as one clean, enriched row. Runs on the Neuralverge engine, so there's **no login, cookies, proxy or API key to configure.** Use it from the UI, the Apify API, or any MCP client, and **pay only when a person is found — misses are free.** ### ✨ Why this Actor - 💸 **Misses are free** — you're charged only when an email resolves to a person. No match, no charge, no empty billable rows. - 📇 **The person, not just an "OSINT hit"** — most email tools only tell you *which sites* an address shows up on. This returns the actual person: `fullName`, `company`, `title`, `phone`, `location` and `linkedin`. - 🔗 **Full LinkedIn profile when found** — up to 20+ structured fields when available: headline, current role, skills and school at the top level, plus the complete positions & education history under `raw`. - ⚡ **Real-time & structured** — every email is resolved live at run time (no stale cache) and returned as clean JSON, ready for CSV/Excel, the Apify API, or an AI agent over MCP. - 🔑 **No login, cookies, proxy or API key** — nothing to configure. ### 🔧 How it works 1. **Provide an email address** in the `email` field. 2. **Run the Actor.** The email is resolved live on the Neuralverge backend. 3. **Get one dataset row per matched person**, with key fields at the top level and the full response attached. Export to CSV, JSON, or Excel, or pull it over the Apify API. If the email resolves to no person, it's logged and **skipped without charge**. ### 💡 Use it for - **Inbound lead routing** — enrich sign-ups and demo requests the moment an email hits your form. - **CRM enrichment** — fill in name, title, company, phone and LinkedIn on thin records. - **Sales prospecting** — turn a list of addresses into people with real role and company context. - **Recruiting** — put a name, background and profile to a candidate's email. - **Trust & anti-fraud checks** — confirm an email maps to a real, consistent identity. ### Input One email per run. | Field | Type | Notes | |---|---|---| | `email` | string | The email address to enrich. | ```json { "email": "steve@builder.io" } ```` > **Accepts any email — business or personal.** You're billed only for addresses that > resolve to a person, so there's no downside to trying one you're unsure about. ### What you'll receive Up to 20+ structured fields per matched person, when available: - **Person** — `fullName`, `firstName`, `lastName`, `gender`, `dateOfBirth`, `photoUrl` - **Contact** — `email`, `emails`, `phone`, `phones` - **Location** — `city`, `state`, `country`, `location` - **Work** — `title`, `headline`, `company` - **LinkedIn** — `linkedin` (profile URL), `connectionCount`, `school`, `skills`; the complete positions & education history under `raw.machine.linkedin` - **Social (when found)** — `xProfile`, `telegram` - **Meta** — `query` (input email), `scrapedAt`, `human` (markdown summary) and the full response under `raw` #### Example output Key fields are flattened to the top level for convenience; the complete, unmodified API response is attached under `raw`. ```json { "query": "steve@builder.io", "scrapedAt": "2026-07-17T10:42:00.000Z", "fullName": "Steve Sewell", "firstName": "Steve", "lastName": "Sewell", "title": "Co-Founder, CEO", "headline": "CEO @ Builder.io - visually code together", "company": "Builder.io", "email": "steve@builder.io", "emails": "steve@builder.io", "phone": "9165058708", "phones": "9165058708", "city": "San Francisco", "state": "CA", "country": "US", "location": "San Francisco, California, United States", "linkedin": "https://linkedin.com/in/steve8708", "xProfile": null, "telegram": null, "gender": null, "dateOfBirth": null, "photoUrl": "https://media.licdn.com/dms/image/v2/D5603AQFUtnmLlbPpFw/profile-displayphoto-shrink_400_400/profile-displayphoto-shrink_400_400/0/1702096308767?e=1784048400&v=beta&t=rlJxsx6Mm4-fmVjBgOnvLmsJ8XS2SKZfn1iMOmXw7r8", "connectionCount": 500, "school": "University of California, Berkeley", "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", "human": "# Email enrichment\n\n- **Input Email:** steve@builder.io\n- **Full names:** Steve Sewell\n- **Gender:** Not found\n- **Date of birth:** Not found\n- **Emails:** steve@builder.io\n- **Phones:** 9165058708\n- **Locations:** US, CA, San Francisco; United States, California, San Francisco\n- **Company:** Builder.io\n- **LinkedIn profile:** https://linkedin.com/in/steve8708\n- **X profile:** Not found\n- **Telegram username:** Not found", "raw": { "session_id": "90237d1c-8a18-4ac7-898c-120d202bd28d", "kind": "email_enrichment", "email": "steve@builder.io", "human": "# Email enrichment\n\n- **Input Email:** steve@builder.io\n- **Full names:** Steve Sewell\n- **Gender:** Not found\n- **Date of birth:** Not found\n- **Emails:** steve@builder.io\n- **Phones:** 9165058708\n- **Locations:** US, CA, San Francisco; United States, California, San Francisco\n- **Company:** Builder.io\n- **LinkedIn profile:** https://linkedin.com/in/steve8708\n- **X profile:** Not found\n- **Telegram username:** Not found", "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=1784048400&v=beta&t=rlJxsx6Mm4-fmVjBgOnvLmsJ8XS2SKZfn1iMOmXw7r8", "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=1784048400&v=beta&t=o-xK_torfvg3VWGvuVA2dRsWS2VV6UVuGRY8jXqh3sE", "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", "companyLogo": "https://media.licdn.com/dms/image/v2/D560BAQF5e4P00Nd5IQ/company-logo_400_400/B56Z0DBIWCHoAc-/0/1773872121522/builder_io_logo?e=1784048400&v=beta&t=hYXKJEN_oSwE6F4CqRbqljftNz7hwCJgUNVVpf65a98", "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=1784048400&v=beta&t=DSYnwF_czOgaX8B51WRNCUfsrZinjNlwTfWaJyaAc0I", "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", "linkedInUrl": "https://www.linkedin.com/search/results/companies/?keywords=PICT" } ] } }, "x_profile": null, "telegram_username": null }, "total_points": 10 } } ``` ### Pricing **$0.010 per matched email** ($10 per 1,000) returned to the dataset. **You pay only when a person is found — unresolved emails are free.** | Event | Price | |---|---| | Actor start | Free | | Matched person returned (per dataset row) | **$0.010** | Competitive for the niche: reverse-email tools on Apify range from ~$5 to $20 per 1,000, and data-provider wrappers reach $150. Emails that resolve to no person are **not billed**. Pricing is on top of your Apify platform usage. **Not sure an address will resolve?** Try it on an email you already know. If we can't match it to a person, no row is written and **you pay nothing.** ### Run it over the API & MCP Results are stored in a standard Apify dataset — export as CSV, JSON, XML or Excel, or fetch on demand through the [Apify API](https://docs.apify.com/api). Call the Actor synchronously and get the enriched person back in a single request: ```bash curl -X POST "https://api.apify.com/v2/acts/neuralverge~neuralverge-email-enrichment/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "email": "steve@builder.io" }' ``` The Actor also plugs into Apify's integrations (Make, Zapier, n8n, webhooks) and can be called from any [MCP](https://mcp.apify.com/) client to give an AI agent a live people-lookup tool. ### Data & compliance Data is compiled from publicly available sources and resolved at request time. You are responsible for ensuring a lawful basis for processing personal data under applicable privacy laws (e.g. GDPR / CCPA) and for using the results only for permitted purposes. ### FAQ **What do I get back from an email?** The person behind it: name, company, job title, phone and location — plus their LinkedIn profile (headline, skills, school) when found. The complete work history and education are attached under `raw`. **Is this email enrichment?** Yes — it's reverse email enrichment: instead of just verifying an address, it enriches it into a full person record (name, company, title, phone, location and LinkedIn). You're charged only when an email actually enriches to a person. **Which emails work best?** Any email works as an input, and you're charged only when one resolves to a person. Work addresses typically return the fullest profiles; anything that doesn't resolve costs nothing. **Do I need an API key, login or proxy?** No. The lookup runs on the Neuralverge engine — you never provide credentials, cookies or a proxy. **Am I charged if an email isn't matched?** No. You're billed only for rows returned to the dataset, i.e. when at least a name is found. **Is this compliant?** The Actor returns data compiled from publicly available sources, resolved at request time. You're responsible for having a lawful basis for processing personal data (e.g. legitimate interest under GDPR, or CCPA compliance) and for using results only for permitted purposes such as B2B outreach, verification or recruiting. **How fast is it, and can I run it at volume?** Each lookup resolves in real time, usually in a few seconds. Run one email per run and parallelise across runs; your standard Apify account concurrency and rate limits apply. **How is this different from the LinkedIn Email Scraper?** This runs **email → person**. If you already have a LinkedIn URL and want the work email, use the LinkedIn Email Scraper instead — that's the opposite direction. **Is the data live?** Yes — every email is resolved at run time, not served from a stale cache. *** **Disclaimer:** This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by any platform whose data may appear in results. LinkedIn® is a registered trademark of LinkedIn Corporation; all trademarks are the property of their respective owners. Use the Actor in accordance with applicable law and the Neuralverge Terms of Service. # Actor input Schema ## `email` (type: `string`): The email address to enrich (one per run). ## Actor input object example ```json { "email": "steve@builder.io" } ``` # Actor output Schema ## `results` (type: `string`): Structured person + company data (name, title, company, phone, location, LinkedIn), one row per matched email. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "email": "steve@builder.io" }; // Run the Actor and wait for it to finish const run = await client.actor("neuralverge/neuralverge-email-enrichment").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "email": "steve@builder.io" } # Run the Actor and wait for it to finish run = client.actor("neuralverge/neuralverge-email-enrichment").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "email": "steve@builder.io" }' | apify call neuralverge/neuralverge-email-enrichment --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=neuralverge/neuralverge-email-enrichment", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reverse Email Lookup — Name, LinkedIn & Phone ✅ Misses Free", "description": "Reverse email lookup and enrichment — find the person behind any email: name, company, job title, phone and full LinkedIn profile. Pay only for matches; misses are free.", "version": "0.1", "x-build-id": "VszI7FFHN3R5z4eWw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/neuralverge~neuralverge-email-enrichment/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-neuralverge-neuralverge-email-enrichment", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/neuralverge~neuralverge-email-enrichment/runs": { "post": { "operationId": "runs-sync-neuralverge-neuralverge-email-enrichment", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/neuralverge~neuralverge-email-enrichment/run-sync": { "post": { "operationId": "run-sync-neuralverge-neuralverge-email-enrichment", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "email": { "title": "Email address", "type": "string", "description": "The email address to enrich (one per run)." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```