# Reverse Phone Lookup — Name, Email & Location ✅ Misses Free (`neuralverge/neuralverge-phone-enrichment`) Actor Reverse phone lookup and enrichment — find the person behind any number: name, email, location, company and carrier, plus a LinkedIn or social profile when available. Pay only for matches; misses are free. - **URL**: https://apify.com/neuralverge/neuralverge-phone-enrichment.md - **Developed by:** [NeuralVerge](https://apify.com/neuralverge) (community) - **Categories:** Lead generation, Automation, Social media - **Stats:** 6 total users, 4 monthly users, 96.9% 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Phone Lookup — Name, Email & Location ✅ Misses Free Reverse phone lookup and enrichment in one call: find the person behind a phone number. Returns **full name, emails, location, company and carrier** — and, in some cases, links to their **LinkedIn and social profiles** — as one clean row per number. Powered by the Neuralverge API. **No login, cookies or proxy**, and **you pay only when a person is found — misses are free.** ### ✨ Why this Actor - 💸 **Misses are free** — you're charged only when a number resolves to a person. No match, no charge; no empty billable rows. - 📇 **The person, not just a carrier** — `fullName`, `email`/`emails`, `city`/`state`/`country`, `company` and `operator` (carrier) in one structured row. - 🔗 **Social profiles when we find them** — some numbers also resolve a `linkedin`, `x` or `telegram` profile (with headline, positions, skills and schools). It's a bonus when available, not guaranteed for every number. - 🔑 **No login, cookies or proxy** — nothing to configure; the lookup runs on the Neuralverge backend. ### 🔧 How it works 1. **Provide a phone number** — any format works: E.164 (`+14155550123`) or plain digits (`14155550123`). The Actor strips `+`, spaces, dashes and parentheses automatically. 2. **Run the Actor.** The lookup runs 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 number resolves to no person, it's logged and **skipped without charge**. ### Input One number per run. | Field | Type | Notes | |---|---|---| | `phone` | string | The phone number to look up. Any format — digits are extracted automatically. | ```json { "phone": "+14155550123" } ```` > Include the country code for the best match rate. ### What you'll receive Each row returns, when available for the number: - **Person** — `fullName`, `firstName`, `lastName`, `gender`, `dateOfBirth`, `photoUrl` - **Contact** — `email`, `emails`, `phone`, `phones` - **Location** — `city`, `state`, `country`, `location` - **Work** — `title`, `headline`, `company` - **Line** — `operator` (carrier) - **Social (when found)** — `linkedin` (profile URL), plus `connectionCount`, `school`, `skills`; `xProfile`, `telegram` - **Meta** — `query` (input number), `scrapedAt`, `human` (markdown summary) and the full response under `raw` Coverage varies by number and country — many numbers return a partial subset, and a LinkedIn or social profile is only resolved in some cases. A row is returned (and billed) only when at least a name is found. #### Example output ```json [ { "query": "919587924808", "scrapedAt": "2026-07-17T14:13:58.593Z", "fullName": "Yashraj Kadam", "firstName": "Yashraj", "lastName": "Kadam", "title": "Senior Software Engineer", "headline": "Senior Software Engineer at Infosys", "company": "Infosys", "phone": "919587924808", "phones": "919587924808", "email": "kadam.yashraj@gmail.com", "emails": "kadam.yashraj@gmail.com", "city": "Pune", "state": "Maharashtra", "country": "India", "location": "Pune, Maharashtra, India", "linkedin": "https://www.linkedin.com/in/yashraj-kadam", "operator": "Jio", "xProfile": "https://x.com/yashraj_kadam", "telegram": "@yashraj_kadam", "gender": "male", "dateOfBirth": "1994-03-12", "photoUrl": "https://media.licdn.com/dms/image/v2/D5603AQ-yashraj-kadam/profile-displayphoto.jpg", "connectionCount": 500, "school": "College of Engineering, Pune", "skills": ["Java", "Spring Boot", "Microservices", "AWS", "Kubernetes"], "human": "# Phone enrichment\n\n- **Input Phone:** 919587924808\n- **Full names:** Yashraj Kadam\n- **Gender:** male\n- **Date of birth:** 1994-03-12\n- **Emails:** kadam.yashraj@gmail.com\n- **Phones:** 919587924808\n- **Locations:** Pune, Maharashtra, India\n- **Company:** Infosys\n- **LinkedIn profile:** https://www.linkedin.com/in/yashraj-kadam\n- **X profile:** https://x.com/yashraj_kadam\n- **Telegram username:** @yashraj_kadam\n- **Operator:** Jio", "raw": { "session_id": "ab1d8d54-60a7-4156-98d5-869dd187ddf8", "kind": "phone_enrichment", "phone": "919587924808", "human": "# Phone enrichment\n\n- **Input Phone:** 919587924808\n- **Full names:** Yashraj Kadam\n- **Gender:** male\n- **Date of birth:** 1994-03-12\n- **Emails:** kadam.yashraj@gmail.com\n- **Phones:** 919587924808\n- **Locations:** Pune, Maharashtra, India\n- **Company:** Infosys\n- **LinkedIn profile:** https://www.linkedin.com/in/yashraj-kadam\n- **X profile:** https://x.com/yashraj_kadam\n- **Telegram username:** @yashraj_kadam\n- **Operator:** Jio", "machine": { "full_names": [ "Yashraj Kadam" ], "gender": "male", "date_of_birth": "1994-03-12", "emails": [ "kadam.yashraj@gmail.com" ], "phones": [ "919587924808" ], "locations": [ { "country": "India", "state": "Maharashtra", "city": "Pune" } ], "company": "Infosys", "linkedin_profile": "https://www.linkedin.com/in/yashraj-kadam", "x_profile": "https://x.com/yashraj_kadam", "telegram_username": "@yashraj_kadam", "operator": "Jio" }, "total_points": 10 } } ] ``` > The row above shows a fully-resolved number. Actual fields reflect what is resolvable > for each number at run time; many numbers return a partial subset (name and email > only, no social profile), and unmatched fields come back as `null`. ### Pricing **$0.010 per matched number** ($10 per 1,000) returned to the dataset. **You pay only when a person is found — unresolved numbers are free.** | Event | Price | |---|---| | Actor start | Free | | Matched person returned (per dataset row) | **$0.010** | Competitive for the niche: direct reverse-lookup tools on Apify range from ~$6.5 to $150 per 1,000, and the segment's all-in-one competitor charges $25. Numbers that resolve to no person are **not billed**. Pricing is on top of your Apify platform usage. ### 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](https://docs.apify.com/api). 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 live contact data. ### 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 **Is this phone enrichment?** Yes — it's a reverse phone lookup and phone enrichment tool: it takes a raw number and enriches it into a full person record (name, email, location, company, carrier and, when available, social profiles). **What do I get back from a number?** A person: name and emails, location, company and carrier. Some numbers also resolve a LinkedIn or social profile — that's a bonus when available, not guaranteed for every number. **Do I need an API key, login or proxy?** No. The lookup runs on the Neuralverge backend — you never provide credentials, cookies or a proxy. **Am I charged if a number isn't matched?** No. You're billed only for rows returned to the dataset, i.e. when at least a name is found. **What number formats work?** Any — the Actor extracts digits automatically. Include the country code for the best match rate; coverage varies by country and carrier. **Is the data live?** Yes — every number 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 ## `phone` (type: `string`): The phone number to enrich (one per run). Any format works — the Actor strips '+', spaces, dashes and parentheses and sends digits only (e.g. 14155550123, 79670777820). ## Actor input object example ```json { "phone": "79670777820" } ``` # Actor output Schema ## `results` (type: `string`): Structured person + company data (name, title, company, email, location, LinkedIn, carrier), one row per matched phone. # 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 = { "phone": "79670777820" }; // Run the Actor and wait for it to finish const run = await client.actor("neuralverge/neuralverge-phone-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 = { "phone": "79670777820" } # Run the Actor and wait for it to finish run = client.actor("neuralverge/neuralverge-phone-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 '{ "phone": "79670777820" }' | apify call neuralverge/neuralverge-phone-enrichment --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=neuralverge/neuralverge-phone-enrichment", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reverse Phone Lookup — Name, Email & Location ✅ Misses Free", "description": "Reverse phone lookup and enrichment — find the person behind any number: name, email, location, company and carrier, plus a LinkedIn or social profile when available. Pay only for matches; misses are free.", "version": "0.1", "x-build-id": "U7t8T4KWKUTjioDC0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/neuralverge~neuralverge-phone-enrichment/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-neuralverge-neuralverge-phone-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/neuralverge~neuralverge-phone-enrichment/runs": { "post": { "operationId": "runs-sync-neuralverge-neuralverge-phone-enrichment", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/neuralverge~neuralverge-phone-enrichment/run-sync": { "post": { "operationId": "run-sync-neuralverge-neuralverge-phone-enrichment", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "phone": { "title": "Phone number", "type": "string", "description": "The phone number to enrich (one per run). Any format works — the Actor strips '+', spaces, dashes and parentheses and sends digits only (e.g. 14155550123, 79670777820)." } } }, "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 } } } } } } } } } } ```