# Catchall Email Verification and Finder - Relentless Identity (`codemaggot/relentless-identity-api`) Actor Relentless Identity is the best API to date for finding and verifying work emails with features including alias resolution, multi-domain discovery, and catchall resolution. - **URL**: https://apify.com/codemaggot/relentless-identity-api.md - **Developed by:** [Code Maggot](https://apify.com/codemaggot) (community) - **Categories:** Lead generation, Integrations, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $21.00 / 1,000 client attempts This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Relentless Identity Email Finder & Verifier Actor **Overview** Find and verify emails at scale using Relentless Identity's live identity-first verification API. This Actor helps SaaS teams, ecommerce operators, sales teams, marketers, and data teams discover likely work emails, verify existing addresses, resolve aliases, detect catch-all behavior, and identify supported corporate identity providers behind a domain. Relentless Identity is built for modern email infrastructure where SMTP-only checks often fail. Instead of relying on stale lookup tables, it combines live provider and mailbox signals to return compact, actionable results for finder and verification workflows. #### Why Relentless Identity? 1. **Live Identity Verification** Verify emails using live identity and routing signals instead of purchased databases, recycled enrichment tables, or stale cached records. 2. **Finder + Probe Workflows** Use the Finder flow to discover likely work emails for a person and company, or use Probe to verify a known email address. 3. **Modern Infrastructure Coverage** Resolve aliases, detect catch-all behavior, inspect MX hosts, and identify identity providers such as Okta, Microsoft Entra ID, Google Workspace, OneLogin, Auth0, Ping Identity, and others. #### Finder vs. Probe | Tool | Endpoint | Best For | Notes | |------|----------|----------|-------| | **Finder** | `/client/attempt` | Finding likely work emails from a person + company/domain input | Includes alias resolution, catch-all resolution, and multi-domain discovery for work email discovery. | | **Probe** | `/client/probe` | Verifying a specific email address | Works for work and non-work emails. Alias resolution applies to work-email workflows. | #### Common Use Cases - **Sales & Marketing Prospecting** Find verified work emails for decision-makers, enrich lead lists, and reduce bounce risk before outreach. - **CRM & Data Enrichment** Fill missing work email fields and validate existing records before syncing to HubSpot, Salesforce, Clay, or custom pipelines. - **Email List Cleaning** Use Probe to validate existing lists, including ecommerce or SaaS customer emails that may not be corporate work emails. - **Fraud, Risk & Identity Checks** Map addresses to identity evidence, detect aliases, and understand whether an email is backed by real provider-side signals. #### Automate Your Workflow - **Webhook Integration** Push Actor results to Zapier, Make, n8n, Slack, or your CRM using Apify webhooks. - **Scheduled Verification** Run recurring jobs to clean lead lists, refresh CRM records, or re-check high-value email addresses. - **Batch Processing** Call the Actor repeatedly from your own workflow or queue if you need many Finder or Probe requests. --- ### Input Examples Provide either `fullName` + `domain` for Finder, or `email` for Probe. Mixing them is an error. #### Finder Input Use Finder when you want to discover the most likely work email for a person at a company. ```json { "fullName": "Jane Doe", "domain": "acme.com" } ```` #### Probe Input Use Probe when you already have an email address and want to verify whether it appears deliverable and identity-backed. ```json { "email": "jane.doe@acme.com" } ``` *** ### Output Structure Each Actor result is the Relentless Identity response returned by the backend. #### Response Shape: `/client/attempt` (Finder) ```json { "state": "deliverable", "outcome": "found", "address": "string", "alternatives": ["string"], "is_alias": true, "alias": { "original": "string", "resolved": "string" }, "is_catchall": true, "identity_providers": [ { "provider": "okta", "hostname": "company.okta.com" } ], "mx_hosts": [ "string" ], "request_id": "string" } ``` #### Response Shape: `/client/probe` (Probe) ```json { "state": "deliverable", "outcome": "found", "address": "string", "is_alias": true, "alias": { "original": "string", "resolved": "string" }, "is_catchall": true, "identity_providers": [ { "provider": "okta", "hostname": "company.okta.com" } ], "mx_hosts": [ "string" ], "request_id": "string" } ``` *** ### Key Data Points | Field | What It Means | Use Case | |-------|---------------|----------| | `state` | Deliverability classification for the returned or verified address | Filter usable emails before outreach or import. | | `outcome` | Whether the request produced a found/verified result | Route successful and unresolved records differently. | | `address` | The discovered or verified email address | Save to CRM, enrichment table, or outreach tool. | | `alternatives` | Additional valid identities found during Finder resolution (Finder only) | Expand outreach or retry against alternate addresses. | | `is_alias` | Whether the email appears to be an alias | Understand whether the submitted address differs from the resolved identity. | | `alias.original` | Original alias address | Audit alias resolution. | | `alias.resolved` | Resolved identity-backed address | Prefer canonical or provider-backed address records. | | `is_catchall` | Whether the domain appears to use catch-all behavior | Avoid treating SMTP acceptance alone as proof of a real inbox. | | `identity_providers` | Detected identity provider signals | Understand the identity stack behind the domain. | | `mx_hosts` | Mail exchanger hosts for the domain | Support deliverability, routing, and infrastructure analysis. | | `request_id` | Unique request identifier | Debugging, support, and reconciliation. | *** ### FAQ **Q: What is the difference between Finder and Probe?**\ A: Finder uses `/client/attempt` to discover a likely work email from person and company/domain inputs. Probe uses `/client/probe` to verify a specific email address. **Q: Does Finder only work for work emails?**\ A: Finder is primarily designed for work email discovery. **Q: Do I need to verify addresses returned by the finder?**\ A: No. **Q: Can Probe verify non-work emails?**\ A: Yes. **Q: Does Probe perform multi-domain discovery?**\ A: No. Probe verifies the specific email address you submit. **Q: Does the Actor resolve aliases?**\ A: Yes, but alias resolution is limited to work-email workflows. Finder and work-email Probe results can return alias information through `is_alias` and the `alias.original` / `alias.resolved` fields. **Q: Does it work with catch-all domains?**\ A: Yes. Relentless Identity is designed to interpret catch-all behavior and return more precise signals than SMTP-only checks. **Q: How many free requests do I get?**\ A: Free-tier users pay the published list price above. **Q: Is pricing the same on Relentless Identity's own platform?**\ A: No. Apify free-tier users pay list price, while paid tiers use the discounted pay-as-you-go pricing. **Q: Can I use Relentless Identity outside Apify?**\ A: Yes. You can sign up directly on the Relentless Identity platform, start free, and use the native API or supported integrations outside Apify. **Q: Are all Relentless Identity endpoints available in this Actor?**\ A: No. This Actor focuses on Finder and Probe. Other endpoints, such as job scheduling endpoints, are not exposed through the Apify Actor. **Q: How fresh is the data?**\ A: Results are produced from live verification signals rather than stale lookup tables. Run scheduled jobs when you want to refresh a CRM, prospect list, or customer email list. **Q: What should I do with uncertain or unresolved results?**\ A: Keep them separate from deliverable records, retry later if appropriate, or route them into a manual review workflow depending on your risk tolerance. *** ### Integration Code Use the Apify API to run the Actor and return the dataset items directly. ```bash curl "https://api.apify.com/v2/actors/codemaggot~relentless-identity-api/run-sync-get-dataset-items?format=json" \ -H "Authorization: Bearer $APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "email": "jane.doe@acme.com" }' ``` If you prefer the run object first, use `run-sync` and then fetch the run's default dataset items. *** ### Learn More - [Homepage](https://relentlessidentity.com) - [Documentation](https://relentlessidentity.com/docs) - [REST API Reference](https://relentlessidentity.com/docs/rest-api-reference) - [MCP Reference](https://relentlessidentity.com/docs/mcp-reference) - [Pricing](https://relentlessidentity.com/pricing) *** *Stop guessing which emails are real. Find, verify, and resolve identities with live signals.* # Actor input Schema ## `fullName` (type: `string`): Required for Client attempt. ## `domain` (type: `string`): Required for Client attempt. ## `email` (type: `string`): Optional. When provided, the Actor performs a Client probe. ## Actor input object example ```json { "fullName": "Jane Doe", "domain": "acme.com", "email": "jane.doe@acme.com" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "fullName": "Jane Doe", "domain": "acme.com", "email": "jane.doe@acme.com" }; // Run the Actor and wait for it to finish const run = await client.actor("codemaggot/relentless-identity-api").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "fullName": "Jane Doe", "domain": "acme.com", "email": "jane.doe@acme.com", } # Run the Actor and wait for it to finish run = client.actor("codemaggot/relentless-identity-api").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 '{ "fullName": "Jane Doe", "domain": "acme.com", "email": "jane.doe@acme.com" }' | apify call codemaggot/relentless-identity-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=codemaggot/relentless-identity-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Catchall Email Verification and Finder - Relentless Identity", "description": "Relentless Identity is the best API to date for finding and verifying work emails with features including alias resolution, multi-domain discovery, and catchall resolution.", "version": "1.0", "x-build-id": "8DO3wWDDD4yn5TiWI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/codemaggot~relentless-identity-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-codemaggot-relentless-identity-api", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/codemaggot~relentless-identity-api/runs": { "post": { "operationId": "runs-sync-codemaggot-relentless-identity-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/codemaggot~relentless-identity-api/run-sync": { "post": { "operationId": "run-sync-codemaggot-relentless-identity-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "fullName", "domain" ], "properties": { "fullName": { "title": "Full name", "type": "string", "description": "Required for Client attempt." }, "domain": { "title": "Domain", "type": "string", "description": "Required for Client attempt." }, "email": { "title": "Email address", "type": "string", "description": "Optional. When provided, the Actor performs a Client probe." } } }, "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 } } } } } } } } } } ```