# Email Verification Waterfall by Signaliz (`signaliz/email-verification-waterfall`) Actor Stop bouncing emails. This verification tool uses a multi-provider waterfall — it automatically routes to a secondary provider for deeper verification for catch-alls. Built by the team behind Signaliz and Content Marketing Media after sending 100M+ emails. - **URL**: https://apify.com/signaliz/email-verification-waterfall.md - **Developed by:** [Signaliz](https://apify.com/signaliz) (community) - **Categories:** Lead generation, Agents, Automation - **Stats:** 2 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $5.00 / 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 ## Email Verification Waterfall by Signaliz Built after sending **100 million+ emails** across hundreds of clients — many enterprise. This is the verification pipeline behind [Signaliz](https://signaliz.com), a SaaS product by [Content Marketing Media (CMM)](https://contentmarketingmedia.org). No API keys needed. Just paste your emails and run. ### Enterprise partners Signaliz is an enterprise partner with **Clay**, **Instantly**, **Octave**, and **Heyreach**. ### What does this Actor do? This Actor verifies whether email addresses are deliverable before you send to them. It uses a multi-provider waterfall approach to maximize accuracy: 1. **Primary verification** checks every email against a high-throughput provider 2. **Catch-all domains** (where the primary provider can't give a definitive answer) automatically get routed to a secondary provider for deeper verification You get a clean `email_verified: true/false` for every email, ready to load into your outbound tools. ### Built for those serious about email validation This isn't a toy verification tool. It was built from hard-won experience running high-volume outbound at scale — 12M+ emails/month across 20+ active client accounts. Every edge case you'll hit at volume (catch-all domains, disposable addresses) is handled. ### Key features - **Waterfall verification** — Multi-provider pipeline catches what single tools miss - **Catch-all resolution** — Don't lose enterprise leads on catch-all domains - **Disposable email detection** — Auto-rejects known disposable/temp email providers - **CSV batch support** — Upload thousands of emails at once, all original columns preserved - **Clean output** — Export results as JSON, CSV, or Excel ### Who is this for? - **Cold email agencies** pre-verifying before loading into Instantly, Smartlead, Lemlist - **SDRs and sales teams** cleaning prospect lists before outreach - **Growth engineers** building verification into automated pipelines - **Data teams** maintaining CRM hygiene at scale - **Anyone** who wants bounce rates below 2% ### Input | Field | Required | Description | |-------|----------|-------------| | `emails` | No* | List of email addresses to verify | | `emailsCsv` | No* | CSV content with an email column | | `emailColumn` | No | Column name if not "email" (default: `email`) | | `batchSize` | No | Emails per API call, 1–100 (default: 100) | *At least one of `emails` or `emailsCsv` must be provided. ### Output Each verified email is pushed to the Apify dataset: ```json { "success": true, "email": "jane@stripe.com", "email_verified": true, "email_is_catch_all": true, "credits_used": 0.5, "verification_details": { "free": false, "role": false, "quality": "risky", "initial_status": "catch_all", "catch_all_result": "deliverable" } } ```` A summary is saved to the key-value store under `OUTPUT`: ```json { "total_emails": 500, "total_verified": 412, "verification_rate": "82.4%", "completed_at": "2026-04-05T12:05:00.000Z" } ``` ### Pricing Pay-per-result through Apify. No external API keys or accounts needed. ### API usage ```bash curl -X POST "https://api.apify.com/v2/acts/YOUR_USERNAME~email-verification-waterfall/runs?token=YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "emails": ["john@acme.com", "jane@bigcorp.com"] }' ``` ### Integrations Works with Zapier, Make, n8n, and any tool that integrates with Apify Actors. Use it as a pre-verification step before loading into Instantly, Smartlead, Apollo, Lemlist, HeyReach, or any sequencing tool. ### About Signaliz [Signaliz](https://signaliz.com) is a GTM data quality platform built by [Content Marketing Media](https://contentmarketingmedia.org), a B2B outbound agency sending 12M+ emails/month across 20+ client accounts. Signaliz is an enterprise partner with Clay, Instantly, Octave, and Heyreach. # Actor input Schema ## `emails` (type: `array`): List of email addresses to verify. You can enter them manually or paste a list. ## `emailsCsv` (type: `string`): Paste raw CSV content with an email column header. All original columns are preserved in the output. ## `emailsCsvUrl` (type: `string`): URL to a publicly accessible CSV file. Use this for large uploads (up to 10,000 emails). Supports Google Sheets CSV export links, Dropbox direct links, or any hosted CSV. ## `datasetId` (type: `string`): Chain from another actor — provide a dataset ID to pull emails from. The dataset must contain rows with an email column. ## `emailColumn` (type: `string`): If your CSV or dataset uses a different column name for emails (e.g. 'Email Address', 'contact\_email'), specify it here. ## `batchSize` (type: `integer`): Number of emails per API call. Higher values are faster. Recommended: 100. ## Actor input object example ```json { "emails": [ "test@example.com" ], "emailColumn": "email", "batchSize": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `summary` (type: `string`): No description # 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 = { "emails": [ "test@example.com" ] }; // Run the Actor and wait for it to finish const run = await client.actor("signaliz/email-verification-waterfall").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 = { "emails": ["test@example.com"] } # Run the Actor and wait for it to finish run = client.actor("signaliz/email-verification-waterfall").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 '{ "emails": [ "test@example.com" ] }' | apify call signaliz/email-verification-waterfall --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=signaliz/email-verification-waterfall", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Email Verification Waterfall by Signaliz", "description": "Stop bouncing emails. This verification tool uses a multi-provider waterfall — it automatically routes to a secondary provider for deeper verification for catch-alls. Built by the team behind Signaliz and Content Marketing Media after sending 100M+ emails.", "version": "1.0", "x-build-id": "1RaKhTBC2EDevWDLy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/signaliz~email-verification-waterfall/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-signaliz-email-verification-waterfall", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/signaliz~email-verification-waterfall/runs": { "post": { "operationId": "runs-sync-signaliz-email-verification-waterfall", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/signaliz~email-verification-waterfall/run-sync": { "post": { "operationId": "run-sync-signaliz-email-verification-waterfall", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "emails": { "title": "Email addresses", "type": "array", "description": "List of email addresses to verify. You can enter them manually or paste a list.", "items": { "type": "string" } }, "emailsCsv": { "title": "Emails CSV (paste)", "type": "string", "description": "Paste raw CSV content with an email column header. All original columns are preserved in the output." }, "emailsCsvUrl": { "title": "CSV file URL", "type": "string", "description": "URL to a publicly accessible CSV file. Use this for large uploads (up to 10,000 emails). Supports Google Sheets CSV export links, Dropbox direct links, or any hosted CSV." }, "datasetId": { "title": "Apify Dataset ID", "type": "string", "description": "Chain from another actor — provide a dataset ID to pull emails from. The dataset must contain rows with an email column." }, "emailColumn": { "title": "Email column name", "type": "string", "description": "If your CSV or dataset uses a different column name for emails (e.g. 'Email Address', 'contact_email'), specify it here.", "default": "email" }, "batchSize": { "title": "Batch size", "minimum": 1, "maximum": 100, "type": "integer", "description": "Number of emails per API call. Higher values are faster. Recommended: 100.", "default": 100 } } }, "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 } } } } } } } } } } ```