# Email Verifier & Enricher Pro (`jurassic_jove/email-verifier-enricher-pro`) Actor Bulk email verifier and corporate email finder in one tool. Validate email deliverability with SMTP, MX and syntax checks, catch-all and disposable detection, plus a 0-100 score. Find corporate emails from name + domain with AI-powered role and seniority classification. Clean lead lists fast. - **URL**: https://apify.com/jurassic\_jove/email-verifier-enricher-pro.md - **Developed by:** [Data Runner](https://apify.com/jurassic_jove) (community) - **Categories:** Lead generation, Automation, AI - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 email verifieds 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 Verifier & Email Finder — Bulk Email Verification + AI Email Enrichment **Verify email deliverability in bulk, and find the corporate email when all you have is a name and a company domain — in one Actor.** This is a bulk email verifier *and* an AI-powered email finder: it cleans your email list (syntax, MX, mailbox confirmation, disposable & role detection), **and** discovers the most likely corporate address from a name + domain, then scores and classifies it. Use it to **clean your email list, reduce bounce rate, improve email deliverability, and protect your sender reputation** — and to turn "name + company" into a verified, role-classified email. One tool, one bill, no stitching a separate finder and verifier together. Great for **bulk email verification**, **CRM list cleaning**, pre-campaign list QA, signup validation, and **sales prospecting / lead enrichment**. --- ### Why this beats a finder + verifier stack Most teams pay twice: an **email finder** to discover addresses, then a separate **email verifier** to confirm deliverability. Stacked together, the cost of one *usable, verified* corporate email typically lands around **$14–$38 per 1,000**. This Actor does both and prices the combined "found **and** verified **and** classified" result at **≈ $15 per 1,000** — the low end of that range, with an AI role/seniority classification on top that standalone finders don't include — and plain verification at **≈ $3 per 1,000**. | Tier | What you get | Price | |------|--------------|-------| | **Verification** | syntax → MX → mailbox confirmation → disposable / role detection → 0–100 deliverability score | **$0.003 / email** (≈ $3 / 1k) | | **Find + enrich** | AI guesses the corporate address from name + domain, verifies it, and classifies role + seniority | **$0.012 / record** (≈ $12 / 1k) | > **Pay-as-you-go, no subscription.** You're charged per result, only for the work performed. Set a **Max total charge** (`maxTotalChargeUsd`) per run to cap spend — the Actor stops cleanly the moment your budget is reached. --- ### Features #### Bulk email verification & list cleaning Verify thousands of addresses in one run and export a clean list — strip dead, risky, and throwaway emails before you send. #### Mailbox confirmation (no email sent) For **Microsoft 365 / Outlook-hosted domains** (a large share of corporate mail), the Actor confirms whether the individual mailbox exists via Microsoft's provider API over HTTPS — **without sending any email**. These addresses can reach a confident `good` verdict. #### Domain-level deliverability Every address is checked for valid **syntax**, a deliverable domain (**MX records**), **disposable / temporary** domains, and **role-based** mailboxes — so even when a mailbox can't be individually confirmed, you get a sound deliverability signal. #### Disposable & temporary email detection Flags throwaway/temporary-domain addresses so you can remove fake signups and junk leads. #### Role-based email detection Identifies role mailboxes (`info@`, `sales@`, `admin@`, …) that go to a team rather than a person — deliverable but low-signal for outreach. #### AI email finder (find work email by name + domain) Give a name and a company domain; the AI engine infers the address convention (`first.last`, `flast`, `first`, …), builds the most likely corporate email, and runs it through verification. #### Transparent 0–100 deliverability score Every address gets a deterministic score and a `good` / `risky` / `bad` status, with the reasons attached. #### Bulk email verification API Run it on demand or from your own code via the Apify API, and pull results as **CSV, JSON, or Excel**. --- ### How to verify and find emails in bulk 1. **Open the Actor** on Apify (or call it via the Apify API). 2. **Add your data** — paste/upload a list into **Emails to verify**, and/or add **Contacts** as `{name, domain}` objects to find missing addresses. 3. **Choose options** — toggle **AI enrichment** (find + classify) and the **deep mailbox check**, and set **Max concurrency**. 4. **Set a budget** — enter **Max total charge (USD)** to cap spend. 5. **Run it.** 6. **Export the results** as **CSV, JSON, or Excel**, or fetch them programmatically via the Apify API. #### Two ways to run it **1. Verify emails you already have** — list-cleaning / QA: ```json { "emails": ["jane.doe@stripe.com", "info@acme.com", "old.contact@dead-domain.xyz"], "smtpCheck": true } ```` **2. Find + verify from name + domain** — the AI engine guesses the address, verifies it, and classifies the role: ```json { "contacts": [ { "name": "Jane Doe", "domain": "stripe.com" }, { "name": "John Smith", "domain": "acme.com" } ], "enrichment": true } ``` You can mix both, and toggle the deep mailbox check and AI enrichment independently. *** ### Input | Field | Type | Description | |-------|------|-------------| | `emails` | array of strings | Addresses to verify. Use for list-cleaning / QA. | | `contacts` | array of `{name, domain}` | The AI engine guesses the most likely corporate email, then verifies it. **Requires `enrichment: true`.** | | `enrichment` | boolean | Adds AI role/seniority classification and corporate-pattern guessing. Billed at the enrichment rate. Default `false`. | | `smtpCheck` | boolean | Deep mailbox check. Confirms the individual mailbox where possible (Microsoft-hosted domains, via HTTPS — no email sent). Default `true`. | | `maxConcurrency` | integer | Records processed in parallel (1–50). Default `10`. | Provide at least one of `emails` or `contacts`. *** ### Output One dataset item per record (export as CSV, JSON, or Excel): ```jsonc { "input": "john.doe@example.com", // or the {name, domain} that was resolved "email": "john.doe@example.com", // resolved / guessed address "deliverability_score": 88, // 0–100 "business_status": "good", // good | risky | bad "technical": { "syntax_valid": true, "domain_has_mx": true, "mailbox_exists": true, // true | false | null (not individually confirmed) "verification_method": "microsoft", // how the mailbox was checked: microsoft | smtp | none "is_catch_all": null, "is_disposable": false, "is_role_based": false // info@, sales@, admin@ … }, "ai_enrichment": { // present only when enrichment = true "guessed_from": "name+domain", // null when the email was supplied "pattern": "first.last", "role_category": "engineering", "seniority": "senior", "confidence": 0.82 }, "verification_details": { /* raw signals for debugging */ }, "source": "email-verifier-enricher-pro" } ``` *** ### The deliverability score (0–100) Deterministic and transparent — the same signals always produce the same score, and every item carries the reasons behind it (`verification_details.score_reasons`). The bands: | Signal | Score | Status | |--------|-------|--------| | Invalid syntax | `0` | `bad` | | Domain has no mail server (no MX) | `≤ 20` | `bad` | | Disposable / temporary domain | `≤ 30` | `bad` | | Mailbox confirmed **not** to exist | `≤ 20` | `bad` | | Role-based address (`info@`, `sales@` …) | capped `~55` | `risky` | | Deliverable domain, mailbox not individually confirmed | `~78` | `risky` | | Mailbox confirmed to exist (Microsoft provider API) | `~88` | `good` | | Mailbox confirmed by a live SMTP probe (external backend) | `90–100` | `good` | `good` = score ≥ 85, `risky` = 40–84, `bad` = below 40. The `verification_method` field tells you how each mailbox verdict was reached. *** ### How mailbox verification works The Actor never sends an email to verify one. It layers signals that don't require sending: - **Syntax + MX** — is the address well-formed and does the domain accept mail? (always run) - **Disposable / role detection** — throwaway domains and team mailboxes. (always run) - **Microsoft mailbox check** — for Microsoft 365 / Outlook-hosted domains, Microsoft's provider API confirms whether the specific mailbox exists, over HTTPS. (the deep check) Confirming an individual mailbox on *any* domain via a raw SMTP probe requires outbound port 25, which shared cloud platforms block as standard anti-spam policy. For domains we can't probe directly, the Actor scores the **domain-level** deliverability honestly (`risky` = "deliverable domain, mailbox not individually confirmed") rather than guessing. Operators can enable **full mailbox confirmation on every domain** (plus catch-all detection) by connecting an external SMTP backend — then non-Microsoft domains also reach a confident `good` / `bad` verdict. See the configuration note below. *** ### How the AI enrichment works When `enrichment` is on, an **AI-powered enrichment engine** does two things, batched for speed: 1. **Corporate pattern guessing** — given a name and a company domain, it infers the most likely address convention (`first.last`, `flast`, `first`, …) and the address itself. The Actor then verifies that guessed address. 2. **Role & seniority classification** — it categorizes the contact (engineering, sales, marketing, executive, operations, finance, hr, support, product, legal, general) and seniority (junior, mid, senior, executive), with a confidence score. A `contacts` record that gets both found and verified is billed for **both** events (verification + enrichment). Enrichment only applies to addresses that are at least deliverable — a `bad` address (invalid, no mail server, disposable, or confirmed nonexistent) is billed **verification only**, so you never pay the enrichment rate for a dead address. *** ### Use cases - **CRM cleanup & email list cleaning** — purge dead and risky addresses; reduce bounce rate and protect your sender reputation. - **Pre-campaign list QA** — verify a list before a send to cut bounces and improve email deliverability. - **Signup / lead-form validation** — score addresses at capture time and block disposable signups. - **Sales prospecting & lead enrichment** — turn "name + company" into a verified, role-classified corporate email. *** ### FAQ #### How do I verify an email address without sending an email? The Actor never sends a message. It validates syntax, looks up the domain's MX records, and — for Microsoft-hosted domains — asks Microsoft's provider API (over HTTPS) whether the specific mailbox exists. You get a 0–100 score and a good/risky/bad status per address, with the method used recorded in `verification_method`. #### How do I verify emails in bulk? Paste or upload your list into the **Emails to verify** field (or pull it via the Apify API), set Max concurrency and a Max total charge, and run. Each address returns a deliverability score and technical signals (MX, mailbox check, disposable, role-based). Export the cleaned results as CSV, JSON, or Excel. #### How do I find someone's work email from just a name and company? Add `{name, domain}` contacts and enable AI enrichment. The AI-powered engine infers the company's address convention (first.last, flast, first, …), constructs the most likely corporate email, then verifies it and classifies the contact's role and seniority with a confidence score. #### What does "mailbox not individually confirmed" mean? For domains where the individual mailbox can't be probed (non-Microsoft domains, without an external SMTP backend), the Actor verifies everything it can at the domain level — valid syntax, a deliverable domain, not disposable, not role-based — and scores the address `~78 risky`. The domain accepts mail; we just haven't confirmed that exact mailbox, and we won't pretend we have. #### What is a role-based email and why does it matter? Role-based addresses like `info@`, `sales@`, or `admin@` go to a team or function rather than a person. They bounce less but convert poorly and can hurt sender reputation in cold outreach, so the Actor detects them and caps their score at ~55 with a `risky` status. #### How accurate is the verification? Accuracy comes from layering syntax, MX, disposable/role detection, and — for Microsoft-hosted domains — a direct mailbox-existence check, rolled into a deterministic 0–100 score with the reasons attached to every result. Where a mailbox can't be individually confirmed, the score is conservative (`risky`) rather than a false `good`. #### How much does it cost to verify or find emails? Pricing is pay-as-you-go with no subscription: verification is **$0.003 per email (~$3 per 1,000)** and find + AI enrichment is **$0.012 per record (~$12 per 1,000)**. Set a Max total charge to cap spend — the Actor stops cleanly the moment your budget is reached. #### Can I detect disposable or temporary email addresses? Yes. The Actor flags disposable and temporary-domain addresses and caps their score at ~30 with a `bad` status, so you can strip throwaway signups out of your list before sending. *** ### Tips - Leave `smtpCheck: true` so Microsoft-hosted mailboxes get the deep check. - Most lists cluster on a handful of domains — the Actor caches MX status per domain, so large clustered lists stay fast and cheap. - Set `maxTotalChargeUsd` to budget each run. The Actor halts cleanly at the cap. *** ### Configuration (operators) The AI enrichment engine is provider-agnostic and configured entirely via environment variables / Apify secrets — set these on the Actor before enabling enrichment: - `LLM_API_KEY` — API key for the enrichment engine (store as an Apify secret). - `LLM_BASE_URL` — engine endpoint base URL. - `LLM_MODEL` — model identifier. If the engine is not configured, enrichment gracefully falls back to a built-in heuristic so runs still complete. **Optional — full SMTP mailbox verification (all domains):** to confirm mailboxes on non-Microsoft domains too (and detect catch-all), point the Actor at an external SMTP relay reachable over HTTPS: - `SMTP_RELAY_URL` — base URL of a Reacher-compatible relay (`POST /v0/check_email`). - `SMTP_RELAY_TOKEN` — bearer token the relay requires (store as an Apify secret). When unset, non-Microsoft domains are scored at the domain level (`risky`, "mailbox not individually confirmed"). # Actor input Schema ## `emails` (type: `array`): List of email addresses to verify. Use this for list-cleaning / QA. ## `contacts` (type: `array`): List of {name, domain} objects. The AI engine guesses the most likely corporate email pattern, then verifies it. ## `enrichment` (type: `boolean`): Adds AI role/seniority classification and corporate-pattern guessing. Billed at the enrichment rate. ## `smtpCheck` (type: `boolean`): Confirms the individual mailbox where possible. For Microsoft-hosted domains (Microsoft 365 / Outlook) this uses a provider API over HTTPS — no email is sent. Other domains are verified at the domain level (syntax, MX, disposable, role). ## `maxConcurrency` (type: `integer`): Maximum number of records processed in parallel. Higher = faster, but more load on mail servers. ## Actor input object example ```json { "emails": [ "john.doe@example.com" ], "contacts": [ { "name": "John Doe", "domain": "example.com" } ], "enrichment": false, "smtpCheck": true, "maxConcurrency": 10 } ``` # 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": [ "john.doe@example.com" ], "contacts": [ { "name": "John Doe", "domain": "example.com" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("jurassic_jove/email-verifier-enricher-pro").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": ["john.doe@example.com"], "contacts": [{ "name": "John Doe", "domain": "example.com", }], } # Run the Actor and wait for it to finish run = client.actor("jurassic_jove/email-verifier-enricher-pro").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": [ "john.doe@example.com" ], "contacts": [ { "name": "John Doe", "domain": "example.com" } ] }' | apify call jurassic_jove/email-verifier-enricher-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jurassic_jove/email-verifier-enricher-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Email Verifier & Enricher Pro", "description": "Bulk email verifier and corporate email finder in one tool. Validate email deliverability with SMTP, MX and syntax checks, catch-all and disposable detection, plus a 0-100 score. Find corporate emails from name + domain with AI-powered role and seniority classification. Clean lead lists fast.", "version": "0.0", "x-build-id": "4fdpG1M2JHonJcG4o" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jurassic_jove~email-verifier-enricher-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jurassic_jove-email-verifier-enricher-pro", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jurassic_jove~email-verifier-enricher-pro/runs": { "post": { "operationId": "runs-sync-jurassic_jove-email-verifier-enricher-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jurassic_jove~email-verifier-enricher-pro/run-sync": { "post": { "operationId": "run-sync-jurassic_jove-email-verifier-enricher-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Emails to verify", "type": "array", "description": "List of email addresses to verify. Use this for list-cleaning / QA.", "items": { "type": "string" } }, "contacts": { "title": "Contacts to find & verify", "type": "array", "description": "List of {name, domain} objects. The AI engine guesses the most likely corporate email pattern, then verifies it." }, "enrichment": { "title": "Enable AI enrichment", "type": "boolean", "description": "Adds AI role/seniority classification and corporate-pattern guessing. Billed at the enrichment rate.", "default": false }, "smtpCheck": { "title": "Deep mailbox check", "type": "boolean", "description": "Confirms the individual mailbox where possible. For Microsoft-hosted domains (Microsoft 365 / Outlook) this uses a provider API over HTTPS — no email is sent. Other domains are verified at the domain level (syntax, MX, disposable, role).", "default": true }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of records processed in parallel. Higher = faster, but more load on mail servers.", "default": 10 } } }, "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 } } } } } } } } } } ```