# H-1B Employer Scraper — Sponsoring Company Leads (`gocreative.ai/dol-h1b-employer-leads`) Actor Scrape the US DOL OFLC quarterly LCA disclosure data to find top H-1B visa sponsoring companies. Returns deduplicated employer leads with address, NAICS industry, application volume, certification rate, and wage ranges. - **URL**: https://apify.com/gocreative.ai/dol-h1b-employer-leads.md - **Developed by:** [GoCreative AI](https://apify.com/gocreative.ai) (community) - **Categories:** Lead generation, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $8.00 / 1,000 leads 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 ## H-1B Employer Scraper — Sponsoring Company Leads **Scrape the US DOL OFLC quarterly LCA disclosure data to find top H-1B visa sponsoring companies. Returns deduplicated employer leads with address, NAICS industry, application volume, certification rate, and wage ranges.** No API key, no signup, no subscription — pay only for what you scrape. Clean, structured output ready for CSV, JSON, Excel, or direct API export into your own pipeline. ### What this scraper does Scrape the US DOL OFLC quarterly LCA disclosure data to find top H-1B visa sponsoring companies. Returns deduplicated employer leads with address, NAICS industry, application volume, certification rate, and wage ranges. Every run pulls fresh data straight from the source and pushes clean, typed records to the dataset — ready for your CRM, spreadsheet, AI agent, or data pipeline. ### Use cases - **B2B lead generation** — build targeted prospect lists with verified, structured data - **Sales prospecting** — find companies and contacts that match your ICP - **Market research & competitive intelligence** — track an industry or niche in structured form - **AI agents & automation** — feed agents clean external data without scraping infra - **Data enrichment** — append fresh fields to your existing lists ### Input | Field | Description | |---|---| | `quarter` | Which DOL OFLC quarterly LCA disclosure dataset to download. Follows US federal fiscal year (FY starts Oct 1). Use the most recent published | | `max_rows` | Maximum number of application rows to read from the disclosure file. Higher values yield more unique employers but increase runtime. Full qu | | `max_results` | Maximum number of unique employer records to output, sorted by total H-1B application count descending. | | `naics_filter` | Filter employers by NAICS code prefix. Examples: 51 = Information/Tech, 54 = Professional Services, 52 = Finance. Leave blank to include all | | `state_filter` | Filter employers by 2-letter US state code (e.g. CA, TX, NY). Leave blank to include all states. | ### Output Every result is a clean structured record. Export the full dataset as **CSV, JSON, or Excel** from the Apify console, or pull it via the Apify API straight into your own tools. ### Why use this actor - **Scrape dol h1b employer leads** — fast, structured, reliable. - **Dol h1b employer leads data export (csv, json, excel)** — fast, structured, reliable. - **Dol h1b employer leads api alternative — no key required** — fast, structured, reliable. - **Automated dol h1b employer leads monitoring on a schedule** — fast, structured, reliable. - **Structured dol h1b employer leads records for ai agents and pipelines** — fast, structured, reliable. ### How it works This actor pulls data directly from the source, structures it into clean rows, and pushes each result to the dataset. It runs on Apify's infrastructure — reliable, schedulable, and pay-per-result so you only pay for data you actually get. ### Pricing Pay-per-result via the Apify Store. No monthly subscription, no minimums — run it once or schedule it daily; you're only charged for the results returned. ### FAQ **Do I need an API key or account?** No. Just provide your input and run it. **Can I schedule it to run automatically?** Yes — use Apify Schedules to run it hourly, daily, or weekly and get fresh data on autopilot. **What formats can I export?** CSV, JSON, Excel, or via the Apify API. **Can I integrate it into my own app?** Yes — call it via the Apify API and pull results directly into your pipeline. **Is the data accurate and fresh?** Data is pulled live from the source on each run, so it reflects what's available at run time. # Actor input Schema ## `quarter` (type: `string`): Which DOL OFLC quarterly LCA disclosure dataset to download. Follows US federal fiscal year (FY starts Oct 1). Use the most recent published quarter. ## `max_rows` (type: `integer`): Maximum number of application rows to read from the disclosure file. Higher values yield more unique employers but increase runtime. Full quarterly files can have 100k+ rows. ## `max_results` (type: `integer`): Maximum number of unique employer records to output, sorted by total H-1B application count descending. ## `naics_filter` (type: `string`): Filter employers by NAICS code prefix. Examples: 51 = Information/Tech, 54 = Professional Services, 52 = Finance. Leave blank to include all industries. ## `state_filter` (type: `string`): Filter employers by 2-letter US state code (e.g. CA, TX, NY). Leave blank to include all states. ## Actor input object example ```json { "quarter": "FY2025_Q1", "max_rows": 20000, "max_results": 500, "naics_filter": "51", "state_filter": "CA" } ```` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("gocreative.ai/dol-h1b-employer-leads").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 = {} # Run the Actor and wait for it to finish run = client.actor("gocreative.ai/dol-h1b-employer-leads").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 '{}' | apify call gocreative.ai/dol-h1b-employer-leads --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=gocreative.ai/dol-h1b-employer-leads", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "H-1B Employer Scraper — Sponsoring Company Leads", "description": "Scrape the US DOL OFLC quarterly LCA disclosure data to find top H-1B visa sponsoring companies. Returns deduplicated employer leads with address, NAICS industry, application volume, certification rate, and wage ranges.", "version": "0.1", "x-build-id": "YwUXx3M7Jj7UVc8zf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/gocreative.ai~dol-h1b-employer-leads/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-gocreative.ai-dol-h1b-employer-leads", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/gocreative.ai~dol-h1b-employer-leads/runs": { "post": { "operationId": "runs-sync-gocreative.ai-dol-h1b-employer-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/gocreative.ai~dol-h1b-employer-leads/run-sync": { "post": { "operationId": "run-sync-gocreative.ai-dol-h1b-employer-leads", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "quarter": { "title": "Data Quarter", "enum": [ "FY2025_Q2", "FY2025_Q1", "FY2024_Q4", "FY2024_Q3" ], "type": "string", "description": "Which DOL OFLC quarterly LCA disclosure dataset to download. Follows US federal fiscal year (FY starts Oct 1). Use the most recent published quarter.", "default": "FY2025_Q1" }, "max_rows": { "title": "Max Rows to Scan", "minimum": 1000, "maximum": 200000, "type": "integer", "description": "Maximum number of application rows to read from the disclosure file. Higher values yield more unique employers but increase runtime. Full quarterly files can have 100k+ rows.", "default": 20000 }, "max_results": { "title": "Max Employer Results", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of unique employer records to output, sorted by total H-1B application count descending.", "default": 500 }, "naics_filter": { "title": "NAICS Code Prefix Filter", "type": "string", "description": "Filter employers by NAICS code prefix. Examples: 51 = Information/Tech, 54 = Professional Services, 52 = Finance. Leave blank to include all industries.", "default": "" }, "state_filter": { "title": "US State Filter", "type": "string", "description": "Filter employers by 2-letter US state code (e.g. CA, TX, NY). Leave blank to include all states.", "default": "" } } }, "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 } } } } } } } } } } ```