# Company Website Intelligence Extractor (`iammienta/agent-company-website-intelligence`) Actor Extract a structured company research profile from any website. Built for AI agents, lead enrichment, CRM prep, and outbound research: offer, ICP, positioning, contact paths, evidence URLs, warnings, and confidence. - **URL**: https://apify.com/iammienta/agent-company-website-intelligence.md - **Developed by:** [Pete Mientkiewicz](https://apify.com/iammienta) (community) - **Categories:** AI, Agents, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Company Website Intelligence Extractor Company Website Intelligence Extractor turns a public company website into a structured company research profile for AI agents, lead enrichment, CRM preparation, sales research, and outbound workflows. Give it a domain or URL and it returns a compact JSON profile with positioning, offer signals, likely audience, contact paths, evidence pages, warnings, and confidence. ### Use cases - Build company research briefs before outbound sales. - Enrich a domain list with website positioning and contact evidence. - Help an AI sales agent understand what a company does before writing a message. - Prepare CRM records with offer, ICP, website, social, and contact-path clues. - Triage companies before deeper enrichment with LinkedIn, Google Maps, or email tools. ### Use this Actor when Use this Actor when an agent needs a first-pass company profile from a website, especially for lead qualification, market research, prospecting, or workflow chaining. ### Do not use this Actor when Do not use it for legal, financial, or compliance due diligence. It only reads public web pages and should treat thin, blocked, or outdated websites as weak signals. ### Input ```json { "domainOrUrl": "https://scaleupsystems.co", "maxPages": 3 } ```` ### Output The Actor writes one structured record to the default dataset. Typical fields include: - `sourceUrl` - `status` - `companyNameGuess` - `positioningSummary` - `offerSignals` - `likelyAudience` - `businessModelSignals` - `contactPaths` - `emails` - `socialLinks` - `evidencePages` - `confidence` ### Agent workflow 1. Run this Actor with a company domain. 2. Read `results` from the default dataset URL. 3. Use `positioningSummary`, `offerSignals`, and `businessModelSignals` to decide whether the company fits your workflow. 4. Use `evidencePages` and `contactPaths` as citations or next-step URLs. ### Limitations - Output is research-grade, not a verified company database. - Blocked pages, JavaScript-heavy sites, and sparse websites may reduce confidence. - Contact details are extracted only when visible on public pages. ### Pricing and runtime This MVP uses bounded page fetches and compact JSON output. Keep `maxPages` low for agent-driven workflows and increase only when deeper evidence is needed. # Actor input Schema ## `domainOrUrl` (type: `string`): Company domain or full website URL to analyse. ## `maxPages` (type: `integer`): Maximum number of pages from the same website to fetch. ## Actor input object example ```json { "domainOrUrl": "https://scaleupsystems.co", "maxPages": 4 } ``` # Actor output Schema ## `results` (type: `string`): Structured results in the default dataset. # 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 = { "domainOrUrl": "https://scaleupsystems.co" }; // Run the Actor and wait for it to finish const run = await client.actor("iammienta/agent-company-website-intelligence").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 = { "domainOrUrl": "https://scaleupsystems.co" } # Run the Actor and wait for it to finish run = client.actor("iammienta/agent-company-website-intelligence").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 '{ "domainOrUrl": "https://scaleupsystems.co" }' | apify call iammienta/agent-company-website-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=iammienta/agent-company-website-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Company Website Intelligence Extractor", "description": "Extract a structured company research profile from any website. Built for AI agents, lead enrichment, CRM prep, and outbound research: offer, ICP, positioning, contact paths, evidence URLs, warnings, and confidence.", "version": "0.1", "x-build-id": "a4NZoOt95ft1ZcRYk" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/iammienta~agent-company-website-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-iammienta-agent-company-website-intelligence", "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/iammienta~agent-company-website-intelligence/runs": { "post": { "operationId": "runs-sync-iammienta-agent-company-website-intelligence", "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/iammienta~agent-company-website-intelligence/run-sync": { "post": { "operationId": "run-sync-iammienta-agent-company-website-intelligence", "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": [ "domainOrUrl" ], "properties": { "domainOrUrl": { "title": "Domain or URL", "type": "string", "description": "Company domain or full website URL to analyse." }, "maxPages": { "title": "Max pages", "minimum": 1, "maximum": 10, "type": "integer", "description": "Maximum number of pages from the same website to fetch.", "default": 4 } } }, "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 } } } } } } } } } } ```