# Company Signal - AI Company Research (`complex_intricate_networks/company-research-ai`) Actor Turn any company name or domain into a structured account-research dataset. Automatically extract firmographics, multi-source funding history, recent news, and hiring indicators. Agent-ready JSON format built for MCP, Claude, Cursor, CRM sync, or CSV export. - **URL**: https://apify.com/complex\_intricate\_networks/company-research-ai.md - **Developed by:** [CIN](https://apify.com/complex_intricate_networks) (community) - **Categories:** MCP servers, AI, Lead generation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Signal: Firmographics, Funding & News Enrichment Turn a company name or domain into a structured, agent-ready account intelligence dataset. **Company Signal** aggregates firmographics, funding round histories, recent news headlines, and hiring indicators into a single normalized record. Whether you are powering B2B SDR enrichment, VC deal-flow research, market monitoring, or direct Model Context Protocol (MCP) workflows for Claude Desktop and Cursor, Company Signal delivers high-intent data without token-bloating HTML noise. --- ### 🚀 Key Features * **Multi-Source Signal Aggregation:** Scrapes direct website metadata, about-page signals, Google News feeds, and public funding announcements in parallel. * **Funding Deduplication Engine:** Intelligently groups and deduplicates public funding events across multiple news outlets by round type, date, and dollar amount. * **Agent & MCP Ready:** Outputs standardized JSON tailored for AI context windows, eliminating raw HTML noise and prompt overhead. * **Accuracy & Relevance Guard:** Filters out unrelated press coverage for companies with common English brand names (e.g., *Next*, *Adobe*). * **Confidence Scoring:** Assigns an explicit accuracy score (`0.0` to `1.0`) to every record so downstream workflows know when data is verified. --- ### 📥 Input Parameters | Parameter | Type | Required | Description | | :--- | :--- | :--- | :--- | | `companies` | Array | **Yes** | List of target objects with `domain` and/or `name` (e.g., `[{"domain": "stripe.com", "name": "Stripe"}]`). | | `includeNews` | Boolean | No | Search for and return recent press headlines (Default: `true`). | | `includeFunding` | Boolean | No | Detect public funding events and build a funding timeline (Default: `true`). | | `maxNewsItems` | Integer | No | Maximum number of news items to collect per company (Default: `5`, Max: `20`). | --- ### 📤 Output Schema Example ```json { "companyName": "Vercel", "domain": "vercel.com", "resolvedAt": "2026-07-23T13:10:10.718Z", "confidence": 0.75, "sourcesUsed": ["website", "about-page", "news", "funding-news"], "firmographics": { "title": "Agentic Infrastructure - Vercel", "description": "The autonomous stack for every app and agent.", "siteName": "Vercel" }, "funding": { "detected": true, "lastRound": { "headline": "Vercel Raises $300 Million in Series F at $9.3 Billion Valuation", "amount": "$300 Million", "roundType": "Series F", "mentionCount": 2, "publishedAt": "2025-10-01T07:00:00.000Z" }, "fundingHistory": [ { "headline": "Vercel Raises $300 Million in Series F...", "amount": "$300 Million", "roundType": "Series F", "publishedAt": "2025-10-01T07:00:00.000Z" } ] }, "news": [ { "title": "Vercel Acquires Talent Behind Egypt’s Stakpak to Build Agentic Infrastructure", "url": "[https://news.google.com/](https://news.google.com/)...", "publishedAt": "2026-07-20T09:27:04.000Z", "source": "TechAfrica News" } ] } # Actor input Schema ## `companies` (type: `array`): List of companies to analyze (domain or name). ## `includeNews` (type: `boolean`): Fetch recent news headlines from Google News RSS. ## `includeFunding` (type: `boolean`): Detect public funding events from news sources. ## `maxNewsItems` (type: `integer`): Maximum news articles per company. ## Actor input object example ```json { "companies": [ { "domain": "stripe.com", "name": "Stripe" }, { "domain": "openai.com", "name": "OpenAI" } ], "includeNews": true, "includeFunding": true, "maxNewsItems": 5 } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "companies": [ { "domain": "stripe.com", "name": "Stripe" }, { "domain": "openai.com", "name": "OpenAI" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("complex_intricate_networks/company-research-ai").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "companies": [ { "domain": "stripe.com", "name": "Stripe", }, { "domain": "openai.com", "name": "OpenAI", }, ] } # Run the Actor and wait for it to finish run = client.actor("complex_intricate_networks/company-research-ai").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 '{ "companies": [ { "domain": "stripe.com", "name": "Stripe" }, { "domain": "openai.com", "name": "OpenAI" } ] }' | apify call complex_intricate_networks/company-research-ai --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=complex_intricate_networks/company-research-ai", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Company Signal - AI Company Research", "description": "Turn any company name or domain into a structured account-research dataset. Automatically extract firmographics, multi-source funding history, recent news, and hiring indicators. Agent-ready JSON format built for MCP, Claude, Cursor, CRM sync, or CSV export.", "version": "0.0", "x-build-id": "xZQxWtaSs8Tr8oyCj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/complex_intricate_networks~company-research-ai/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-complex_intricate_networks-company-research-ai", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/complex_intricate_networks~company-research-ai/runs": { "post": { "operationId": "runs-sync-complex_intricate_networks-company-research-ai", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/complex_intricate_networks~company-research-ai/run-sync": { "post": { "operationId": "run-sync-complex_intricate_networks-company-research-ai", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "companies" ], "properties": { "companies": { "title": "Companies List", "type": "array", "description": "List of companies to analyze (domain or name)." }, "includeNews": { "title": "Include News", "type": "boolean", "description": "Fetch recent news headlines from Google News RSS.", "default": true }, "includeFunding": { "title": "Include Funding Signals", "type": "boolean", "description": "Detect public funding events from news sources.", "default": true }, "maxNewsItems": { "title": "Max News Items", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum news articles per company.", "default": 5 } } }, "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 } } } } } } } } } } ```