# B2B Signal Scout (`amcllc/b2b-signal-scout`) Actor AI Powered Business Leads Scout - **URL**: https://apify.com/amcllc/b2b-signal-scout.md - **Developed by:** [AMCLLC](https://apify.com/amcllc) (community) - **Categories:** AI, Lead generation - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.01 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## B2B Signal Scout Turn a company website into a lead record you can act on. B2B Signal Scout crawls the pages buyers care about (pricing, contact, about, careers, legal) and produces a clean dataset with contact signals plus AI-written lead intelligence: what they sell, who they sell to, lead score, and outreach angles. ### Who It's For - SDRs and outbound teams building targeted lists - Agencies doing prospect research at scale - Founders validating markets and building pipeline ### What You Get (Per Company) - Contact signals: emails, phones, LinkedIn, X/Twitter, GitHub, contact form detection - Intent clues: pricing pages found, careers page found, basic website footprint - AI enrichment: summary, what they sell, target customers, lead score + reason, outreach angles ### Output - Dataset: one item per company (usually one per start URL origin). - Key-value store: `OUTPUT` includes a run summary and AI enrichment stats. Example dataset fields (abridged): ```json { "companyUrl": "https://example.com", "emails": ["sales@example.com"], "pricingPages": ["https://example.com/pricing"], "aiLeadScore": 78, "aiWhatTheySell": "...", "aiOutreachAngles": ["..."] } ```` ### Notes - Respect target sites' terms and robots rules. - This Actor uses an HTTP crawler for speed; JavaScript-heavy sites may have limited extraction. # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## `maxRequestsPerCrawl` (type: `integer`): Maximum number of requests that can be made by this crawler. ## `maxDepth` (type: `integer`): Maximum link depth from the start URLs. Set to 0 to only process the start URLs and the predefined paths. ## `sameHostnameOnly` (type: `boolean`): If enabled, the crawler only enqueues links from the same hostname as the start URL. ## `includePaths` (type: `array`): Paths that will be enqueued for each start URL origin (useful for pricing/contact/legal pages). ## `maxConcurrency` (type: `integer`): Maximum number of concurrent requests. ## `requestDelayMillis` (type: `integer`): Optional delay applied at the start of each request handler to reduce load on target servers. ## `proxyConfiguration` (type: `object`): Use Apify Proxy for IP rotation to prevent blocking. ## `debugLog` (type: `boolean`): Enable verbose logging (useful for development). ## `aiEnrichmentEnabled` (type: `boolean`): When enabled, the Actor uses OpenAI to convert crawl evidence into structured lead intelligence. ## `openaiApiKey` (type: `string`): Optional override for the OpenAI API key. Prefer setting OPENAI\_API\_KEY as an Actor secret instead of passing it in input. ## `openaiModel` (type: `string`): Model used for structured enrichment. GPT-4.1 mini is a good default for cost-sensitive production runs. ## `aiMaxCompanies` (type: `integer`): Maximum number of companies that will be sent to the AI model for enrichment. ## `aiConcurrency` (type: `integer`): How many AI enrichment requests can run in parallel. ## `aiMaxInputCharsPerCompany` (type: `integer`): Maximum crawl evidence characters sent to the AI model for each company. ## `aiMaxOutputTokens` (type: `integer`): Maximum output tokens requested from the AI model per company. ## `aiTemperature` (type: `number`): Sampling temperature for AI enrichment. Lower values are more deterministic. ## `apifyPpeEnabled` (type: `boolean`): If you monetize this Actor with Apify pay-per-event, enable this to charge for each AI enrichment. Disable for local development. ## `apifyPpeEventName` (type: `string`): Event name used when charging via Actor.charge(). Configure the same event in Apify Console (Publication -> Monetization). ## `apifyPpeChargeOn` (type: `string`): When to charge the PPE event: 'attempt' (before OpenAI call) or 'success' (after a successful enrichment). ## `apifyPpeStopOnLimit` (type: `boolean`): If enabled, the Actor stops further AI enrichments when the user's max cost limit is reached (remaining items will have aiSkippedReason=charge\_limit\_reached). ## Actor input object example ```json { "startUrls": [ { "url": "https://crawlee.dev" } ], "maxRequestsPerCrawl": 100, "maxDepth": 2, "sameHostnameOnly": true, "includePaths": [ "/", "/pricing", "/contact", "/about", "/company", "/careers", "/jobs", "/security", "/legal", "/privacy", "/terms", "/cookie", "/cookies", "/status" ], "maxConcurrency": 20, "requestDelayMillis": 0, "debugLog": false, "aiEnrichmentEnabled": true, "openaiModel": "gpt-4.1-mini", "aiMaxCompanies": 25, "aiConcurrency": 3, "aiMaxInputCharsPerCompany": 12000, "aiMaxOutputTokens": 700, "aiTemperature": 0.2, "apifyPpeEnabled": true, "apifyPpeEventName": "ai-enrichment", "apifyPpeChargeOn": "attempt", "apifyPpeStopOnLimit": true } ``` # Actor output Schema ## `overview` (type: `string`): No description ## `report` (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 = { "startUrls": [ { "url": "https://crawlee.dev" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("amcllc/b2b-signal-scout").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 = { "startUrls": [{ "url": "https://crawlee.dev" }] } # Run the Actor and wait for it to finish run = client.actor("amcllc/b2b-signal-scout").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 '{ "startUrls": [ { "url": "https://crawlee.dev" } ] }' | apify call amcllc/b2b-signal-scout --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=amcllc/b2b-signal-scout", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "B2B Signal Scout", "description": "AI Powered Business Leads Scout", "version": "0.1", "x-build-id": "vwvcG8592hDM8flUI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/amcllc~b2b-signal-scout/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-amcllc-b2b-signal-scout", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/amcllc~b2b-signal-scout/runs": { "post": { "operationId": "runs-sync-amcllc-b2b-signal-scout", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/amcllc~b2b-signal-scout/run-sync": { "post": { "operationId": "run-sync-amcllc-b2b-signal-scout", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxRequestsPerCrawl": { "title": "Max Requests per Crawl", "type": "integer", "description": "Maximum number of requests that can be made by this crawler.", "default": 100 }, "maxDepth": { "title": "Max Crawl Depth", "type": "integer", "description": "Maximum link depth from the start URLs. Set to 0 to only process the start URLs and the predefined paths.", "default": 2 }, "sameHostnameOnly": { "title": "Same Hostname Only", "type": "boolean", "description": "If enabled, the crawler only enqueues links from the same hostname as the start URL.", "default": true }, "includePaths": { "title": "Include Paths", "type": "array", "description": "Paths that will be enqueued for each start URL origin (useful for pricing/contact/legal pages).", "default": [ "/", "/pricing", "/contact", "/about", "/company", "/careers", "/jobs", "/security", "/legal", "/privacy", "/terms", "/cookie", "/cookies", "/status" ], "items": { "type": "string" } }, "maxConcurrency": { "title": "Max Concurrency", "type": "integer", "description": "Maximum number of concurrent requests.", "default": 20 }, "requestDelayMillis": { "title": "Request Delay (ms)", "type": "integer", "description": "Optional delay applied at the start of each request handler to reduce load on target servers.", "default": 0 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Use Apify Proxy for IP rotation to prevent blocking." }, "debugLog": { "title": "Debug logging", "type": "boolean", "description": "Enable verbose logging (useful for development).", "default": false }, "aiEnrichmentEnabled": { "title": "AI enrichment enabled", "type": "boolean", "description": "When enabled, the Actor uses OpenAI to convert crawl evidence into structured lead intelligence.", "default": true }, "openaiApiKey": { "title": "OpenAI API key", "type": "string", "description": "Optional override for the OpenAI API key. Prefer setting OPENAI_API_KEY as an Actor secret instead of passing it in input." }, "openaiModel": { "title": "OpenAI model", "type": "string", "description": "Model used for structured enrichment. GPT-4.1 mini is a good default for cost-sensitive production runs.", "default": "gpt-4.1-mini" }, "aiMaxCompanies": { "title": "Max AI-enriched companies", "type": "integer", "description": "Maximum number of companies that will be sent to the AI model for enrichment.", "default": 25 }, "aiConcurrency": { "title": "AI concurrency", "type": "integer", "description": "How many AI enrichment requests can run in parallel.", "default": 3 }, "aiMaxInputCharsPerCompany": { "title": "AI input chars per company", "type": "integer", "description": "Maximum crawl evidence characters sent to the AI model for each company.", "default": 12000 }, "aiMaxOutputTokens": { "title": "AI max output tokens", "type": "integer", "description": "Maximum output tokens requested from the AI model per company.", "default": 700 }, "aiTemperature": { "title": "AI temperature", "type": "number", "description": "Sampling temperature for AI enrichment. Lower values are more deterministic.", "default": 0.2 }, "apifyPpeEnabled": { "title": "Pay per event (PPE) enabled", "type": "boolean", "description": "If you monetize this Actor with Apify pay-per-event, enable this to charge for each AI enrichment. Disable for local development.", "default": true }, "apifyPpeEventName": { "title": "PPE event name", "type": "string", "description": "Event name used when charging via Actor.charge(). Configure the same event in Apify Console (Publication -> Monetization).", "default": "ai-enrichment" }, "apifyPpeChargeOn": { "title": "PPE charge timing", "enum": [ "attempt", "success" ], "type": "string", "description": "When to charge the PPE event: 'attempt' (before OpenAI call) or 'success' (after a successful enrichment).", "default": "attempt" }, "apifyPpeStopOnLimit": { "title": "Stop when user limit reached", "type": "boolean", "description": "If enabled, the Actor stops further AI enrichments when the user's max cost limit is reached (remaining items will have aiSkippedReason=charge_limit_reached).", "default": true } } }, "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 } } } } } } } } } } ```