# News Intelligence Pro (AI Powered) (`obsequious_ontologist/news-intelligence-pro`) Actor Turn news into business intelligence. AI-powered sentiment analysis, brand monitoring, and competitor tracking from 50+ sources. Get market insights, trend alerts, and reputation management in real-time. - **URL**: https://apify.com/obsequious\_ontologist/news-intelligence-pro.md - **Developed by:** [Dave Thomson](https://apify.com/obsequious_ontologist) (community) - **Categories:** News, AI, SEO tools - **Stats:** 11 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## News Intelligence Pro **AI-powered news aggregation and analysis platform for business intelligence, brand monitoring, and market research.** Built for the Apify $1M Challenge by Serup.ai. Transform raw news data into actionable business insights with advanced AI analysis. ### 🧠 Key Features #### Multi-Source News Aggregation - **Major News Outlets**: CNN, BBC, Reuters, AP News, Bloomberg, Financial Times, TechCrunch - **Real-time Monitoring**: Continuous news tracking from trusted sources - **Global Coverage**: Multi-language support and regional sources - **Smart Filtering**: Keyword-based content filtering and relevance scoring #### AI-Powered Analysis - **Sentiment Analysis**: Emotional tone detection with confidence scores - **Smart Summarization**: AI-generated key points and summaries - **Topic Classification**: Automatic categorization into business-relevant topics - **Entity Recognition**: Extract people, companies, locations, and events - **Trend Detection**: Identify emerging stories and viral content #### Business Intelligence - **Brand Monitoring**: Track mentions of your company or competitors - **Market Sentiment**: Industry-specific mood tracking and analysis - **Competitor Analysis**: Share of voice and sentiment comparison - **Breaking News Detection**: Identify trending stories and viral content - **Historical Analysis**: Trend patterns and forecasting ### 💰 Flexible Pricing Tiers #### Free Tier - 50 articles/month with full AI analysis - Perfect for testing and small projects - No credit card required #### Built-in AI Tier - **$6 per 1,000 articles** analyzed - Full AI processing included (sentiment, summarization, categorization) - Built-in OpenAI integration - no API setup required - Content moderation and safety controls - Rate limiting and cost controls #### Enterprise BYOK Tier - **$2 per 1,000 articles** (infrastructure only) - Bring Your Own OpenAI API Key for unlimited usage - No usage caps or rate limits - Advanced enterprise features - Priority support ### 🚀 Quick Start #### Simple Example - Basic News Feed (No AI) ```json { "news_sources": ["cnn", "bbc"], "enable_ai_analysis": false, "date_range": "1d", "max_articles": 100 } ```` **Use case**: Free tier - Basic news aggregation without AI analysis. Perfect for RSS replacement or simple monitoring. #### Medium Example - Brand Monitoring (Built-in AI) ```json { "news_sources": ["reuters", "bloomberg", "tech_crunch"], "keywords": "Tesla, Elon Musk, electric vehicles", "enable_ai_analysis": true, "sentiment_analysis": true, "entity_extraction": true, "date_range": "7d", "max_articles": 500, "languages": ["en"], "industry_focus": ["technology", "business"] } ``` **Use case**: Built-in AI ($6/1K articles) - Track brand sentiment and mentions. Ideal for PR teams and brand managers. #### Complex Example - Enterprise Intelligence (BYOK) ```json { "news_sources": ["reuters", "bloomberg", "financial_times", "ap_news", "tech_crunch"], "keywords": "AI regulation, ChatGPT, Microsoft, Google, artificial intelligence policy", "enable_ai_analysis": true, "openai_api_key": "sk-YOUR-OPENAI-KEY", "sentiment_analysis": true, "summarization": true, "topic_classification": true, "entity_extraction": true, "date_range": "30d", "max_articles": 10000, "languages": ["en", "es", "fr"], "industry_focus": ["technology", "finance", "politics"] } ``` **Use case**: BYOK tier ($2/1K articles) - Unlimited AI analysis with your own OpenAI key. Perfect for enterprises, hedge funds, and research firms needing massive scale. ### 📊 Output Data Structure ```json { "title": "Breaking: AI Company Announces Major Breakthrough", "url": "https://example.com/article", "published_at": "2025-01-01T12:00:00Z", "source": { "name": "TechCrunch", "domain": "techcrunch.com", "credibility_score": 0.82 }, "analysis": { "sentiment": { "score": 0.75, "label": "positive", "confidence": 0.89, "reasoning": "Article discusses positive breakthrough and market opportunity" }, "summarization": { "summary": "AI company reveals new technology that could revolutionize the industry...", "key_points": [ "New AI technology announced", "Significant market potential identified", "Industry experts react positively" ] }, "classification": { "categories": ["Technology", "Business", "AI/ML"], "entities": { "companies": ["OpenAI", "Microsoft"], "people": ["CEO Name"], "locations": ["San Francisco"] }, "keywords": ["AI", "breakthrough", "technology", "investment"] }, "trending_score": 0.78 }, "processing_session": { "sources": ["tech_crunch"], "ai_enabled": true, "date_range": "1d" } } ``` ### 🎯 Use Cases #### Marketing & PR Teams - **Brand Mention Tracking**: Monitor all mentions across news sources - **Crisis Management**: Real-time alerts for negative sentiment - **Campaign Impact**: Measure media coverage and sentiment - **Competitor Intelligence**: Track competitor news and market position #### Financial Services - **Market Sentiment Analysis**: Track investor mood and market trends - **Earnings Coverage**: Monitor financial news and analyst opinions - **Regulatory Updates**: Stay informed on policy changes - **ESG Monitoring**: Track environmental and social impact news #### Business Intelligence - **Industry Trends**: Identify emerging market opportunities - **Competitive Analysis**: Monitor competitor activities and announcements - **Market Research**: Gather insights on customer sentiment and trends - **Strategic Planning**: Data-driven decision making with news intelligence #### Startups & Scale-ups - **Fundraising Intel**: Track VC news and funding announcements - **Market Timing**: Identify optimal timing for product launches - **Partnership Opportunities**: Monitor potential partner companies - **Thought Leadership**: Track industry discussions and trending topics ### 🔧 Technical Features #### Enterprise-Grade Architecture - **High-Performance Processing**: Analyze 1000+ articles in minutes - **Intelligent Rate Limiting**: Respectful request throttling - **Robust Error Handling**: Automatic retry and recovery - **Content Moderation**: Built-in safety and content filtering - **Dataset Export**: Rich data output in Apify dataset format #### Data Quality & Reliability - **Source Credibility Scoring**: Quality ratings for news sources - **Duplicate Detection**: Smart deduplication across sources - **Content Validation**: Ensure article quality and relevance - **Historical Data**: Time-series analysis and trend tracking - **Export Options**: JSON, CSV, Excel with rich metadata #### AI & Machine Learning - **Advanced NLP**: State-of-the-art sentiment analysis and entity recognition - **Contextual Understanding**: Smart topic classification and trend detection - **Customizable Analysis**: Configure AI features based on your needs - **Cost Optimization**: Intelligent processing to minimize AI costs - **Multi-language Support**: Process news in multiple languages ### 🛡️ Security & Compliance #### Data Protection - **Secure Processing**: All data encrypted in transit and at rest - **Privacy Controls**: No personal data storage beyond processing - **Content Moderation**: Automatic filtering of inappropriate content - **Rate Limiting**: Built-in protections against abuse #### API Security - **Key Management**: Secure handling of user-provided API keys - **Access Controls**: User-specific data isolation - **Audit Logging**: Complete processing history and cost tracking - **Compliance Ready**: GDPR and data protection compliance ### 📈 Performance & Scaling #### Speed & Efficiency - **Fast Processing**: 8-10 articles analyzed per second - **Concurrent Operations**: Parallel processing for maximum throughput - **Smart Caching**: Optimized performance for repeated queries - **Minimal Latency**: Real-time processing and alerts #### Cost Management - **Transparent Pricing**: Clear cost breakdown and usage tracking - **Budget Controls**: Daily spending limits and alerts - **Usage Analytics**: Detailed cost analysis and optimization tips - **Flexible Billing**: Pay only for what you use ### 🏆 Competitive Advantages #### vs Basic News Scrapers - **AI Analysis Included**: Not just raw data - actionable insights - **Business Intelligence**: Designed for enterprise decision-making - **Multi-source Aggregation**: Comprehensive coverage in one tool - **Real-time Processing**: Live monitoring vs batch processing #### vs Premium News APIs - **Lower Cost**: $6 vs $10-20 per 1K articles from competitors - **Instant Setup**: No lengthy integration or contracts - **Built-in AI**: Advanced analysis without additional AI subscriptions - **Transparent Pricing**: Clear costs vs complex tiered pricing #### vs Custom Development - **Ready-to-Use**: Launch in minutes, not months - **Maintained & Updated**: Continuous improvements and new features - **Proven Reliability**: Enterprise-grade infrastructure - **Cost Effective**: Lower total cost than building in-house ### 🚀 Getting Started For complete setup instructions, see the [Apify documentation](https://docs.apify.com/platform/actors/development). #### Local Development ```bash apify run ``` #### Deploy to Apify Platform ```bash apify login apify push ``` *** **Transform your news monitoring from manual research to automated intelligence.** Start with our free tier and scale as you grow. No contracts, no hidden fees - just powerful news intelligence when you need it. # Actor input Schema ## `news_sources` (type: `array`): Select news sources to monitor. Choose from major outlets. ## `keywords` (type: `string`): Keywords, brand names, or topics to monitor (comma-separated). Leave empty to analyze all articles. ## `enable_ai_analysis` (type: `boolean`): Enable sentiment analysis, summarization, and categorization (uses built-in AI - costs $6 per 1,000 articles) ## `openai_api_key` (type: `string`): Provide your own OpenAI API key for unlimited usage (pricing: $2 per 1,000 articles). Leave empty to use built-in AI. ## `sentiment_analysis` (type: `boolean`): Analyze emotional tone of articles (positive, negative, neutral) ## `summarization` (type: `boolean`): Generate AI-powered summaries of long articles ## `topic_classification` (type: `boolean`): Automatically categorize articles by topic (Politics, Business, Tech, etc.) ## `entity_extraction` (type: `boolean`): Extract people, companies, locations, and events mentioned in articles ## `date_range` (type: `string`): Time period to analyze ## `max_articles` (type: `integer`): Maximum number of articles to analyze ## `languages` (type: `array`): Languages to include in analysis ## `industry_focus` (type: `array`): Focus on specific industries for enhanced analysis ## Actor input object example ```json { "news_sources": [ "cnn", "bbc", "reuters" ], "enable_ai_analysis": true, "sentiment_analysis": true, "summarization": true, "topic_classification": true, "entity_extraction": true, "date_range": "1d", "max_articles": 1000, "languages": [ "en" ], "industry_focus": [ "general" ] } ``` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("obsequious_ontologist/news-intelligence-pro").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = {} # Run the Actor and wait for it to finish run = client.actor("obsequious_ontologist/news-intelligence-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 '{}' | apify call obsequious_ontologist/news-intelligence-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=obsequious_ontologist/news-intelligence-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "News Intelligence Pro (AI Powered)", "description": "Turn news into business intelligence. AI-powered sentiment analysis, brand monitoring, and competitor tracking from 50+ sources. Get market insights, trend alerts, and reputation management in real-time.", "version": "0.0", "x-build-id": "pixWmrmZ6zLGqLlwo" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/obsequious_ontologist~news-intelligence-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-obsequious_ontologist-news-intelligence-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/obsequious_ontologist~news-intelligence-pro/runs": { "post": { "operationId": "runs-sync-obsequious_ontologist-news-intelligence-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/obsequious_ontologist~news-intelligence-pro/run-sync": { "post": { "operationId": "run-sync-obsequious_ontologist-news-intelligence-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "news_sources" ], "properties": { "news_sources": { "title": "News Sources", "minItems": 1, "maxItems": 10, "type": "array", "description": "Select news sources to monitor. Choose from major outlets.", "items": { "type": "string", "enum": [ "cnn", "bbc", "reuters", "ap_news", "tech_crunch", "bloomberg", "financial_times" ] }, "default": [ "cnn", "bbc", "reuters" ] }, "keywords": { "title": "Keywords & Brand Monitoring", "type": "string", "description": "Keywords, brand names, or topics to monitor (comma-separated). Leave empty to analyze all articles." }, "enable_ai_analysis": { "title": "Enable AI Analysis", "type": "boolean", "description": "Enable sentiment analysis, summarization, and categorization (uses built-in AI - costs $6 per 1,000 articles)", "default": true }, "openai_api_key": { "title": "OpenAI API Key (BYOK)", "type": "string", "description": "Provide your own OpenAI API key for unlimited usage (pricing: $2 per 1,000 articles). Leave empty to use built-in AI." }, "sentiment_analysis": { "title": "Sentiment Analysis", "type": "boolean", "description": "Analyze emotional tone of articles (positive, negative, neutral)", "default": true }, "summarization": { "title": "Article Summarization", "type": "boolean", "description": "Generate AI-powered summaries of long articles", "default": true }, "topic_classification": { "title": "Topic Classification", "type": "boolean", "description": "Automatically categorize articles by topic (Politics, Business, Tech, etc.)", "default": true }, "entity_extraction": { "title": "Entity Recognition", "type": "boolean", "description": "Extract people, companies, locations, and events mentioned in articles", "default": true }, "date_range": { "title": "Date Range", "enum": [ "1h", "6h", "1d", "3d", "7d", "30d" ], "type": "string", "description": "Time period to analyze", "default": "1d" }, "max_articles": { "title": "Maximum Articles", "minimum": 10, "maximum": 10000, "type": "integer", "description": "Maximum number of articles to analyze", "default": 1000 }, "languages": { "title": "Languages", "minItems": 1, "type": "array", "description": "Languages to include in analysis", "items": { "type": "string", "enum": [ "en", "es", "fr", "de", "it", "pt", "zh", "ja", "ko", "ar" ] }, "default": [ "en" ] }, "industry_focus": { "title": "Industry Focus", "type": "array", "description": "Focus on specific industries for enhanced analysis", "items": { "type": "string", "enum": [ "technology", "finance", "healthcare", "politics", "sports", "entertainment", "business", "science", "environment", "general" ] }, "default": [ "general" ] } } }, "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 } } } } } } } } } } ```