Games & Esports News Intelligence Pipeline (AI-Powered) avatar
Games & Esports News Intelligence Pipeline (AI-Powered)

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Games & Esports News Intelligence Pipeline (AI-Powered)

Games & Esports News Intelligence Pipeline (AI-Powered)

Developed by

bySeitz AI & Automation

bySeitz AI & Automation

Maintained by Community

This actor is a powerful data-gathering tool that transforms raw news from top RSS feeds (focused on Video Games, Esports, and Gaming Culture) into structured, actionable intelligence. It uses DuckDuckGo News Search to gather real-time context and an LLM (OpenAI) to perform advanced analysis.

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💸 Venture Capital Intelligence Pipeline (AI Powered)

This Apify Actor processes Venture Capital and Tech funding news from major RSS feeds and transforms headlines into structured, actionable intelligence using the Google Search Results Scraper's AI Overview and combined Language Model (LLM) analysis.

This pipeline replaces unreliable traditional web scraping (Playwright/Trafilatura) with a robust, two-stage AI analysis approach, ensuring high data uniformity and value for VC professionals, investors, and analysts.


✨ New Functionality and Value Proposition

The actor now delivers reliable, structured data by pivoting entirely away from content scraping and towards intelligent aggregation and analysis.

FeatureNew Method (AI Pipeline)Value to End-User
Data ReliabilityHighly reliable via Apify's managed Google Search Scraper.Guaranteed, uniform summary data, bypassing paywalls.
Core SummaryAI Overview from Google Search, providing a concise, aggregated summary.High-quality, standardized news digest.
Sentiment AnalysisAdded: Sentiment label (Positive, Neutral, Negative).Quick assessment of the market/investor mood toward the news.
CategorizationAdded: Primary market topic (Funding Round, Acquisition/Exit, Venture Strategy, etc.).Easy data filtering for deal flow, trend spotting, and competitive analysis.
Key EntitiesAdded: List of 1-3 major companies, investors, or founders.Enables immediate linking of news to specific startups or VC firms.

⚙️ How the Pipeline Works

The workflow is managed by LangGraph and consists of three robust steps:

  1. RSS Fetcher: Collects and deduplicates articles from specified VC RSS feeds (TechCrunch, Crunchbase, Forbes VC, etc.).
  2. Google Search AI Summary (Pay Point 1): Uses the article title as a query input for the apify/google-search-results Actor with the aiModeOnly setting enabled. This reliably extracts the AI Overview, which serves as the article's core summary.
  3. Combined LLM Analysis (Pay Point 2): The AI Overview text is passed to a single, structured LLM call (e.g., GPT-3.5-turbo). This call simultaneously performs Sentiment Analysis, Categorization, and Key Entity Extraction, returning all analytical data in one efficient JSON object.

💰 Cost Structure (2 Pay Points per Article)

The cost structure is based on two separate, valuable service calls for every successfully processed article:

Pay PointServiceEvent NamePurpose
1 (Search)Google Search Results Scraperarticle-fetchCovers the cost of running the Google Search Actor and acquiring the AI Overview.
2 (Analysis)OpenAI/External LLMllm-analysis-tokens-usedCovers the token cost for the single, combined LLM request that generates the sentiment, category, and entities.

📥 Output Dataset Schema (DatasetRecord)

The final output is a structured JSON object pushed to the Apify dataset, containing only the high-value data points:

Field NameTypeDescription
sourcestringSource of the article (e.g., TechCrunch).
titlestringHeadline of the article.
urlstringFull URL of the original article.
publishedstring (Optional)Date and time the article was published.
summarystring (Optional)AI Overview summary retrieved from Google Search.
sentimentstring (Optional)Sentiment label: Positive, Neutral, Negative, or N/A.
categorystring (Optional)Primary VC topic: (e.g., Funding Round, Acquisition/Exit).
key_entitiesarray of strings (Optional)Key entities: List of up to 3 major companies/investors mentioned.