0%
reduction in video production time
0%
reduction in manual news monitoring time
0%
faster access to summarized updates
0%
centralized storage of scraped and summarized news data
0-60%
improvement in decision-making speed
0x
scalability efficiency
PROJECT OVERVIEW
Staying updated with the latest news typically requires manual browsing, filtering, and summarizing information from multiple sources. To automate this process, we built a News Scraping & News Chat AI Agent using n8n.
The system combines automated news scraping, AI-powered summarization, structured storage, and conversational delivery. It integrates: ScrapingDog for Google News scraping, Google Gemini for summarization, Google Sheets for structured storage.
The solution consists of two connected workflows: News scraping and summarization workflow, Chat-based AI agent workflow for on-demand news access.
This enables real-time monitoring and interactive news consumption.
Objectives
- Automate Google News scraping
- Generate AI-powered summaries
- Provide chat-based access to latest news
- Store structured news data for reporting
- Build a modular and reusable automation system
- Enable real-time information delivery
The Challenge
Manual news monitoring presents several challenges:
The goal was to create a fully automated, AI-driven news intelligence system.
THE SOLUTION ARCHITECTURE (HOW DOES IT WORK?)
We designed two interconnected workflows inside n8n that handle scraping, summarization, storage, and conversational response.
How Does It Work?
Step 1: Chat Trigger
- User sends a message like: “Give me today’s latest news.”
- Chat Message Received trigger activates the AI agent workflow
Step 2: AI Intent Understanding
- AI Agent analyzes user request
- Identifies need for latest news data
Step 3: Trigger Scraping Workflow
- Chat AI Agent calls the scraping workflow
- Uses “When Executed by Another Workflow” trigger
- Ensures fresh data retrieval
Step 4: Google News Scraping
- HTTP request sent to ScrapingDog
- Google News data retrieved in JSON format
Step 5: Split & Process Articles
- Split Out node separates each article
- Edit Fields extracts:
Title
Snippet
Source
Update time
Link
Step 6: Data Preprocessing
- JavaScript node cleans and normalizes data
- Ensures consistency before AI summarization
Step 7: AI News Summarization
- Google Gemini generates concise summaries
- Converts raw news into human-readable insights
Step 8: Store in Google Sheets
- Structured records appended to Google Sheets
- Enables persistent storage and reporting
Step 9: Conversational Response
- Summarized data returned to chat agent
- User receives a clear, conversational news summary
Technology stack Included
Key Benefits
Fully automated Google News scraping
AI-powered concise summaries
Real-time conversational access
Structured and report-ready data storage
Modular and scalable architecture
Easy integration with dashboards and other systems
The Solution Is Ideal For
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Closure
This implementation demonstrates how automation, AI summarization, and conversational interfaces can transform news monitoring into an intelligent, real-time system.
By leveraging n8n for orchestration, ScrapingDog for data collection, and Google Gemini for intelligent summarization, we created a scalable AI news assistant capable of delivering structured, conversational insights instantly.
The architecture can be extended to industry-specific news tracking, competitor monitoring, financial updates, or social media trend analysis making it a powerful foundation for AI-driven information systems.
