Overview
This workflow automates the process of scraping AI-related articles from TechCrunch, classifying them using a GPT-4.1 Nano agent, and distributing the results to Google Sheets and Telegram channels.
Key Features
- Automated Scheduling: Initiates at set intervals using a schedule trigger.
- Web Scraping: Extracts the latest AI articles from TechCrunch via HTTP requests and HTML parsing.
- Data Processing: Splits and processes URLs, cleans data, and prepares it for analysis.
- AI Classification: Utilizes a GPT-4.1 Nano agent to classify and summarize articles for relevance and quality.
- Batch Processing: Handles multiple articles efficiently with batch and loop nodes.
- Multi-Channel Output: Sends structured results to Google Sheets for record-keeping and Telegram for instant notifications.
Benefits
- Time Savings: Eliminates manual research and data entry, streamlining content monitoring.
- Accuracy: Ensures only relevant, high-quality AI articles are surfaced and shared.
- Real-Time Updates: Delivers timely notifications to stakeholders via Telegram.
- Centralized Records: Maintains a searchable archive in Google Sheets for future reference.
Use Cases
- Market Intelligence: Stay updated on AI trends and news for competitive analysis.
- Content Curation: Quickly identify and share relevant articles with teams or audiences.
- Research Automation: Support analysts and marketers with up-to-date, classified information.
Integrations
- TechCrunch (web scraping)
- GPT-4.1 Nano (AI classification)
- Google Sheets (data storage)
- Telegram (notifications)
