Automated Web Data Search, Extract and Summarization Workflow

This n8n workflow automates the process of searching web data, extracting relevant information, and generating concise summaries using advanced AI models. It is designed to streamline the retrieval and processing of online content for research, monitoring, or content curation purposes.

The workflow starts manually, allowing the user to trigger the process. It initiates a web scraping request to Bright Data’s API, targeting a specific dataset or snapshot. It then checks the progress of an existing data snapshot, downloading the dataset once ready.

Next, the workflow uses Bright Data’s API to trigger a new web search on platforms like Perplexity.ai, which is designed to gather relevant search results. The gathered data, often in HTML format, is then processed through a series of nodes that extract readable content, split the text into manageable chunks, and prepare it for AI-based processing.

Multiple AI nodes, including Google Gemini models, are deployed for different tasks: one for summarization of search results and another for extracting structured, readable data from HTML. This demonstrates AI’s ability to assist with content summarization, formatting, and analysis.

The entire process is monitored for errors, with wait nodes allowing for asynchronous data processing. Finally, the summarized and extracted data is sent to external endpoints via webhook notifications, making the results accessible for further use or analysis.

This workflow is highly practical for digital marketers, researchers, and developers aiming to automate and enhance their data collection, processing, and insight generation efforts from web sources.