Web Scraping & Research Engine
8 workflows that pull structured data off any website — including the JavaScript-heavy ones that break normal scrapers
What This Pack Does
Extracts structured data from web pages across the full range of difficulty — static HTML, JavaScript-rendered pages, multi-page crawls, and data locked inside images — then stores and synthesises it.
Who It's For
Anyone who has written a scraper, watched it break when the site changed, and wants extraction that degrades gracefully. Useful for market research, lead lists, price monitoring, and competitive tracking.
Expected Outcome
Turn any set of web pages into structured, queryable data without writing a scraper per site
Highlights
- Pipeline: Fetch → Extract → Crawl → Render → Store → Synthesise
- AI extraction that survives layout changes instead of breaking on them
- Selenium workflow for JavaScript-only sites that plain HTTP cannot read
- Vision-based extraction for data trapped in images and rendered tables
- Deep research workflow chaining search, scrape, and synthesis into one report
Included Workflows(8)
Fetch
Extract
Crawl
Render
Store
Synthesise
Setup Requirements
An n8n instance and OpenAI API key cover most workflows. Vision-based extraction needs a ScrapingBee key, deep research needs Apify, and the Selenium workflow needs a reachable Selenium instance (self-hosted n8n makes this easier).
Example Use Case
A market researcher needs pricing and feature data on 60 competitor products. They use the multi-page crawl workflow to collect the product URLs, the AI extraction workflow to pull structured fields without writing a per-site selector, and the vision workflow for three vendors whose specs only exist inside comparison images. Everything lands in Google Sheets, and the deep research workflow produces a written summary of where each competitor sits — a job that previously took a week of manual collection.
Primary Integrations
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