Building an Autonomous AI News Agent with n8n & Bright Data (Part 1)

Estimated reading time: ~6 minutes

Key Takeaways

24/7 Market Monitoring — Build a system that tracks an entire industry without human intervention.
Hybrid Scraper Architecture — Combine Jina AI for standard sites with Bright Data for protected sources.
URL Deduplication — Use an internal database to prevent redundant AI processing and save costs.
Part 1 of 3 — This video covers the Ingestion Engine; Parts 2 & 3 cover AI processing and publishing.

Is 24/7 Industry Monitoring Possible Without Human Analysts?

That was the challenge I set out to solve for the Black Sea agricultural market. We needed a system that could track wheat prices, logistics updates, and market analytics in real-time, translate them, and publish reports automatically.

Today, I am releasing Part 1 of a 3-part video series breaking down the exact architecture of this system.

The Challenge: Ingestion at Scale

The first hurdle in any automation project is getting the data. We faced two distinct problems:

Standard Sites: Easy to read, but messy formatting.
Protected Sites: Heavy anti-bot measures (Cloudflare, IP bans).

The Solution: A Hybrid Scraper

In this video, I show you how I built the "Ingestion Engine" using n8n.

Jina AI: We use this for standard sites to instantly convert HTML to clean Markdown.
Bright Data: For the difficult sites (like APK-Inform), we utilize Bright Data's Web Unlocker infrastructure to manage IP rotation and browser fingerprinting automatically.

Watch Part 1: The Scraper Architecture

In this deep dive, I walk you through the n8n canvas, explaining how we normalize data, filter noise using JavaScript logic, and—crucially—how we use an internal database to deduplicate URLs to save money on AI credits.

What's Next?

This workflow is just the beginning. In Part 2, we will look at how Generative AI acts as our "Chief Editor" to write SEO-optimized articles based on this data.