How I Automated News Discovery with n8n (439K Views, €0 Spent)

Source: Dev.to

Overview

I’m building AKCACHE.io, a managed database service focused on EU digital sovereignty. My marketing depends on catching relevant EU policy news early, but manually scanning news sites daily was killing my productivity.

Then I got lucky. I found a German government report about US cloud access and posted it to r/europe. The result: 439 K views, 2.9 K upvotes, 229 comments – all organic. Zero ad spend.

Link to the post

I’ve spent money on ads before. To get even 50 K impressions would cost thousands of euros. This single post drove more qualified traffic than months of paid campaigns.

The problem: I can’t manually hunt for articles like this every day. So I did what any developer would do: I automated it.

The Solution: n8n News Discovery Pipeline

I already host n8n on my server, so the setup cost was €0. Here’s how it works.

Step 1: Aggregate News Sources

The workflow pulls from multiple RSS feeds every 6 hours:

• heise.de (German tech news)
• Ars Technica
• Euractiv (EU policy)
• EUobserver
• TechCrunch
• The Verge
• Google News RSS (custom search query)

Step 2: Filter by Keywords

After merging all sources, I filter for the last 6 hours (since the workflow runs every 6 hours) and use JavaScript to check for relevant keywords:

const keywords = [
  'cloud act',
  'fisa',
  'digital sovereignty',
  'gdpr',
  'eu cloud',
  'data residency',
  'schrems',
  'gaia-x',
  // etc.
];

This cuts down ~100 articles to maybe 10–15 relevant ones.

Step 3: AI Relevance Scoring

Each article that passes keyword filtering goes to GPT‑4o‑mini for analysis:

• Score 1‑10 for relevance
• Extract key topics
• Determine urgency (high/medium/low)
• Suggest post angle

Cost consideration: I use GPT‑4o‑mini for cost efficiency, but watch the token‑per‑minute limit, so I added a 1‑minute wait between API calls.

Step 4: Store and Notify

Articles scoring 7+ get saved to PostgreSQL and sent to me via email with:

• Title and score
• Why it matters
• Suggested post hook
• One‑click link to generate a draft

Step 5: Auto‑Generate Reddit Posts (Human‑in‑Loop)

Each email contains a clickable link that triggers a second workflow via a GET request. When I click it:

1. AI fetches the full article
2. Generates a Reddit post title and body
3. Naturally mentions my product where relevant
4. Returns a formatted post ready to copy/paste

I intentionally don’t auto‑post. I want automation for the tedious research part, not the human‑judgment part.

The Results

Before automation

• 30 + minutes daily scanning news
• Missed ~80 % of relevant articles
• Inconsistent posting

After automation

• ~2 minutes daily reviewing AI‑filtered results
• Catch articles within 6 hours of publication
• Consistent content pipeline

Best part: The whole flow runs on my existing server. No SaaS subscriptions, no external dependencies.

Technical Details

Workflow triggers

• Schedule: Every 6 hours starting at 00:00
• Webhook: Manual trigger via URL for generating posts

Stack

• n8n (self‑hosted)
• PostgreSQL (article storage)
• OpenAI GPT‑4o‑mini
• Standard email node

You can adapt this for any use case – just change the RSS sources and keywords to match what you’re tracking.

Questions? Ask in the comments.