[n8n] Intelligent logic for crisis monitoring workflows

As an engineer, I’m used to monitoring server logs and uptime. But I realized that for brand reputation or high-level risk, the "outage" often starts in the news before it hits our internal dashboards. For a while, I relied on Google Alerts and basic keyword scrapers. **It was a disaster.** My Slack was a graveyard of false positives and "noisy" mentions that had zero impact on our business. I got tired of the "boy who cried wolf" notifications, so I automated a more "intelligent" logic using n8n and Perigon. **How I cut the noise by 90%:** The breakthrough wasn't just "better keywords"—it was adding logical filters to the workflow: 1. **The "3-Source Rule":** I configured the Perigon node to only trigger if an event is reported by at least **3 unique news sources**. This instantly filtered out the "one-off" blog posts and random noise. 2. **Category Scoping:** Instead of a global search, I locked the workflow to `Tech` and `Business` categories. If a keyword appears in a sports article, I don't see it. 3. **The AI Executive Brief:** Instead of sending me 15 links to the same story, the workflow uses a `Summarize` node to analyze the **Cluster** of news and write a 180-word executive brief. It tells me: *What happened, Business Impact, and What to watch next.* Happy to share the workflow