Week 9: How We Built an AI-Powered News Analyst with n8n and Gemini
Staying on top of AI news is becoming harder each week, as the sheer volume of updates and noise continues to grow. The firehose of news, announcements, and research papers has become a full-time job to manage. You know the feeling: trying to separate meaningful patterns from fleeting hype, all while under pressure to keep yourself or your team informed about what truly matters.
Manual sifting through dozens of sources is inefficient and inconsistent. What if you miss a subtle signal, a new framework or a funding trend, that shifts the competitive landscape?
This is not a problem of having too little information; it’s a problem of having too much.
Turning the firehose into a feed
We’ve been thinking about this challenge and recently built a system to address it. We used n8n to orchestrate a workflow that acts as an automated analyst. This system is a clear example of building an AI Native pipeline, a system where intelligence is a core architectural component, not just an add-on.
This system ingests articles from multiple sources, including TechCrunch, MIT Technology Review, and Wired. It then passes each one to a Google Gemini model, which analyzes it, scores its relevance to new AI trends, and extracts a summary and keywords. Finally, it filters the results to deliver a curated digest of only the most relevant articles directly to a Slack channel every morning.
More than just a feed reader
This wasn’t about building a better feed reader. It was about building a system that transforms unstructured information into a strategic asset. For a team making real-world decisions, this is what matters.
It's how you ensure that critical developments don’t slip through the cracks, and it helps you avoid making strategic choices with incomplete information. The system creates a continuous stream of intelligence, not just a list of links.
A repeatable AI Native pattern
The architecture for this automated news analyst is a pattern we're seeing more and more: a layered pipeline that moves from data ingestion to aggregation, analysis, curation, and delivery. This is the essence of building AI Native systems, where intelligence is embedded in the workflow.
This same blueprint can be adapted far beyond news.
Where it's all heading
What we built hints at where this is all heading: scalable content ingestion, intelligent content classification, and dynamic content routing. These are core capabilities of an AI Native organization.
The same principles could be applied to:
- Analyze customer feedback from various channels
- Monitor market sentiment
- Process internal documents
This kind of intelligence system is a logical step forward in building systems that can process, understand, and act on the flood of information that shapes modern business. It’s the foundation for a central nervous system for your organization's data.
See how it works
For a full breakdown of the architecture and the n8n workflow, including the code for the AI prompt, you can see how it was built on our blog.