A workflow gathers fresh items from sources like RSS feeds, Google Search results, or saved lists, then filters what matters using keywords, domains, and simple rules. Next, an AI step summarizes each story, pulls out key points, and adds tags like “competitor,” “regulation,” or “trend.” Finally, it delivers a digest to Slack or email and logs everything in Google Sheets so you can search later. You can run it on a schedule or trigger it from a webhook.

Not really. Most Flowpast workflows are plug-and-play: connect your accounts, add your topics, and turn them on.

If you or your team spends about 2 hours a day skimming sources, automation can cut this in half by removing the busywork: collecting links, deduping, and turning long articles into quick summaries. The bigger win is consistency. You stop missing updates on busy days, and you avoid multiple people researching the same story. Many teams also reuse summaries for internal updates, client reporting, and content briefs, which saves another chunk of time each week.

You need an n8n workspace, at least one source (RSS feed URLs work great), and a destination like Slack or Google Sheets. For AI summaries, you’ll add an API key for OpenAI (or another model provider if the workflow supports it). Start with a small topic list, then expand once the noise level feels right. Frankly, the best setup is one daily digest plus a “breaking news” alert for high-priority keywords.