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I built an n8n automation that processes incoming webhook requests and routes them based on predefined rules. The system uses a switch node to direct requests into different workflows such as IP lookup, domain analysis, hash checks, and CVE data processing. Each branch handles a specific function and returns structured responses via webhooks. This automation enables real-time data processing, improves efficiency, and ensures accurate routing for different cybersecurity related queries.
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From sidewalk to doorstep.
A closer look at ROVR, a landing page concept for an autonomous delivery robot.
A robot at your door is new for most people, so every section answers a question a first time customer would ask: how it gets here, what it can carry, what it costs and what happens if it gets stuck.
Our favorite part is the FAQ, rebuilt as a chat where you can ask ROVR anything.
What would you want to know before a robot delivers your groceries?
Love the idea of turning the FAQ into a conversation. My first question would be: what happens when the robot encounters something unexpected mid-delivery? Showing how ROVR handles those moments could build more trust than any feature list.
Built an AI-powered lead qualification automation using n8n. The system receives incoming leads, validates their information, analyzes customer needs, assigns a lead score from 0 to 100, creates or updates CRM contacts, and sends Telegram notifications. It also handles duplicate contacts and processing errors.
This is a solid, practical build. The flow makes sense: validate → analyze → score → CRM → notify. What I like most is the duplicate handling and error processing — those are usually the first things people skip, and they're exactly what makes a lead system actually usable day...