AI 资讯
Zenith: the real sky above you, right now
This is a submission for Weekend Challenge: Passion Edition What I Built The theme was passion, and mine has always been the sky and everything beyond it. Day or night, there's a specific kind of awe in remembering that the sky isn't a backdrop. It's real, it's happening right now, and every point of light is an actual place. Night is simply when you can see the most of it. I wanted to put that feeling into a browser tab. Zenith takes your location, cinematically lowers you from orbit down onto your exact spot on Earth, and becomes a first-person view of your real sky, one you can drag to look around. Every star is where it actually is. The Sun, the Moon, and the visible planets are computed for your latitude, longitude, and this exact minute, and placed where they truly are. It isn't a fixed picture either: the whole sky rotates slowly in real time, so stars rise and set while you watch. Tap any object and you travel to it. The camera flies out through the real starfield, the object grows from a point into a detailed close-up, and a short, grounded briefing appears telling you what you're actually looking at, from where you're standing, right now. A warm voice reads it to you. Stay a while and Zenith reminds you that there are people over your head: it shows how many humans are in space this moment, by name, and draws the real International Space Station crossing your sky whenever it's above your horizon. Not information about space. The quiet, enormous wonder of looking up and knowing, for a moment, exactly what you're looking at. Demo Live: https://zenith-rgerjeki.vercel.app A short walkthrough: the descent to your location, dragging the real sky, and flying to a planet for an AI briefing read aloud in a warm voice. Code rgerjeki / Zenith Zenith The sky above you, right now. I've always been drawn to the sky, and everything beyond it. Zenith is a first-person view of yours : it takes your location, lowers you onto your exact spot on Earth, and gives you the real
AI 资讯
Building a Low-Latency Voice AI Sales Agent with ElevenLabs and n8n (End-to-End Blueprint)
In the hyper-competitive landscape of modern B2B outbound sales, speed-to-lead and outreach capacity are the ultimate drivers of pipeline volume . Yet, traditional Sales Development Representative (SDR) teams face a exhausting bottleneck: reaches and qualifications are limited by human bandwidth . A typical outbound SDR spends up to 80% of their day dialing numbers, navigating IVR phone trees, hitting voicemail, and dealing with incorrect contact records. When an inbound lead submits a form requesting a product demo, the average company takes 42 minutes to respond. By that time, prospect engagement has cooled by over 400%. To shatter this operational limit, modern revenue operations (RevOps) teams are transitioning from rigid auto-dialers and static voice bots to autonomous voice AI sales agents . By pairing the hyper-realistic conversational engine of ElevenLabs with the visual orchestration power of n8n , you can deploy a scalable, context-aware calling agent that handles inbound qualification and outbound follow-up calls in real-time. This technical blueprint provides an end-to-end guide to designing, securing, and deploying a production-grade Voice AI Sales Agent using ElevenLabs Conversational AI and n8n . We will cover how to manage conversation state, execute live database tool calls, secure webhook communication, route calls dynamically, and configure infrastructure to achieve sub-second response latency . The Architecture of an Enterprise Voice Agent Building a conversational voice agent requires a multi-layered system that operates in near real-time. When a human speaks over a telephony network, their voice must be digitized, transcribed, processed by a large language model (LLM), synthesized back into audio, and sent back down the line—all within a fraction of a second. To ensure stability, scalability, and absolute separation of concerns, our architecture decouples the telephony and voice generation layer from the logic and database integration layer . [