๐๐๐ถ๐น๐ ๐ฎ ๐ฅ๐ฒ๐ฎ๐น-๐ง๐ถ๐บ๐ฒ ๐ฉ๐ผ๐ถ๐ฐ๐ฒ ๐๐ ๐ฅ๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต ๐๐ด๐ฒ๐ป๐ ๐๐๐ถ๐ป๐ด ๐ป๐ด๐ป + ๐ข๐ฝ๐ฒ๐ป๐๐ ๐๏ธ๐ง I recently built a real-time voice-enabled AI agent that can research any question you ask and respond back in voice, almost instantly. The goal was to move beyond text-only chatbots and build an AI system that feels natural, conversational, and research-driven. ๐น ๐ช๐ต๐ฎ๐ ๐๐ต๐ถ๐ ๐๐ผ๐ถ๐ฐ๐ฒ ๐๐ ๐ฎ๐ด๐ฒ๐ป๐ ๐ฑ๐ผ๐ฒ๐ ๐๏ธ Accepts real-time voice or text input from the frontend ๐ Sends queries to an n8n Webhook for processing ๐ค Uses an AI Agent to research and understand the question ๐ง Generates a concise, high-quality summary ๐ Converts the response into voice output โก Returns the answer back to the user in real time ๐น ๐ช๐ผ๐ฟ๐ธ๐ณ๐น๐ผ๐ ๐๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ Frontend sends user input โ n8n Webhook OpenAI model processes the research query AI Agent refines the output into a short, clear explanation Response is sent back instantly via webhook Voice layer delivers the final answer audibly ๐น ๐ช๐ต๐ ๐๐ต๐ถ๐ ๐บ๐ฎ๐๐๐ฒ๐ฟ๐ Most AI assistants still rely heavily on text. This workflow shows how: Voice-first AI experiences can be built with automation Research-based answers can be delivered instantly AI agents can feel more human, accessible, and interactive Real-time AI systems donโt need heavy backend infrastructure ๐น ๐ง๐ฒ๐ฐ๐ต ๐ฆ๐๐ฎ๐ฐ๐ธ n8n (Webhooks & Workflow Automation) OpenAI (LLM for research & reasoning) LangChain AI Agent Voice Input & Voice Output Layer This project helped me learn more about: Real-time AI workflows Voice-based AI interactions AI agent prompting & summarization Building practical AI assistants with n8n Still learning. Still building. Sharing the journey ๐ If youโre interested in: โ
Voice AI Agents โ
AI Research Assistants โ
n8n Automation โ
Real-time AI Systems Letโs connect and learn together ๐ Hire Me:
[email protected] watsnumber 03112817660