Ask questions about past meetings using voice with OpenAI and Pinecone

Description This workflow allows users to ask questions about past meetings using their voice. It converts the voice question into text, searches stored meeting notes using Pinecone, and replies with a spoken answer generated by AI. It helps teams quickly recall decisions, tasks, and discussions without reading long meeting notes. 🧠🔊 🔁 What This Template Does 1️⃣ Receives a voice question through a webhook endpoint. 🌐 2️⃣ Converts the audio question into text using speech transcription. 🎤➡️📝 3️⃣ Cleans and prepares the question for searching. ✅ 4️⃣ Converts the question into an embedding for semantic search. 🔍 5️⃣ Searches relevant meeting notes from Pinecone using the team namespace. 📚 6️⃣ Combines retrieved meeting context into a single readable format. 🧩 7️⃣ Uses AI to answer the question strictly from the meeting context. 🤖 8️⃣ Converts the AI’s text answer into spoken audio. 🔊 9️⃣ Sends the audio response back to the user via webhook. 🔁 ⭐ Key Benefits ✅ Allows hands-free access to meeting information ✅ Saves time searching through meeting notes ✅ Prevents AI hallucinations using RAG ✅ Supports multiple teams using namespaces ✅ Works with voice-based tools and assistants ✅ Improves meeting recall and clarity 🧩 Features - Voice-based question input - Speech-to-text transcription - Semantic search using Pinecone - Team-based data isolation - Context-aware AI responses - Text-to-speech output - Webhook-driven architecture 🔐 Requirements - OpenAI API key for transcription, embeddings, and speech generation - Azure OpenAI credentials for chat responses - Pinecone API key with a configured index - Matching embedding model for ingest and query - Webhook client capable of sending audio files 🎯 Target Audience - Teams that conduct frequent meetings - Managers needing quick decision recall - Remote and distributed teams - Product, engineering, and operations teams - Automation builders using n8n - Organizations adopting voice-based workflows