Ask questions about past meetings using voice with OpenAI and Pinecone

Description

📊 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