Generate contextual recommendations from Slack using Pinecone

This advanced Retrieval-Augmented Generation (RAG) automation template for n8n enables contextual, real-time recommendations using Slack messages as input. The workflow extracts referenced documents from Google Drive, performs semantic retrieval from Pinecone, and generates next-step advice using GPT-4o — tailored specifically for executives and knowledge workers.

Perfect for AI copilots, Slack-based assistants, or CTO coaching tools, this no-code RAG implementation gives you the building blocks to combine unstructured inputs with memory-augmented intelligence.

What This Template Does

✅ Triggers from a Slack Message or Mention Monitors a Slack channel using a bot, capturing user input in real-time. 🔍 Extracts Key Info from Message GPT-4o parses the message to identify the subject person and Google Drive link (if present). 📥 Downloads File from Google Drive Automatically fetches and extracts PDF content using the built-in extractor. 📇 Retrieves Metadata from Google Sheets & Pinecone

Looks up user ID from Google Sheets and retrieves context from Pinecone based on embeddings and reranking.

🧠 Contextual Response via GPT-4o (RAG) Combines user data and document context to generate a single, actionable next step using a tightly scoped GPT-4o prompt.

🛠️ Auto-Fixes & Structures Output Ensures formatted response with recommendedaction, rationale, and optional risknote.

📨 Sends Final Output Back to Slack Posts the recommendation directly to the channel as a reply.