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-4 - tailored specifically for executives and knowledge workers. Perfect for AI copilots, Slack-based assistants, or CEO 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-4 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-4 (RAG) Combines user data and document context to generate a single, actionable next step using a tightly scoped GPT-4 prompt. - Auto-Fixes & Structures Output Ensures formatted response with recommended_action, rationale, and optional risk_note. - Sends Final Output Back to Slack Posts the recommendation directly to the channel as a reply. **Required Integrations** - Slack Bot with channels:history & app_mentions:read - Google Drive OAuth for file fetching - Google Sheets for ID mapping - Pinecone for vector document retrieval - Azure OpenAI or OpenAI GPT-4 for language processing - (Optional) Cohere for reranking results **Ideal Use Cases** - Executive coaching bots (e.g., for CEOs or founders) - Slack-based internal AI assistants - AI-powered document summarization with memory - Actionable recommendations based on real Slack conversations - Enterprise knowledge augmentation from vector DBs **Why This Template Stands Out** 1. Combines live Slack interaction, file ingestion, and Pinecone retrieval into a fully RAG-powered response system. 2. AI prompts are carefully scoped for actionable, context-aware, and time-bound responses. 3. No-code setup with modular components for scaling or adapting to new use cases (e.g., different roles or goals).
- Platform
- n8n
- Category
- AI
- Price
- $14.99
- Creator
- Rahul Joshi
- set
- slack
- stickyNote
- googleDrive
- slackTrigger
- agent
- extractFromFile
- googleSheetsTool
- rerankerCohere
- lmChatAzureOpenAi
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
Related AI workflows
- Launch Your First AI-Powered Chatbot with Actionable Tools$9.99
- Automate AI Video Creation and YouTube Upload with Google Sheets$14.99
- Build a WhatsApp Assistant with Memory, Google Suite, Multi-AI, Research, and Imaging$24.99
- Automate Blog Post Creation and Publishing with GPT, Leonardo AI, and WordPress$14.99
- Email Agent$500.99
- Automate SEO Keyword Generation with ChatGPT from Google Sheets$3.99
More from Rahul Joshi
Need this deployed? We'll set it up for you.
Our automation experts deploy this workflow in your stack, connect your accounts, and verify it works — or build a custom solution from scratch.