Field intelligence for AI-first professionalsVol. II · Nº 56 · Saturday, August 15, 2026
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763 workflows, ready to run.

Community-built n8n automations, searchable live from the template library. Open one on n8n.io and import the JSON straight into your instance.

AI Customer Support Chat for Web Hosting with Google Gemini & WHMCSThis n8n template implements a Customer Support Chat Agent for Web Hosting Companies with Google Gemini, Google Sheets Knowledge base and WHMCS API to Check Domain Name AvailabilitAI Agent · Simple Memory · Google Gemini Chat Model0 views
Search Outlook Emails with Natural Language Queries using GPT-4oThis workflow allows you to search your Outlook mailbox with natural language. You type what you’re looking for (e.g., “invoice from last week”), and the workflow: Uses OpenAI toMicrosoft Outlook · AI Agent · OpenAI Chat Model · Simple Memory · Structured Output Parser0 views
Create a Company Policy Chatbot with RAG, Pinecone Vector Database, and OpenAIA RAG Chatbot with n8n and Pinecone Vector Database Retrieval-Augmented Generation (RAG) allows Large Language Models (LLMs) to provide context-aware answers by retrieving inforGoogle Drive · AI Agent · Embeddings OpenAI · OpenAI Chat Model · Simple Memory0 views
Customer Support Chatbot with RAG using OpenAI and Pinecone🤖 Simple RAG Customer Support Chatbot 📋 Overview This intelligent customer support chatbot leverages Retrieval-Augmented Generation (RAG) to provide accurate, contextual responGoogle Drive · AI Agent · Embeddings OpenAI · OpenAI Chat Model · Simple Memory0 views
AI Voice & Text Note-Taking with LINE Messaging, Supabase Vector DB & GmailOverview This workflow lets you capture, store, and retrieve notes from LINE chats — both text and voice messages — and automatically send them to your Gmail inbox. By leveraging HTTP Request · Code · AI Agent · Embeddings OpenAI · OpenAI Chat Model0 views
Auto-respond to Slack Messages with GPT and Pinecone Vector RAG Context🛠 GPT-5 + Pinecone-Powered Slack Auto-Responder — Real-Time, Context-Aware Replies for IT & Engineering Teams Description Cut down on context-switching and keep your Slack threadSlack · AI Agent · Embeddings OpenAI · OpenAI Chat Model · Simple Memory0 views
Generate Business Requirement Documents with Multi-agent GPT & Google WorkspaceMulti-agent RAG system for smarter BRD (Business Requirement Document) writing Who’s it for This workflow is designed for Business Analysts, Project Managers, and Operations TeamsGoogle Sheets · HTTP Request · Google Drive · SendGrid · Code0 views
Optimize Unstructured Data for RAG with Blockify IdeaBlocks TechnologyThis workflow contains community nodes that are only compatible with the self-hosted version of n8n. Blockify® Data Optimization Workflow Blockify Optimizes Data for RAG - GivingHTTP Request · Google Drive · Code · AI Agent · Embeddings OpenAI0 views
Client FAQ Bot with RAG using Google Drive PDFs & Azure GPT-4o-miniDescription: Build your own AI-powered Client FAQ system with Retrieval-Augmented Generation (RAG) — fully automated using n8n, Google Drive, and Azure OpenAI (GPT-4o-mini). This Google Drive · Basic LLM Chain · Azure OpenAI Chat Model0 views
Answer Questions from Documents with RAG using Supabase, OpenAI & Cohere RerankerThis workflow contains community nodes that are only compatible with the self-hosted version of n8n. This comprehensive RAG workflow enables your AI agents to answer user questionGoogle Drive · Code · AI Agent · Embeddings OpenAI · Supabase Vector Store0 views
Build a Retrieval-Based Chatbot with Telegram, OpenAI and Google Drive PDF Backup📚 Telegram RAG Chatbot with PDF Document & Google Drive Backup An upgraded Retrieval-Augmented Generation (RAG) chatbot built in n8n that lets users ask questions via Telegram andTelegram · Google Drive · Code · AI Agent · Embeddings OpenAI0 views
Build Comprehensive Entity Profiles with GPT-4, Wikipedia & Vector DB for ContentThis n8n template demonstrates how to build an intelligent entity research system that automatically discovers, researches, and creates comprehensive profiles for business entitiesAI Agent · Basic LLM Chain · OpenAI Chat Model · Structured Output Parser · Character Text Splitter0 views
Vision RAG and Image Embeddings using Cohere Command-A and Embed v4Cohere's new multimodal model releases make building your own Vision RAG agents a breeze. If you're new to Multimodal RAG and for the intent of this template, it means to embed andHTTP Request · AI Agent · Embeddings Cohere · Simple Memory · Code Tool0 views
Chat with Internal Documents using Ollama, Supabase Vector DB & Google Drive📚 Chat with Internal Documents (RAG AI Agent) ✅ Features Answers should given only within provided text. Chat interface powered by LLM (Ollama) Retrieval-Augmented Generation (RAGGoogle Drive · Supabase · AI Agent · Ollama Chat Model · Ollama Model0 views
Enhance AI Chatbot Responses with InfraNodus Knowledge Graph ReasoningAugment AI chatbot prompts with a knowledge graph reasoning ontology and improve the quality of responses with Graph RAG. In this workflow, we augment the original prompt using thHTTP Request305 views
Build Persistent Chat Memory with GPT-4o-mini and Qdrant Vector Database🧠 Long-Term Memory System for AI Agents with Vector Database Transform your AI assistants into intelligent agents with persistent memory capabilities. This production-ready workfAI Agent · Embeddings OpenAI · OpenAI Chat Model · Structured Output Parser · Recursive Character Text Splitter0 views
Automate SEO Tasks with Google Search Console & AI via MCP Server🚀 Google Search Console MCP Server 📋 Description This n8n workflow serves as a Model Context Protocol (MCP) server, connecting MCP-compatible AI tools (like Claude) directly to0 views
AI-Powered Stock Analysis with AI Scoring and Gmail Report DeliveryWorkflow Description and Setup Guide This workflow provides comprehensive AI-driven stock analysis, generating detailed deep reports by leveraging advanced vector-based data retriGmail · AI Agent · Embeddings OpenAI · Recursive Character Text Splitter · Supabase Vector Store0 views