Documentdefaultdataloader → Memory Buffer Window

A lightweight, self-hosted AI assistant built entirely in n8n. Multi-channel messaging (Telegram, WhatsApp, Gmail), persistent memory, task management, and autonomous work — all in a single visual wor

This workflow acts as a 24/7 sales agent, engaging leads across WhatsApp, Instagram, Facebook, Telegram, and your website. It intelligently transcribes audio messages, answers questions using a knowle

This comprehensive workflow bundle is designed as a powerful starter kit, enabling you to build a multi-functional AI assistant on Telegram. It seamlessly integrates AI-powered voice interactions, an

• Create a Google Drive folder to watch. • Connect your Google Drive account in n8n and authorize access. • Point the Google Drive Trigger node to this folder (new/modified files trigger the flow).

⚡AI-Powered YouTube Playlist & Video Summarization and Analysis v2. Uses lmChatGoogleGemini, agent, splitOut, chainLlm. Chat trigger; 72 nodes.

This n8n workflow transforms entire YouTube playlists or single videos into interactive knowledge bases you can chat with. Ask questions and get summaries without needing to watch hours of content. 🔗

The "WhatsApp Productivity Assistant with Memory and AI Imaging" is a comprehensive n8n workflow that transforms your WhatsApp into a powerful, multi-talented AI assistant. It's designed to handle a w

This workflow automates patient communication for medical clinics using the WhatsApp Business API. It supports appointment booking, rescheduling, service inquiries, follow-ups, and document submission

Chat with docs - 5minAI New version. Uses httpRequest, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi. Event-driven trigger; 62 nodes.

I prepared a detailed guide that illustrates the entire process of building an AI agent using Supabase and Google Drive within N8N workflows.

This workflow automates customer support across multiple channels (Email, Live Chat, WhatsApp, Slack, Discord) using AI-powered responses enhanced with Retrieval Augmented Generation (RAG) and your pr

YouTube Agent. Uses supabase, agent, lmChatAnthropic, outputParserStructured. Webhook trigger; 56 nodes.

This template is a complete, hands-on tutorial for building a RAG (Retrieval-Augmented Generation) pipeline. In simple terms, you'll teach an AI to become an expert on a specific topic—in this case, t

Tech Radar. Uses googleDrive, documentDefaultDataLoader, stickyNote, mySql. Scheduled trigger; 53 nodes.

This project is built on top of the famous open source ThoughtWorks Tech Radar.

OIL Rag. Uses lmChatOpenAi, embeddingsOpenAi, agent, telegramTrigger. Event-driven trigger; 53 nodes.

/billing - For payment and invoice questions /tech-support - For technical assistance /return-policy - For returns and refunds Command-based routing Direct department access via slash commands Tracks

Code Extractfromfile. Uses manualTrigger, sort, httpRequest, compression. Event-driven trigger; 50 nodes.

🤖 AI Powered RAG Chatbot for Your Docs + Google Drive + Gemini + Qdrant. Uses documentDefaultDataLoader, textSplitterTokenSplitter, vectorStoreQdrant, splitInBatches. Event-driven trigger; 50 nodes.

BambooHR AI-Powered Company Policies and Benefits Chatbot. Uses manualTrigger, documentDefaultDataLoader, embeddingsOpenAi, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 50 nodes.

BambooHR AI-Powered Company Policies and Benefits Chatbot. Uses manualTrigger, documentDefaultDataLoader, embeddingsOpenAi, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 50 nodes.

2464. Uses httpRequest, compression, editImage, documentDefaultDataLoader. Event-driven trigger; 50 nodes.

Workflow 2464. Uses httpRequest, compression, editImage, documentDefaultDataLoader. Event-driven trigger; 50 nodes.

This workflow creates a powerful RAG (Retrieval-Augmented Generation) chatbot that can process, store, and interact with documents from Google Drive using Qdrant vector storage and Google's Gemini AI.