n8n workflows for Textsplitterrecursivecharactertextsplitter.

Supercharge your trading decisions with this end-to-end AI automation that connects market intelligence, technical analysis, and automated trade execution — all without manual intervention.

Bread-Meat-Delivery. Uses lmChatOpenAi, agent, httpRequest, redis. Webhook trigger; 91 nodes.

Api Schema Extractor. Uses manualTrigger, httpRequest, splitOut, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 88 nodes.

Wait Splitout. Uses manualTrigger, httpRequest, splitOut, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 88 nodes.

This workflow automates the process of discovering and extracting APIs from various services, followed by generating custom schemas. It works in three distinct stages: research, extraction, and schema

My Workflow. Uses outputParserStructured, httpRequest, lmChatGoogleGemini, chainLlm. Scheduled trigger; 82 nodes.

Your AI workforce is ready. Are you?

Agent IA Projet Client. Uses executeWorkflowTrigger, lmChatOpenAi, toolWorkflow, vectorStoreQdrant. Event-driven trigger; 79 nodes.

Hi! I’m Amanda, a creator of intelligent automations using n8n and Make. I’ve been building AI-powered workflows for over 2 years, always focused on usability and innovation. This one here is very spe

• 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).

This intelligent chatbot leverages cutting-edge financial APIs and AI-driven analysis to deliver comprehensive stock research reports. Get instant access to professional-grade investment analysis that

RAG_Ingest. Uses httpRequest, vectorStoreSupabase, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 73 nodes.

⚡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. 🔗

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

This n8n template automatically classifies incoming emails (Sales, Support, Internal, Finance, Promotions) and routes them to a dedicated OpenAI LLM Agent for processing. Depending on the category, th

HeyDinastia. Uses executeCommand, httpRequest, youTube, postgres. Webhook trigger; 66 nodes.

Automate Outreach Prospect automates finding, enriching, and messaging potential partners (like restaurants, malls, and bars) using Apify Google Maps scraping, Perplexity enrichment, OpenAI LLMs, Goog

This simple philosophy changes the way we think about automated sales agents. Context changes everything. In this 4-part workflow, we start by creating a knowledge base that will act as context across

Build a powerful, customizable AI chatbot for your WordPress website that intelligently retrieves posts, answers questions, and engages in natural conversations. This complete solution handles content

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.

I originally started to template to ask questions on the "n8n @ scale office-hours" livestream videos but then extended it to include the latest videos on the official channel.

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

Auto repost job with RAG is a workflow designed to automatically extract, process, and publish job listings from monitored sources using Google Drive, OpenAI, Supabase, and WordPress. This integration

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

RAG AI Agent Template V5. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, googleDrive. Event-driven 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.

Automatically extract job listings from any website URL, format them with AI, and publish directly to WordPress. Just send a URL via Telegram, and watch as the workflow scrapes the job details, enhanc

This n8n workflow turns your Telegram bot into a smart, multi-modal AI assistant that accepts text, documents, images, and audio messages, interprets them using OpenAI models, and responds instantly w

Code Extractfromfile. Uses manualTrigger, sort, httpRequest, compression. 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.

Are you a popular tech startup accelerator (named after a particular higher order function) overwhelmed with 1000s of pitch decks on a daily basis? Wish you could filter through them quickly using AI

This workflow enables companies to provide instant HR support by automating responses to employee queries about policies and benefits: Retrieves company policies, benefits, and HR documents from Bambo

Turn your docs into an AI-powered internal or public-facing assistant. This chatbot workflow uses RAG (Retrieval-Augmented Generation) with Supabase vector search to answer employee or customer questi

Streamline client onboarding and lay the groundwork for future Retrieval-Augmented Generation (RAG) capabilities by automatically transforming Slack messages into structured data using GPT-4o, Google

Reranks #1. Uses googleDrive, vectorStoreSupabase, embeddingsOpenAi, documentDefaultDataLoader. Event-driven trigger; 48 nodes.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

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

AI Multi-Document Analyzer with Smart Recommendations & Reporting

AI Email Agent - Complete System. Uses gmailTrigger, gmail, vectorStorePGVector, embeddingsOpenAi. Event-driven trigger; 47 nodes.

Ditch the endless scroll for AI trends. Meet Archi, your personal AI research assistant that hits you up once a week with everyone you need to know. 🧑🏽‍🔬

This workflow automates the early-stage job application process using AI.

Splitout Code. Uses stickyNote, toolWorkflow, mcpTrigger, executeWorkflowTrigger. Event-driven trigger; 44 nodes.

This n8n implementation exposes other cool API features from Qdrant such as facet search, grouped search and recommendations APIs. With this, we can build an easily customisable and maintainable Qdran

Template name Smart AI Support Assistant for Telegram

Workflow 3636. Uses toolWorkflow, mcpTrigger, executeWorkflowTrigger, httpRequest. Event-driven trigger; 44 nodes.

Dynamic Models. Uses lmChatOpenRouter, agent, gmailTool, airtableTool. Event-driven trigger; 43 nodes.

This n8n workflow enables an AI agent to interact with users through GoHighLevel SMS, leveraging a knowledgebase dynamically built by scraping the company's website.

Survey Insights With Qdrant, Python And Information Extractor. Uses embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, googleSheets. Event-driven trigger; 42 node

Breakdown Documents Into Study Notes Using Templating Mistralai And Qdrant. Uses localFileTrigger, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, embeddingsMistralCloud. Event-

Splitout Code. Uses embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, googleSheets. Event-driven trigger; 42 nodes.

Localfile Wait. Uses localFileTrigger, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, embeddingsMistralCloud. Event-driven trigger; 42 nodes.

Workflow 2339. Uses localFileTrigger, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, embeddingsMistralCloud. Event-driven trigger; 42 nodes.

This n8n workflow takes in a document such as a research paper, marketing or sales deck or company filings, and breaks them down into 3 templates: study guide, briefing doc and timeline.

Imagine having a personal AI secretary accessible right from your Telegram, ready to assist you with information and remember everything you discuss. This n8n workflow transforms Telegram into your in

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights

2339. Uses localFileTrigger, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, embeddingsMistralCloud. Event-driven trigger; 42 nodes.

Agente AI RAG. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, googleDrive. Event-driven trigger; 42 nodes.

V3 Local Agentic RAG AI Agent. Uses documentDefaultDataLoader, memoryPostgresChat, chatTrigger, agent. Webhook trigger; 41 nodes.

Author: Jadai kongolo

This workflow implements a self-healing Retrieval-Augmented Generation (RAG) maintenance system that automatically updates document embeddings, evaluates retrieval quality, detects embedding drift, an

This workflow automates end-to-end e-commerce order processing from intake through fulfillment by orchestrating multiple AI-powered validation stages and external system integrations. Designed for e-c

Homerag. Uses documentDefaultDataLoader, memoryPostgresChat, chatTrigger, agent. Webhook trigger; 41 nodes.

The workflow operates through a three-step process that handles incoming chat messages with intelligent tool orchestration: Message Trigger: The node triggers whenever a user message arrives and passe

This workflow automates academic research processing by routing queries through specialized AI models while maintaining contextual memory. Designed for researchers, faculty, and graduate students, it

Build an All-Source Knowledge Assistant with Claude, RAG, Perplexity, and Drive. Uses chatTrigger, memoryPostgresChat, embeddingsOpenAi, rerankerCohere. Chat trigger; 40 nodes.

Advanced Ai Demo Presented At Ai Developers 14 Meetup. Uses slack, stickyNote, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi. Chat trigger; 39 nodes.

Advanced Ai Demo (Presented At Ai Developers #14 Meetup). Uses slack, stickyNote, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi. Chat trigger; 39 nodes.

Workflow 2358. Uses slack, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi, documentDefaultDataLoader. Chat trigger; 39 nodes.

2358. Uses slack, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi, documentDefaultDataLoader. Chat trigger; 39 nodes.

This workflow was presented at the AI Developers meet up in San Fransico on 24 July, 2024. Categorize incoming Gmail emails and assign custom Gmail labels. This example uses the Text Classifier node,

local_RAG. Uses documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, chatTrigger, memoryBufferWindow. Event-driven trigger; 39 nodes.

RSSフィードから海外のテック記事を収集し、AIで選定・翻訳・要約する. Uses rssFeedRead, n8n-nodes-qdrant, vectorStoreQdrant, documentDefaultDataLoader. Webhook trigger; 39 nodes.

Wait Splitout. Uses manualTrigger, embeddingsMistralCloud, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 38 nodes.

Wait Splitout. Uses manualTrigger, embeddingsMistralCloud, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 38 nodes.

Every company has documents sitting in Google Drive that nobody reads. HR policies, sales playbooks, product FAQs, financial guidelines — all written once, never found again. This workflow turns all o

This n8n workflows builds another example of creating a knowledgebase assistant but demonstrates how a more deliberate and targeted approach to ingesting the data can produce much better results for y

📝 Description This workflow helps automatically classify incoming emails using a combination of conditional logic and minimal AI-based classification. The system checks email content, performs sentime

Every day at 8 AM, the workflow automatically retrieves the latest F1 data—including driver standings, qualifying results, race schedules, and circuit information. All sources are merged into a unifie

This n8n workflow builds a self-improving AI agent for handling email responses. It integrates Gmail for incoming messages, uses an AI agent with a Supabase vector store for knowledge retrieval, draft

Customer Insights With Qdrant, Python And Information Extractor. Uses manualTrigger, html, splitOut, documentDefaultDataLoader. Event-driven trigger; 37 nodes.

Splitout Code Export. Uses manualTrigger, html, splitOut, documentDefaultDataLoader. Event-driven trigger; 37 nodes.

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights

My workflow 3. Uses formTrigger, splitInBatches, lmChatGoogleGemini, httpRequest. Event-driven trigger; 36 nodes.

Splitout Schedule. Uses scheduleTrigger, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Scheduled trigger; 36 nodes.

Splitout Code. Uses manualTrigger, hackerNews, splitOut, vectorStoreQdrant. Event-driven trigger; 36 nodes.

Indexation. Uses formTrigger, embeddingsOllama, textSplitterRecursiveCharacterTextSplitter, modelSelector. Event-driven trigger; 36 nodes.

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights

This can be one way to help reduce the amount of manual work in managing the issue backlog for busy teams with little effort. This template contains 2 separate flows which run continuously via schedul

Scheduled triggers initiate automated contract reviews. The system fetches documents from cloud storage and email, then uses AI to extract key terms, obligations, and compliance requirements. Multi-mo

2374. Uses hackerNews, vectorStoreQdrant, embeddingsOpenAi, documentDefaultDataLoader. Event-driven trigger; 36 nodes.

Agente de Agendamento YT (V.2). Uses googleSheets, n8n-nodes-evolution-api, openAi, redis. Webhook trigger; 36 nodes.

This workflow ingests educational PDF URLs from Google Sheets, extracts and chunks their text, generates embeddings with Google Gemini, and stores them in a Supabase pgvector table for retrieval, whil

Personal Portfolio Resume CV Chatbot. Uses embeddingsGoogleGemini, stickyNote, scheduleTrigger, lmChatGoogleGemini. Scheduled trigger; 35 nodes.

4827. Uses agent, lmChatOpenAi, embeddingsOpenAi, memoryBufferWindow. Event-driven trigger; 35 nodes.

This template is designed for internal support teams, product specialists, and knowledge managers in technology companies who want to automate ingestion of product documentation and enable AI-driven,

This n8n workflow implements a fully automated Retrieval-Augmented Generation (RAG) pipeline powered by Google Drive, OpenAI embeddings, and Pinecone.

This template is perfect for:

This n8n workflow automates the process of ingesting documents from multiple sources (Google Drive and web forms) into a Qdrant vector database for semantic search capabilities. It handles batch proce

Whatsapp. Uses agent, lmChatOpenAi, embeddingsOpenAi, memoryBufferWindow. Event-driven trigger; 35 nodes.

Bitrix24 Open Chanel RAG Chatbot Application Workflow example with Webhook Integration. Uses httpRequest, noOp, respondToWebhook, documentDefaultDataLoader. Webhook trigger; 34 nodes.

This workflow implements a complete Voice AI Chatbot system for Wordress that integrates speech recognition, guardrails for safety, retrieval-augmented generation (RAG), Qdrant vector search, and audi

Transform your Bitrix24 Open Line channels with an intelligent chatbot that leverages Retrieval-Augmented Generation (RAG) technology to provide accurate, document-based responses to customer inquirie

This workflow is built for individuals, teams, and businesses that receive regular inquiries via email and want to automate responses in a way that’s intelligent, brand-aligned, and always up to date.

Ai Agent To Chat With Files In Supabase Storage. Uses httpRequest, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, extractFromFile. Event-driven trigger; 33 nodes.

Wait Code Export. Uses manualTrigger, httpRequest, html, embeddingsMistralCloud. Event-driven trigger; 33 nodes.

Ai Agent To Chat With Files In Supabase Storage. Uses httpRequest, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, extractFromFile. Event-driven trigger; 33 nodes.

supabase. Uses httpRequest, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi. Event-driven trigger; 33 nodes.

This workflow implements a complete Retrieval-Augmented Generation (RAG) system for document ingestion and intelligent querying.

Need to turn a one-line chat request into a fully-wired n8n workflow template—complete with AI agents, RAG, and web-search super-powers—without lifting a finger? That’s exactly what Agent Builder auto

I prepared a detailed guide explaining how to set up and implement this scenario, enabling you to chat with your documents stored in Supabase using n8n.

This n8n workflow demonstrates creating a recipe recommendation chatbot using the Qdrant vector store recommendation API.

This workflow implements a Retrieval-Augmented Generation (RAG) system that integrates Google Drive and Qdrant.

Build a fully functional AI chatbot for any website using Retrieval-Augmented Generation (RAG). This workflow automatically crawls and indexes your entire site into a Qdrant vector database, then powe

n8n telegram RAG. Uses lmChatGoogleGemini, embeddingsGoogleGemini, memoryManager, vectorStoreSupabase. Event-driven trigger; 32 nodes.

An AI-powered sales agent on WhatsApp that handles product inquiries using your Supabase knowledge base and n8n catalog. Customers can send text, voice notes, or images to ask about products, pricing,

An extendable RAG template to build powerful, explainable AI assistants — with query understanding, semantic metadata, and support for free-tier tools like Gemini, Gemma and Supabase.

This workflow allows you to generate riddle-themed vertical videos (9:16), render them using Creatomate, and upload them directly to YouTube — all automatically. It's optimized for low-cost operation

Ideal for businesses that receive frequent inquiries about products or services and want to automate responses, freeing up time to focus on core operations. Polls your inbox for new incoming emails Cl

This n8n template lets you automatically build and maintain an AI-ready knowledge base from Outlook emails and Notion pages. It stores both sources in a Pinecone vector database so your AI agent can r

Transform your customer support with this intelligent Gmail-based automation system that combines AI analysis, vector knowledge bases, and smart escalation workflows. This comprehensive solution autom

This n8n workflow is designed for content creators, bloggers, digital marketers, and social media managers who want to fully automate their content distribution pipeline. The workflow creates an end-t

Based on the workflow image, here is the complete n8n template submission:

This template gives your HR or operations team an AI-powered Slack bot that answers employee questions about internal policies — directly in DM, available to everyone in the workspace, with no per-use

ejemplo RAG vs CRAG. Uses googleDrive, vectorStoreQdrant, embeddingsOllama, agent. Event-driven trigger; 30 nodes.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

Overview

This workflow is designed for support teams, data engineers, and AI developers who want to centralize Jira issue data into a vector database. It collects open issues and their associated comments, con

Requirement-to-Task-V5. Uses lmChatOpenAi, memoryBufferWindow, textClassifier, agent. Event-driven trigger; 30 nodes.

Build A Financial Documents Assistant Using Qdrant And Mistral.Ai. Uses localFileTrigger, manualTrigger, stickyNote, readWriteFile. Event-driven trigger; 29 nodes.

Localfile. Uses localFileTrigger, manualTrigger, stickyNote, readWriteFile. Event-driven trigger; 29 nodes.

Order and Delivery Support. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Event-driven trigger; 29 nodes.

This workflow implements a complete Retrieval-Augmented Generation (RAG) knowledge assistant with built-in document ingestion, conversational AI, and automated analytics using n8n, OpenAI, and Pinecon

This workflow automates the creation and management of a Retrieval-Augmented Generation (RAG) system using Qdrant as a vector store and Google Drive as the document source. It enables full or incremen

This n8n workflow demonstrates how to manage your Qdrant vector store when there is a need to keep it in sync with local files. It covers creating, updating and deleting vector store records ensuring

This workflow implements a Retrieval-Augmented Generation (RAG) system that:

This powerful AI automation add-on upgrades your Telegram Bot Starter Template by integrating a fully functional AI chatbot and a context-aware AI agent that answers user questions using your internal

Empower your workflows with an intelligent AI chat assistant that retrieves real-time context from Google Sheets and a Pinecone knowledge base using Retrieval-Augmented Generation (RAG). 🤖📂 This workf

Deploy a personal AI assistant that answers recruiter questions about your skills and projects, then automatically emails your CV as a PDF attachment when requested. Upload your portfolio documents (r

Building Your First Whatsapp Chatbot. Uses whatsAppTrigger, lmChatOpenAi, memoryBufferWindow, toolVectorStore. Event-driven trigger; 28 nodes.

AI Document Assistant via Telegram + Supabase. Uses lmChatGoogleGemini, openWeatherMapTool, agent, telegramTrigger. Event-driven trigger; 28 nodes.

This n8n template builds a simple WhatsApp chabot acting as a Sales Agent. The Agent is backed by a product catalog vector store to better answer user's questions.

This template creates a Telegram AI Assistant that answers questions based on your documents, powered by Google Gemini and Supabase. Key features include Intelligent HTML Post-processing for rich form

The IngestionDocs workflow is a fully automated **document ingestion and knowledge management system built with n8n**. Its purpose is to continuously ingest organizational documents from Google Drive,

This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

Automates the process of generating, storing, and publishing engaging LinkedIn posts derived from books (PDFs) using AI and vector search.

HR & IT Helpdesk Chatbot with Audio Transcription. Uses stickyNote, manualTrigger, httpRequest, extractFromFile. Event-driven trigger; 27 nodes.

Parents smart bot. Uses telegramTrigger, agent, toolWorkflow, toolHttpRequest. Event-driven trigger; 27 nodes.

HR & IT Helpdesk Chatbot with Audio Transcription. Uses stickyNote, manualTrigger, httpRequest, extractFromFile. Event-driven trigger; 27 nodes.

Supabase RAG AI Agent Custom Auth. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Event-driven trigger; 27 nodes.

An intelligent chatbot that assists employees by answering common HR or IT questions, supporting both text and audio messages. This unique feature ensures employees can conveniently ask questions via

This workflow turns your WhatsApp number into an intelligent AI-powered Sales Agent that answers product queries using real data extracted from a PDF brochure. It loads a product brochure via HTTP Req

What it is: An n8n workflow that enables AI-first WhatsApp support with seamless human handoff. Why it’s unique: The AI agent answers queries using RAG (Supabase vector store + Gemini). If a human int

How it works A manual trigger sets the research topic and generates three parallel Tavily web search queries A Summarizer Agent (Groq Llama 3.3 70B) and an Analyst Agent (OpenRouter GPT) process the s

AI-Business-Agent. Uses vectorStoreSupabase, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Scheduled trigger; 27 nodes.

n8n-4-1: Qdrant. Uses vectorStoreQdrant, embeddingsOpenAi, textClassifier, chainSummarization. Event-driven trigger; 27 nodes.

20-building-your-first-whatsapp-chatbot. Uses whatsAppTrigger, lmChatOpenAi, memoryBufferWindow, toolVectorStore. Event-driven trigger; 27 nodes.

This template is designed for internal support teams, product specialists, and knowledge managers who want to build an AI-powered knowledge assistant with retrieval-augmented generation (RAG) and rein

This comprehensive n8n workflow template creates an intelligent AI chatbot that automatically transforms your Google Drive documents into a searchable knowledge base. The chatbot uses OpenAI's GPT mod

This is a template for n8n's evaluation feature.

Community nodes can only be installed on self-hosted instances of n8n.

Unlock unparalleled efficiency and elevate customer satisfaction with our AI-Powered Customer Support: Email, Knowledge Base & Human Escalation Automation template. This sophisticated n8n workflow is

Insert and retrieve documents. Uses manualTrigger, httpRequest, html, splitOut. Event-driven trigger; 25 nodes.

Agente de Procesamiento de Documentos. Uses httpRequest, vectorStoreSupabase, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Scheduled trigger; 25 nodes.

AI chatbots are only as good as the data they learn from. Most large language models (LLM) rely only on their training datasets.

This workflow automates the process of creating a document-based AI retrieval system using Milvus, an open-source vector database. It consists of two main steps: Data collection/processing Retrieval/r

Transform your AI assistants into intelligent agents with persistent memory capabilities. This production-ready workflow implements a sophisticated long-term memory system using vector databases, enab

The scoring approach is adapted from https://cloud.google.com/vertex-ai/generative-ai/docs/models/metrics-templates#pointwise_groundedness This evaluation works best for an agent that requires documen

Turn WhatsApp chats into instant answers and real-time bookings—all in one n8n workflow. Your AI Agent leverages Gemini embeddings + Pinecone for on-the-fly knowledge retrieval, then logs reservations

It uses Retrieval-Augmented Generation (RAG) to allow users to upload documents, which are then indexed into a vector database, enabling the bot to answer questions based only on the provided content.

RAG + CHAT IA. Uses vectorStorePinecone, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, agent. Event-driven trigger; 25 nodes.

Indexation. Uses formTrigger, embeddingsOllama, textSplitterRecursiveCharacterTextSplitter, modelSelector. Event-driven trigger; 25 nodes.

Personalized AI Tech Newsletter Using RSS, OpenAI and Gmail. Uses splitOut, embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Scheduled trigger; 24 nodes.

Local RAG AI Agent. Uses memoryPostgresChat, lmChatOllama, lmOllama, toolVectorStore. Event-driven trigger; 24 nodes.

Supabase RAG AI Agent. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Event-driven trigger; 24 nodes.

Supabase RAG AI Agent. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Event-driven trigger; 24 nodes.

Contextual Retrieval. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, googleDrive. Event-driven trigger; 24 nodes.

V1 ocal RAG AI Agent. Uses memoryPostgresChat, lmChatOllama, lmOllama, toolVectorStore. Event-driven trigger; 24 nodes.

This n8n template automates the collection, storage, and summarization of technology news from top sites, turning it into a concise, personalized weekly newsletter.

This workflow provides comprehensive AI-driven stock analysis, generating detailed deep reports by leveraging advanced vector-based data retrieval and API integrations for precise financial analytics

**Type of data is binary

This workflow deploys a fully customizable AI chatbot that can be embedded on any website, from custom-coded sites to platforms like WordPress. The chatbot is powered by n8n, uses Supabase for memory

V1 Local RAG AI Agent. Uses memoryPostgresChat, lmChatOllama, lmOllama, toolVectorStore. Event-driven trigger; 24 nodes.

V1 Local RAG AI Agent. Uses memoryPostgresChat, lmChatOllama, lmOllama, toolVectorStore. Event-driven trigger; 24 nodes.

Agent: Local AI RAG: Ollama & Qdrant. Uses memoryPostgresChat, lmChatOllama, lmOllama, toolVectorStore. Event-driven trigger; 24 nodes.

personalized-ai-tech-newsletter-using-rss,-openai-and-gmail. Uses embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, lmChatOpenAi. Scheduled trigger; 24 nodes.

16-personalized-ai-tech-newsletter-using-rss,-openai-and-gmail. Uses embeddingsOpenAi, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, lmChatOpenAi. Scheduled trigger; 24 nodes.

V2 Supabase RAG AI Agent. Uses memoryPostgresChat, lmChatOllama, lmOllama, toolVectorStore. Chat trigger; 23 nodes.

Your LLM is answering the same questions over and over. "What's the weather?" "How's the weather today?" "Tell me about the weather." Same answer, three API calls, triple the cost. This workflow fixes

This template is designed for podcasters, researchers, educators, product teams, and support teams who work with audio content and want to turn it into searchable knowledge. It is especially useful fo

This n8n workflow automates email support using AI and vector database technology to provide smart, context-aware responses. It seamlessly integrates email automation and document management, ensuring

An on-premises, domain-specific AI assistant for Kaggle (tested on binary disaster-tweet classification), combining LLM, an n8n workflow engine, and Qdrant-backed Retrieval-Augmented Generation (RAG).

Enable smart, real-time answers in your WhatsApp groups using a custom webhook, Pinecone vector database, and no Facebook Business setup.

This n8n workflow automates the process of summarizing uploaded books from Google Drive using vector databases and LLMs. It uses Cohere for embeddings, Qdrant for storage and retrieval, and DeepSeek o