n8n workflows for Supabase Vector Store.

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.

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

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

Your AI workforce is ready. Are you?

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.

Search Worflow Docker Complete. Uses documentDefaultDataLoader, textSplitterCharacterTextSplitter, vectorStoreSupabase, embeddingsOllama. Scheduled trigger; 71 nodes.

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

Who is this for? This workflow is ideal for HR teams, startups, and enterprises that want to handle employee interactions through WhatsApp and automate responses using LLM (OpenAI) and intelligent rou

crawl4 ai. Uses documentDefaultDataLoader, textSplitterCharacterTextSplitter, vectorStoreSupabase, embeddingsOllama. Scheduled trigger; 65 nodes.

Search Worflow Docker. Uses documentDefaultDataLoader, textSplitterCharacterTextSplitter, vectorStoreSupabase, embeddingsOllama. Scheduled trigger; 65 nodes.

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

This workflow automates multi-channel AI-driven sales engagement for lead qualification, service information delivery, and consultation booking. It integrates WhatsApp, Facebook Messenger, Instagram D

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.

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

Unleash the full potential of your HighLevel CRM by adding an intelligent GPT-5 Agent that does more than just follow commands — it understands context, retrieves the right data, and executes actions

My workflow 2529. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, googleDrive. Event-driven trigger; 54 nodes.

05. Base_To_Copy. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, googleDrive. Event-driven trigger; 54 nodes.

Wordpress Ai Chatbot To Enhance User Experience With Supabase And Openai. Uses manualTrigger, embeddingsOpenAi, documentDefaultDataLoader, textSplitterTokenSplitter. Event-driven trigger; 53 nodes.

RAG & GenAI App With WordPress Content. Uses manualTrigger, embeddingsOpenAi, documentDefaultDataLoader, textSplitterTokenSplitter. Event-driven trigger; 53 nodes.

RAG & GenAI App With WordPress Content. Uses manualTrigger, embeddingsOpenAi, documentDefaultDataLoader, textSplitterTokenSplitter. Event-driven trigger; 53 nodes.

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

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

Agente_Atendimento_E_commerce. Uses baserow, redis, openAi, httpRequest. Webhook trigger; 52 nodes.

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

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.

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

Agente_RAG. Uses supabase, embeddingsOpenAi, documentDefaultDataLoader, textSplitterCharacterTextSplitter. Chat trigger; 50 nodes.

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

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.

AI-powered workflow that transforms any article URL into platform-optimized social media posts for LinkedIn, Twitter (X), and Reddit. Uses Mozilla Readability for content extraction, multi-agent AI wi

Corvus 3.2 Beta. Uses httpRequest, agent, lmChatOpenAi, vectorStoreSupabase. Webhook trigger; 48 nodes.

Code-Orch_Agent. Uses chatTrigger, lmChatOpenAi, memoryPostgresChat, toolWorkflow. Chat trigger; 47 nodes.

This n8n workflow automates the process of ingesting files from Google Drive into a Supabase database, preparing them for a knowledge base system. It supports text-based files (PDF, DOCX, TXT, etc.) a

This template creates a comprehensive, production-ready Retrieval-Augmented Generation (RAG) system. It builds a sophisticated AI agent that can answer questions based on documents stored in a specifi

use cases: research stock market in Indonesia. analyze the performance of companies belonging to certain subsectors or company comparing financial metrics between BBCA and BBRI providing technical ana

YT Processing UPDATED. Uses googleSheets, youTube, httpRequest, googleDrive. Event-driven trigger; 44 nodes.

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

Ultimate Agentic RAG AI Agent Template. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, stickyNote. Event-driven trigger; 42 nodes.

Turn your cluttered inbox into a smart, autonomous assistant that categorizes emails, replies to leads, checks your calendar, and notifies you on Telegram—all without lifting a finger.

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 template crawls a website from its sitemap, deduplicates URLs in Supabase, scrapes pages with Crawl4AI, cleans and validates the text, then stores content + metadata in a Supabase vector store us

This workflow builds a dual-system that connects automated document ingestion with a live product catalog chatbot powered by Mistral AI and Supabase.

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

📺 Full walkthrough video: https://youtu.be/r5kN_la0O7I

This workflow acts as an autonomous Tier 2 Customer Support Agent. It doesn't just answer questions; it manages the entire lifecycle of a support ticket—from triage to resolution with Guardrails to de

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

🛠️ How It Works: System Architecture Workflow ini bekerja melalui empat lapisan proses utama yang terintegrasi secara otomatis: Input Processing & Routing Telegram Trigger: Menangkap setiap pesan masu

This RAG workflow allows you to build a smart chat assistant that can answer user questions based on any collection of documents you provide. It automatically imports and processes files from Google D

Page Management. Uses documentDefaultDataLoader, embeddingsOpenAi, googleDrive, googleDriveTrigger. Event-driven trigger; 37 nodes.

BTL AI Page Management. Uses documentDefaultDataLoader, embeddingsOpenAi, googleDrive, googleDriveTrigger. Event-driven trigger; 37 nodes.

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

Indoor Farming Agent. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Webhook trigger; 36 nodes.

This workflow is perfect for: Businesses and teams who need an automated solution to organize, analyze, and retrieve insights from their internal documents. Researchers who want to quickly analyze and

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

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

This workflow creates a conversational assistant that can answer questions based on your Google Drive documents. It automatically processes various file types and uses Retrieval-Augmented Generation (

Upsert Huge Documents In A Vector Store With Supabase And Notion. Uses embeddingsOpenAi, textSplitterTokenSplitter, splitInBatches, chainRetrievalQa. Chat trigger; 34 nodes.

RAG on living data. Uses embeddingsOpenAi, textSplitterTokenSplitter, splitInBatches, chainRetrievalQa. Chat trigger; 34 nodes.

This workflow adds the capability to build a RAG on living data. In this case Notion is used as a Knowledge Base. Whenever a page is updated, the embeddings get upserted in a Supabase Vector Store.

Ai Agent To Chat With Files In Supabase Storage. Uses httpRequest, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, extractFromFile. 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.

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.

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.

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 Telegram workflow batches rapid-fire messages from the same user into one prompt (20–30s debounce), then sends a single AI reply.

Overview

This workflow is your all-in-one pipeline to turn any document into a powerful searchable knowledge base using RAG (Retrieval-Augmented Generation). From the moment a file lands in your Google Drive,

Fluxo-N8N. Uses googleSheetsTool, dataTable, dataTableTool, informationExtractor. Webhook trigger; 30 nodes.

crawl4Ai-rag. Uses httpRequest, xml, documentDefaultDataLoader, textSplitterCharacterTextSplitter. Event-driven trigger; 30 nodes.

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

Supabase RAG AI Agent PDFs & More. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Event-driven trigger; 29 nodes.

CreateWorkPlan. Uses informationExtractor, lmChatAzureOpenAi, outputParserStructured, mcpClientTool. Webhook trigger; 29 nodes.

This workflow is an AI-powered multi-agent system built for startup founders and small business owners who want to automate decision-making, accountability, research, and communication, all through Wh

Answers should given only within provided text. Chat interface powered by LLM (Ollama) Retrieval-Augmented Generation (RAG) using Supabase Vector DB Multi-format file support (PDF, Excel, Google Docs,

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

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

A complete AI-powered study assistant system that lets you chat naturally with your documents stored in Google Drive:

AI-powered n8n workflow that creates viral LinkedIn posts by learning from successful content. Features two modules: (1) Telegram-based scraper that builds a vector database of viral LinkedIn posts, a

RAG_AI_Agent_PDFs_Excel. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Webhook trigger; 28 nodes.

MCP_SUPABASE_AGENT. Uses mcpTrigger, vectorStoreSupabase, embeddingsOpenAi, stickyNote. Event-driven trigger; 27 nodes.

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

Version: 1.0.0 n8n Version: 1.88.0+ Author: Koresolucoes License: MIT

This template is for businesses, customer support teams, and professionals who want to deliver AI-powered WhatsApp assistance. It helps automate conversations, schedule meetings, answer FAQs, and send

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

This workflow is for Product Managers, Indie Hackers, and Customer Success teams who collect feature requests but struggle to notify specific users when those features actually ship. It helps you turn

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.

claude - Agent Yedid AI. Uses httpRequest, agent, lmChatOpenAi, memoryBufferWindow. Webhook trigger; 27 nodes.

RAG Reranking. Uses googleDrive, documentDefaultDataLoader, extractFromFile, chatTrigger. Chat trigger; 26 nodes.

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

Turn your website chat into a lead-generating machine. Visitors chat with an AI that answers questions from your knowledge base, captures their contact info, syncs everything to Google Sheets, and aut

This workflow automatically indexes your n8n workflows every 24 hours, converts them into vector embeddings using OpenAI and stores them in Supabase. It exposes a webhook that lets you query your work

> Zoom + n8n + GPT-4o + Supabase RAG

Reranker. Uses googleDrive, documentDefaultDataLoader, vectorStoreSupabase, rerankerCohere. Event-driven trigger; 26 nodes.

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

Document Ingestion & Processing

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

One-line summary : Answers WhatsApp in under 100 words, understands voice notes, and retrieves trusted answers from your Google Drive docs (RAG) kept fresh weekly.

Fadhil. Uses agent, chatTrigger, mySql, vectorStoreSupabase. Chat trigger; 25 nodes.

Corvus — Ingestão via Formulário. Uses agent, lmChatOpenAi, vectorStoreSupabase, embeddingsOpenAi. Webhook trigger; 25 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.

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

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

Chatbot. Uses googleDrive, vectorStoreSupabase, googleDriveTrigger, documentDefaultDataLoader. Event-driven trigger; 23 nodes.

RAG Agent supabase. Uses chatTrigger, lmChatOpenAi, embeddingsOpenAi, formTrigger. Chat trigger; 23 nodes.

Crawl4AI Agent. Uses httpRequest, xml, documentDefaultDataLoader, textSplitterCharacterTextSplitter. Event-driven trigger; 23 nodes.

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

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

Automatically draft email replies using AI. This workflow monitors your Gmail inbox, filters out automated emails (newsletters, receipts, notifications), and uses AI to create draft responses only for

Optimized Realtor Bot Workflow. Uses telegramTrigger, telegram, openAi, agent. Event-driven trigger; 23 nodes.

n8n-3-2: c4ai — Local Supabase. Uses httpRequest, xml, documentDefaultDataLoader, textSplitterCharacterTextSplitter. Event-driven trigger; 23 nodes.

n8n-4-2: c4ai — Local Supabase RAG. Uses httpRequest, xml, documentDefaultDataLoader, textSplitterCharacterTextSplitter. Event-driven trigger; 23 nodes.

Agent: Local AI RAG: Ollama & Supabase Vector. Uses memoryPostgresChat, lmChatOllama, lmOllama, toolVectorStore. Chat trigger; 23 nodes.

Go beyond basic Retrieval-Augmented Generation (RAG) with this advanced template. While a simple RAG setup can answer straightforward questions, it often fails when faced with complex queries and can

This n8n workflow ensures data freshness in the RAG system by handling modifications to existing files. It complements the "Document Ingestion" workflow by triggering whenever a file in the monitored

N8N Workflow Fixed. Uses chatTrigger, agent, lmChatOpenAi, memoryBufferWindow. Chat trigger; 22 nodes.

Supabase Insertion Upsertion Retrieval. Uses googleDrive, documentDefaultDataLoader, stickyNote, chainRetrievalQa. Chat trigger; 21 nodes.

Supabase Insertion & Upsertion & Retrieval. Uses googleDrive, documentDefaultDataLoader, stickyNote, chainRetrievalQa. Chat trigger; 21 nodes.

Supabase RAG AI Agent. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Event-driven trigger; 21 nodes.

This is a demo workflow to showcase how to use Supabase to embed a document, retrieve information from the vector store via chat and update the database. set your credentials for Supabase set your cre

RestaurantBot Pro is a complete AI-powered restaurant ordering system that transforms your WhatsApp into a smart ordering platform. This intelligent automation handles customer interactions in any lan

Build a custom, intelligent knowledge base in minutes. This n8n workflow provides a complete Retrieval-Augmented Generation (RAG) system using Google Gemini and Supabase. It features a seamless dual-f

Runner QA system. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Event-driven trigger; 21 nodes.

ai-fitness-2. Uses googleDrive, embeddingsGoogleGemini, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Scheduled trigger; 21 nodes.

OPO. Uses openAi, telegram, telegramTrigger, agent. Event-driven trigger; 21 nodes.

What this does

Create a smart chatbot that answers questions using your Google Drive PDFs—perfect for support, internal docs, education, or research. n8n instance (cloud or self-hosted) Google Drive account (with PD

This workflow indexes Google Drive documents into a Supabase vector store using OpenAI embeddings, then exposes a webhook that uses a GPT-4o-mini RAG agent to answer incoming questions with short, voi

voice-assistant. Uses googleDriveTrigger, supabase, googleDrive, vectorStoreSupabase. Event-driven trigger; 19 nodes.

InsightsLM - Chat. Uses lmChatOllama, outputParserStructured, chainLlm, vectorStoreSupabase. Webhook trigger; 19 nodes.

Sales Automation, Artificial Intelligence, CRM Operations, Coaching & Training, AI Agents (RAG)

This template is an end-to-end demo of a chatbot using business data from multiple sources (e.g. Notion, Chargebee, Hubspot etc.) with RAG + SQL.

Description An intelligent conversational AI system that provides contextual responses by combining chat history, vector database knowledge retrieval, and web search capabilities. How it Works (High-l

Convert any website into a searchable vector database for AI chatbots. Submit a URL, choose scraping scope, and this workflow handles everything: scraping, cleaning, chunking, embedding, and storing i

Upload to Supabase Demo. Uses extractFromFile, vectorStoreSupabase, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 18 nodes.

N8N Expert. Uses embeddingsOpenAi, lmChatOpenAi, supabase, chainLlm. Webhook trigger; 18 nodes.

Many websites lack a smart, searchable interface. Visitors often leave due to unanswered questions. This workflow transforms any website into a Retrieval-Augmented Generation (RAG) chatbot—automatical

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

This workflow turns WhatsApp voice messages into an AI assistant using Twilio, VAPI, and modular MCP servers. It handles scheduling, email, and knowledge queries all by voice. WhatsApp → Twilio → VAPI

This n8n workflow is the data ingestion pipeline for the "RAG System V2" chatbot. It automatically monitors a specific Google Drive folder for new files, processes them based on their type, and insert

Learn your voice. Generate posts that sound like you — not AI.

Opo45V5U31Hszckj. Uses documentDefaultDataLoader, embeddingsOpenAi, textSplitterCharacterTextSplitter, vectorStoreSupabase. Event-driven trigger; 18 nodes.

This n8n template demonstrates how to build a WhatsApp-based AI chatbot that answers user questions using document retrieval (RAG) powered by Supabase for storage, OpenAI embeddings for semantic searc

This workflow automates the process of converting Google Drive documents into searchable vector embeddings for AI-powered applications:

This guide is designed for developers, data scientists, and AI enthusiasts who want to create intelligent chatbots capable of understanding and using custom data. Whether you are building a research a

beyscolleciton. Uses chatTrigger, agent, lmChatOpenAi, memoryBufferWindow. Chat trigger; 16 nodes.

RAG. Uses httpRequest, agent, lmChatGoogleGemini, memoryPostgresChat. Webhook trigger; 16 nodes.

Sitemap To Supabase. Uses httpRequest, xml, documentDefaultDataLoader, textSplitterCharacterTextSplitter. Event-driven trigger; 16 nodes.

⚡ How it works

This workflow builds a Retrieval-Augmented Generation (RAG) document chat assistant inside n8n using Supabase Vector Store and AI models.

N8N-Rag-Ingestion-Workflow. Uses googleDriveTrigger, googleDrive, vectorStoreSupabase, documentDefaultDataLoader. Event-driven trigger; 15 nodes.

GPT-5 MCP Multi-Source Orchestrator is a next-generation AI agent for n8n that blends the raw intelligence of GPT-5 with the structured power of MCP tools and multi-source data retrieval. It unifies y

contoh-rag-agent. Uses vectorStoreSupabase, postgresTool, agent, chatTrigger. Webhook trigger; 14 nodes.

Chatbot Webhook. Uses lmChatGoogleGemini, agent, outputParserStructured, memoryPostgresChat. Webhook trigger; 14 nodes.

My workflow 10. Uses vectorStoreSupabase, googleDrive, embeddingsOpenAi, documentDefaultDataLoader. Event-driven trigger; 14 nodes.

Firecrawl RAG. Uses embeddingsOpenAi, vectorStoreSupabase, lmChatOpenAi, agent. Event-driven trigger; 13 nodes.

This workflow automates the first line of customer support by intelligently drafting email replies. It bridges the gap between your CRM (Supabase), your technical documentation (Vector Store), and you

d27-content-automation. Uses googleSheets, chainRetrievalQa, retrieverVectorStore, vectorStoreSupabase. Event-driven trigger; 11 nodes.

AppFlowy Content Sync to Vector Store. Uses n8n-nodes-appflowy, textSplitterRecursiveCharacterTextSplitter, documentDefaultDataLoader, embeddingsOllama. Event-driven trigger; 11 nodes.

Post de discourser. Uses httpRequest, vectorStoreSupabase, embeddingsOpenAi, documentDefaultDataLoader. Scheduled trigger; 11 nodes.

Store Notion's Pages as Vector Documents into Supabase with OpenAI. Uses stickyNote, embeddingsOpenAi, textSplitterTokenSplitter, notionTrigger. Event-driven trigger; 9 nodes.

Store Notion's Pages as Vector Documents into Supabase with OpenAI. Uses stickyNote, embeddingsOpenAi, textSplitterTokenSplitter, notionTrigger. Event-driven trigger; 9 nodes.

d23-RAG. Uses chatTrigger, chainRetrievalQa, lmChatGoogleGemini, retrieverVectorStore. Chat trigger; 7 nodes.

This workflow integrates Google Sheets with Supabase Vector Store for storing personal data as vectors. It utilizes OpenAI and Google Gemini AI models for enhanced data processing and querying.

Grant Application Routing. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Order Shipped Notification. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Blood Test Email Alert. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Notion API Update. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Fitness API Weekly Report. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 12 nodes.

Onboarding Checklist Slack. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Drink Water Reminder. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Blog Comment Discord. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 12 nodes.

Habit Form Weekly Summary. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Disaster API SMS. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 12 nodes.

Zoom Attendance Log. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Return Ticket Assignment. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 12 nodes.

Issue Trello Card. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 12 nodes.

Record Crypto Prices. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 12 nodes.

Bank SMS Alert to Telegram. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Course Completion Certificate. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Medication SMS Reminder. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 12 nodes.

Etsy Review to Slack. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Unsplash to Pinterest. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsCohere, vectorStoreSupabase. Webhook trigger; 12 nodes.

Competitor Price Scraper. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

GitHub Commit Jenkins. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Auto-post Blogs to LinkedIn and Twitter. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.

Alert on Instagram Competitor Story. Uses stickyNote, textSplitterCharacterTextSplitter, embeddingsOpenAi, vectorStoreSupabase. Webhook trigger; 12 nodes.