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Supabase

Database and application backend platform.

Official source ↗ · Source checked 2026-10-25

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Tasks covered in this library

9 tag-associated cases; tool roles have not all been reviewed. This is not the product’s full capability range.

Latest case update:2026-10-25

Workflows, prerequisites & evidence

Content & Creative

Chat with Supabase Storage files using n8n AI Agent

Auto-vectorize PDFs and text files from a Supabase bucket, then answer contextual questions via a chat interface

Read the case’s method and prerequisites

Prerequisites: n8n instance; Supabase project (with Storage and vector extension); OpenAI API Key. Credential types required: supabaseApi and openAiApi. Costs depend on OpenAI embedding and chat usage plus Supabase usage. The source does not provide Supabase vector table initialization SQL; you must prepare the documents table and match_documents function yourself.

n8n · supabase

Associated by case tags. Verify costs, permissions and actual results in the case.

Sales, Marketing & Support

Build an n8n + Peliqan RAG + Text-to-SQL Business Data Chatbot

Input: multi-source business data (CRM/Notion/ERP) → Process: Peliqan sync + Supabase vector store + AI Agent routing → Output: natural-language query answers

Read the case’s method and prerequisites

Requires n8n self-hosted (community node restriction). Prerequisites: Peliqan.io free trial, at least one business data source (Hubspot/Pipedrive/Notion/etc.), Supabase project, OpenAI API Key. Set N8N_COMMUNITY_PACKAGES_ALLOW_TOOL_USAGE=True on self-hosted environment. Costs: OpenAI API usage-based; Peliqan/Supabase have free tiers.

n8n · supabase · peliqan

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Money, Bills & Benefits

Build a Telegram Financial AI Agent with n8n

Input: Telegram message or Chat trigger → Processing: AI Agent calls transaction/balance tools → Output: Telegram reply and financial report

Read the case’s method and prerequisites

Requires an n8n instance (self-hosted or n8n Cloud with community nodes enabled). Prerequisites: Supabase PostgreSQL database with three tables (transactions, balances, memoria_chat), OpenAI API Key, Telegram Bot Token, and two supporting tool workflows (Register Tool / Balance Tool). The source does not provide the tool-workflow JSONs; obtain or build them separately.

n8n · telegram · postgres · supabase

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Content & Creative

n8n Template: RAG Chat Assistant with Claude, Supabase Vector Store, and Postgres Memory

Receives messages via Chat Trigger, processes through an AI Agent calling Claude and Supabase vector retrieval, with Postgres-stored conversation context, and returns a response.

Read the case’s method and prerequisites

Prerequisites: n8n instance (LangChain nodes recommended), Anthropic API key, OpenAI API key, Supabase project with a vector-enabled table, and a PostgreSQL database. Costs depend on API usage and hosting. The workflow.json tableName defaults to '=Your_database' and must be replaced with your actual table name.

n8n

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Sales, Marketing & Support

Telegram Voice or Text Triggers Apollo Lead Scraping, Parsed by GPT-4, Stored in Supabase

Input: Telegram voice/text command → Process: Whisper transcription + GPT parameter extraction → Apify Apollo Scraper → verify and deduplicate → Output: Supabase new leads table + Telegram receipt

Read the case’s method and prerequisites

Requires n8n v0.231+ (self-hosted or Cloud), Telegram Bot Token, OpenAI API Key, Apify account with Apollo-io Scraper Actor, and Supabase project credentials (or swap for Airtable/Sheets). Credential types: telegramApi, openAiApi, apifyApi, postgres. The workflow.json can be imported directly into n8n.

n8n · telegram · apify · supabase · postgres

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Work & Operations

WhatsApp Automated HR Service System: GPT Classification + Google Workspace

Employee sends WhatsApp message → LLM classifies intent → routes to 5 specialized AI agents → auto-processes leave, attendance, FAQ, complaints, candidate shortlisting → replies via WhatsApp

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Prerequisites: n8n instance; WhatsApp Business API credentials (Twilio or Meta); OpenAI API key; Google Sheets/Calendar/Gmail OAuth2; Supabase vector store. Costs: OpenAI per-token; WhatsApp Business API per-message; Google Workspace per subscription. Note: Google Sheets document IDs, Supabase table names, office geo-fence coordinates, and WhatsApp phone numbers in workflow.json are placeholders and must be replaced.

n8n · whatsapp · google-sheets · google-calendar · supabase

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Sales, Marketing & Support

n8n Multi-Channel AI Sales Agent: WhatsApp, Facebook, Instagram Auto-Lead & Booking

Route customer messages from WhatsApp, Facebook Messenger, Instagram DM, and n8n Chat through a GPT-4o agent to automatically qualify leads, answer product questions, log to CRM, and book consultations

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Prerequisites: self-hosted n8n (Langchain community nodes required); OpenAI API key (GPT-4o + Whisper + Embeddings); Airtable account with base (Contacts/Opportunities tables); Supabase vector database (product knowledge base); PostgreSQL database (conversation memory); WhatsApp Business Cloud, Facebook/Instagram Business accounts with webhook configuration access; Meta Graph API credentials. Note: crmAgent and calendarAgent are sub-workflows not included in this template; you must build or source them separately. All node parameters are empty in workflow.json and require post-import configuration.

n8n · supabase · whatsapp

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Work & Operations

Auto-Assign JIRA Tickets with n8n: Supabase Vector Store + AI Matching

Periodically write resolved JIRA tickets to a Supabase vector store; for stale unassigned tickets, use AI to find similar historical records and auto-assign by workload

Read the case’s method and prerequisites

Prerequisites: accessible n8n instance; JIRA Cloud project and API credentials (jiraSoftwareCloudApi); Supabase project with pgvector extension enabled and a documents table; OpenAI API credentials (openAiApi). The template contains two scheduled flows: Flow 1 pulls resolved tickets daily into the vector store; Flow 2 scans stale unassigned tickets, runs AI similarity search and workload-based sorting, then auto-assigns. You must modify JQL and parameters to match your actual project name, team members, and time thresholds. Source does not provide cost estimates.

n8n · supabase

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Content & Creative

Build an AI Agent in n8n: Chat with Files from Supabase Storage and Google Drive

Automatically vectorize documents from a Supabase private bucket or Google Drive folder, then query them through an AI agent with natural-language Q&A

Read the case’s method and prerequisites

Prerequisites: an n8n instance (self-hosted or cloud); a Supabase project with API credentials (supabaseApi); an OpenAI API key (openAiApi); Google Drive OAuth2 credentials (googleDriveOAuth2Api); a LlamaParse API key (httpHeaderAuth). Create a private Supabase bucket and files/documents tables with vector matching enabled. Costs: OpenAI embedding and chat models billed by token; LlamaParse billed by page; Supabase billed by storage and DB usage.

n8n · supabase · google-drive · llamaparse

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