Supabase workflows
10 results — all source-linked n8n references
Monitor brand visibility in AI search with ChatGPT, Perplexity, Gemini, Claude, and Supabase
Quick Overview This workflow asks buyer-intent questions to ChatGPT Search (OpenAI), Perplexity, Google Gemini Search, and Anthropic Claude, scores whether your brand is cited or mentioned in each answer, logs every check to Supabase, and outputs an overall and per-engine visibility scorecard. How it works Starts when you run the workflow manually. Sets your brand name/domain and a list of buyer questions, then creates one item per question. Sends each question to Anthropic Claude, OpenAI Chat Completions (gpt-4o-search-preview), Perplexity (sonar), and Google Gemini with Google Search enabled. Parses each engine’s response to detect whether your brand domain is cited or your brand name is mentioned, and assigns a score (1 for cited, 0.5 for mentioned, 0 for absent). Writes each scored check (brand, engine, question, score, cited, mentioned) as a row into a Supabase table. Aggregates the results into a per-engine percentage and an overall panel score, then prints a console scorecard with top “not cited” targets. Setup Add environment variables in n8n for ANTHROPIC_API_KEY, OPENAI_API_KEY, PERPLEXITY_API_KEY, and GEMINI_API_KEY. Create a Supabase table named ai_visibility_log with c
Build multi-touch attribution reports with Supabase multi-model MTA
Quick Overview This workflow ingests marketing touch events, stores them in Supabase, stitches identities by shared email, and calculates first-touch, last-touch, linear, and time-decay multi-touch attribution credit per channel, outputting a side-by-side model comparison. How it works Runs when triggered manually (or can be adapted to receive real touch events via a webhook). Loads configuration such as the channel list and the time-decay half-life window. Generates a batch of synthetic multi-touch customer journeys for the demo run. Writes all touch events to a Supabase table via the Supabase REST API. Reloads the stored touches from Supabase and merges visitors into a single identity when they share an email address. Computes revenue-weighted channel credit across converting journeys using first-touch, last-touch, linear, and time-decay attribution models. Prints a formatted comparison table of channel credit across the four models. Setup Create a Supabase project and table (for example, mta_touches) to store touch events, matching the fields used in the workflow (visitor_id, email, channel, ts, is_conversion, revenue). Add SUPABASE_URL and SUPABASE_KEY environment variables to
Match product manager jobs with Supabase, Anthropic Claude, Adzuna, and Resend
Quick overview This workflow ingests job postings from Greenhouse/Lever/Ashby job boards, Adzuna, and RemoteOK into a Supabase jobs pool, then daily uses Anthropic Claude to score a short list against a single candidate profile and emails the best matches via Resend. How it works Runs every 3 hours to fetch job listings from curated Greenhouse, Lever, and Ashby ATS boards, Adzuna searches, and the RemoteOK API. Parses each source into a common job format (title, company, location, URL, description, and posted date). Deduplicates jobs, drops postings older than 90 days, marks “fresh” jobs, and upserts the results into a Supabase jobs table. Runs daily at 08:00, loads the single role profile and pulls up to 15 fresh jobs from Supabase that roughly match the role keyword. Removes jobs already matched for that role using the Supabase user_job_matches table, then batches the remaining jobs and sends them to Anthropic Claude for fit scoring. Keeps jobs at or above the configured minimum score, saves the new matches back to Supabase, and sends an HTML email digest to the role’s email address via Resend. If any execution fails, an error workflow formats the failure details and sends an ale
Send DocuSign envelopes with Supabase contract data
Quick overview This workflow is triggered by another n8n workflow, fetches an assessment record from Supabase, generates an HTML contract, and sends it as a DocuSign envelope using JWT authentication in either production or sandbox based on the recipient email, then writes the envelope ID and status back to Supabase. How it works Receives an execution request from another workflow with an assessment ID (and optional contract title). Retrieves the matching assessment record from the Supabase assessments table. Generates a styled contract HTML document from the assessment data and Base64-encodes it for DocuSign. Chooses the DocuSign sandbox or production path based on whether the contact email contains a specific marker string. Calls a Supabase Edge Function to create a DocuSign JWT assertion, exchanges it for a DocuSign access token, and creates a “sent” envelope with two signers and anchor-based signature tabs. Updates the Supabase assessment record with the DocuSign envelopeId and sets the contract status to envelope_sent. Setup Create and connect Supabase credentials in n8n, and update the Supabase project URL for the Edge Function endpoint (/functions/v1/docusign-sign-jwt). Conf
Manage gym check-ins and subscriptions with Supabase, Google Sheets, and QR codes
Quick overview Youtube Video: https://youtu.be/QyIalCCy6s8?si=Zlmde_oZz3qbDGwJ Github Repo: https://github.com/blankarrayy/automated-gym-checkin-system This workflow handles gym entry via QR codes by validating check-in requests against Supabase subscription data, logging entry attempts in Supabase, it also generates QR codes for check-in and registration and syncs new user IDs to Google Sheets. How it works Receives a POST request on the /gymcheckin webhook with header authentication and an entry_id query parameter. Looks up the entry_id in the Supabase entry_logs table to detect whether the QR code was already used. If the entry_id is unused, extracts the user ID from the request body and fetches subscription records from the Supabase gym_sub table. Validates that the user exists and has an active subscription, then writes an entry attempt record to the Supabase entry_logs table. Returns a webhook response granting entry (200), rejecting unknown users (401), rejecting inactive subscriptions (401), or rejecting reused QR codes (409). On the /qr-for-gym-checkin webhook, generates a new check-in QR code (pointing to the /gymcheckin URL with a random entry_id) and returns it as a bin
Send fee-due WhatsApp reminders to students using Supabase
Quick overview This workflow runs daily to fetch pending student fee records from Supabase, filters fees due in three days, and sends WhatsApp Business template reminders via the Meta WhatsApp Cloud API, then updates Supabase to mark each reminder as sent. How it works Runs every day at 9:00 AM on a schedule. Pulls all pending fee records from Supabase where reminder_sent is false and status is pending. Filters the results to only students whose due_date matches exactly three days from today. Sends a pre-approved WhatsApp template message (Meta WhatsApp Cloud API) to each student’s phone number. Updates the corresponding Supabase row to set reminder_sent to true so the reminder is not sent again. Setup Create a Supabase project, add a student_fees table (including student_phone, due_date, amount_due, status, and reminder_sent fields), and ensure your fee records are stored there. Add Supabase credentials in n8n and set the correct table name in the Supabase nodes. Set up Meta WhatsApp Business Cloud API access in n8n (system user token/credentials) and fill in your WhatsApp phone number ID. Create and get approval for a WhatsApp message template, then replace REPLACE_WITH_YOUR_APPR
Recover missed clinic appointments with Supabase and WhatsApp
Quick overview This workflow runs every 15 minutes to find unprocessed clinic appointments in Supabase that are more than 30 minutes past their scheduled time and sends a WhatsApp Business template message to the patient to prompt rebooking, then flags the appointment so it is not messaged again. How it works Runs every 15 minutes on a schedule. Reads appointments from Supabase where the patient is not checked in and the no-show reminder has not been processed. Filters the results to appointments that are at least 30 minutes past the scheduled appointment time. Loops through each qualifying appointment and sends a pre-approved WhatsApp Business template to the patient’s phone number. Updates the appointment record in Supabase to mark it as processed so it is not nudged again. Setup Create a Supabase project with an appointments table (including appointment_time, patient_phone, checked_in, and no_show_processed) and ensure your booking system writes appointments into it. Add a Supabase credential in n8n with access to the project and table used by the workflow. Set up Meta WhatsApp Business Cloud API access in n8n (token/connection), then enter your WhatsApp phone number ID and an a
Call analyzer with AssemblyAI transcription and OpenAI assistant integration
Video Guide I prepared a detailed guide that showed the whole process of building a call analyzer. .png) Who is this for? This workflow is ideal for sales teams, customer support managers, and online education services that conduct follow-up calls with clients. It’s designed for those who want to leverage AI to gain deeper insights into client needs and upsell opportunities from recorded calls. What problem does this workflow solve? Many follow-up sales calls lack structured analysis, making it challenging to identify client needs, gauge interest levels, or uncover upsell opportunities. This workflow enables automated call transcription and AI-driven analysis to generate actionable insights, helping teams improve sales performance, refine client communication, and streamline upselling strategies. What this workflow does This workflow transcribes and analyzes sales calls using AssemblyAI, OpenAI, and Supabase to store structured data. The workflow processes recorded calls as follows: Transcribe Call with AssemblyAI: Converts audio into text with speaker labels for clarity. Analyze Transcription with OpenAI: Using a predefined JSON schema, OpenAI analyzes the transcription to extract
Telegram Bot with Supabase memory and OpenAI assistant integration
Video Guide I prepared a detailed guide that showed the whole process of building an AI bot, from the simplest version to the most complex in a template. .png) Who is this for? This workflow is ideal for developers, chatbot enthusiasts, and businesses looking to build a dynamic Telegram bot with memory capabilities. The bot leverages OpenAI's assistant to interact with users and stores user data in Supabase for personalized conversations. What problem does this workflow solve? Many simple chatbots lack context awareness and user memory. This workflow solves that by integrating Supabase to keep track of user sessions (via What this workflow does This Telegram bot template connects with OpenAI to answer user queries while storing and retrieving user information from a Supabase database. The memory component ensures that the bot can reference past interactions, making it suitable for use cases such as customer support, virtual assistants, or any application where context retention is crucial. 1.Receive New Message: The bot listens for incoming messages from users in Telegram. Check User in Database: The workflow checks if the user is already in the Supabase database using the Create N
Better Oauth2.0 workflow for Pipedrive CRM with Supabase
This workflow provides an OAuth 2.0 auth token refresh process for better control. Developers can utilize it as an alternative to n8n's built-in OAuth flow to achieve improved control and visibility. In this template, I've used Pipedrive API, but users can apply it with any app that requires the authorization_code for token access. This resolves the issue of manually refreshing the OAuth 2.0 token when it expires, or when n8n's native OAuth stops working. What you need to replicate this Your database with a pre-existing table for storing authentication tokens and associated information. I'm using Supabase in this example, but you can also employ a self-hosted MySQL. Here's a quick video on setting up the Supabase table. Create a client app for your chosen application that you want to access via the API. After duplicating the template: a. Add credentials to your database and connect the DB nodes in all 3 workflows. Enable/Publish the first workflow, "1. Generate and Save Pipedrive tokens to Database." Open your client app and follow the Pipedrive instructions to authenticate. Click on Install and test. This will save your initial refresh token and access token to the database. Pleas