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Connect Supabase to ElevenLabs Conversational AI Voice Agents

Seamless Real-Time Voice AI with Database Power

Setup time

10-15mins

Difficulty

Intermediate

Category

Scheduling & Communication

Type

API

Let your AI Voice Agents Access Live Data with Supabase

The Supabase + ElevenLabs integration creates a powerful voice-driven interface for your application data. Your AI agents can now query databases, react to real-time changes, and trigger server-side logic through natural conversation – all while maintaining the low-latency performance your users expect.

How It Works

Your ElevenLabs voice agents connect directly to Supabase's auto-generated REST API and Edge Functions, enabling real-time data access during conversations. Users can ask questions like "What's my order status?" or "Show me today's analytics," and your agent instantly retrieves and responds with live data from your Supabase database.

Key Capabilities

  • Real-time data queries during voice conversations
  • Secure API integration with built-in authentication
  • Serverless logic execution via Supabase Edge Functions
  • Global low-latency access through distributed infrastructure
  • Seamless scalability that grows with your user base

Developer Benefits

This integration is built for developers who need reliable, controllable voice AI that integrates seamlessly with existing systems. No complex custom backends required – Supabase's PostgreSQL foundation means you can use standard SQL while ElevenLabs handles the voice layer with enterprise-grade reliability.

Features

Integrations features

Powerful capabilities that make your voice agents smarter and more responsive

Real-Time Database Access

  • Direct API calls to Supabase during live conversations
  • Instant data retrieval with sub-second response times
  • Support for complex SQL queries and joins
  • Built-in caching for frequently accessed dat

Secure Authentication & Authorization

  • JWT-based authentication with Supabase Auth
  • Row-level security for user-specific data access
  • API key management with role-based permissions
  • Encrypted data transmission for sensitive information

Edge Function Integration

  • Custom serverless logic execution during calls
  • Multi-table operations and external API calls
  • TypeScript/JavaScript support for complex workflows
  • Global deployment for minimal latency

Multilingual Data Support

  • Voice interactions in 31+ languages
  • Unified database queries regardless of input language
  • Real-time translation capabilities
  • Cultural context preservation in responses

Real-Time Data Synchronization

  • Live database updates during active conversations
  • Webhook support for proactive notifications
  • Event-driven responses to data changes
  • Seamless integration with existing workflows

Installation

Installation guides

Get your Supabase + ElevenLabs integration up and running quickly

Step 1: Prepare Supabase Access

Gather your Supabase project credentials

  • Log into your Supabase dashboard at app.supabase.com
  • Select your project or create a new one
  • Navigate to Settings then API in the left sidebar
  • Copy your Project URL which looks like https://your-project.supabase.co
  • Copy your Service Role Key for server-side operations
  • Note your Anon Key if you need public access

Configure Row Level Security

  • Go to Authentication then Policies in Supabase
  • Set up appropriate RLS policies for tables your agent will access
  • Ensure service role key has necessary permissions
  • Test policies with sample queries in SQL Editor

Step 2: Configure ElevenLabs Agent

Store Supabase Credentials Securely

  • Navigate to your ElevenLabs Conversational AI dashboard
  • Go to Settings then Secrets Manager
  • Create new secret named SUPABASE_SERVICE_KEY
  • Paste your Supabase service role key as the value
  • Create another secret named SUPABASE_URL with your project URL

Access Tools Configuration

  • Select your voice agent from the dashboard
  • Navigate to Tools section
  • Click Add New Tool to create database integrations

Step 3: Define Database Tools

Query Database Tool

  • Name: query_database
  • Description: Retrieves data from Supabase database
  • Method: GET
  • URL: Enter your Supabase project URL followed by /rest/v1/table_name
  • Add header named apikey and select SUPABASE_SERVICE_KEY from securely stored secrets
  • Add Authorization header and select Bearer token option with SUPABASE_SERVICE_KEY
  • Add Content-Type header with value application/json

Insert Record Tool

  • Name: insert_record
  • Description: Creates new records in Supabase database
  • Method: POST
  • URL: Enter your Supabase project URL followed by /rest/v1/table_name
  • Add header named apikey and select SUPABASE_SERVICE_KEY from securely stored secrets
  • Add Authorization header and select Bearer token option with SUPABASE_SERVICE_KEY
  • Add Content-Type header with value application/json
  • Add Prefer header with value return=representation

Update Record Tool

  • Name: update_record
  • Description: Updates existing records in Supabase
  • Method: PATCH
  • URL: Enter your Supabase project URL followed by /rest/v1/table_name
  • Add header named apikey and select SUPABASE_SERVICE_KEY from securely stored secrets
  • Add Authorization header and select Bearer token option with SUPABASE_SERVICE_KEY
  • Add Content-Type header with value application/json
  • Configure query parameters for record selection

Delete Record Tool

  • Name: delete_record
  • Description: Removes records from Supabase database
  • Method: DELETE
  • URL: Enter your Supabase project URL followed by /rest/v1/table_name
  • Add header named apikey and select SUPABASE_SERVICE_KEY from securely stored secrets
  • Add Authorization header and select Bearer token option with SUPABASE_SERVICE_KEY
  • Configure query parameters for record selection

Step 4: Configure Agent Prompts

Update System Prompt

Add database access instructions to your agent's system prompt:

You have access to a Supabase database with the following tools:

  • query_database: Use this to retrieve information when users ask about data
  • insert_record: Use this to create new entries based on user input
  • update_record: Use this to modify existing data when requested
  • delete_record: Use this to remove records when authorized

Always confirm data modifications with users before executing insert, update, or delete operations. When retrieving data, present it in a natural, conversational manner.

Configure Tool Descriptions

For each tool, provide clear descriptions that help the agent understand when to use them:

  • Query tool: Triggered by questions about existing data, searches, or lookups
  • Insert tool: Activated when users want to add new information or create records
  • Update tool: Used when users request changes to existing data
  • Delete tool: Employed carefully when users need to remove information

Set Up Response Handling

Train your agent to handle database responses appropriately:

  • Parse returned data and present it conversationally
  • Handle empty results gracefully with helpful messages
  • Confirm successful insertions and updates
  • Provide error messages in user-friendly language

Troubleshooting

Troubleshooting & support

Common issues and solutions for smooth operation

Contact support

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