Restaurant Voice Assistant: VAPI + PostgreSQL Bookings & Orders

Build a voice AI assistant for restaurants using VAPI for calls and PostgreSQL for managing bookings, orders, and info queries with natural language processing.

n8n
Restaurant Voice Assistant: VAPI + PostgreSQL Bookings & Orders

This n8n workflow creates a comprehensive voice-powered restaurant assistant that handles table reservations, food orders, and information requests via natural language. Powered by VAPI for real-time voice interactions and PostgreSQL for secure data storage, it processes customer calls to extract details like party size, booking times, and menu items, then confirms via voice while logging everything in dedicated tables (bookings, orders, restaurant_info).

Key features include real-time database operations with immediate confirmations, support for multiple simultaneous calls, and conversational responses for queries on hours, menu, or location. Wait nodes ensure smooth data flow, and all data is indexed for performance. Benefits include automating customer service, reducing staff workload, and providing 24/7 availability, ideal for busy restaurants seeking efficient voice AI solutions.

Use cases: Small to medium restaurants for reservation management; quick-service spots for order intake; any eatery wanting voice-enabled self-service. Requires VAPI subscription (per-minute billing) and PostgreSQL setup. Easy to customize with your restaurant data for scalable automation.

$24.99
Last updated October 17, 2026
30-day money-back guarantee
Instant download
Lifetime updates included

New buyers can create an account from the cart to unlock a controlled $10 first-purchase credit on eligible orders of $25+.

Secure checkout powered by Stripe

Support

How to import this workflow into n8n

  1. 1Purchase or download the workflow to get the n8n workflow JSON file.
  2. 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
  3. 3Open each node marked with a credential warning and connect your own accounts and API keys.
  4. 4Run the workflow once manually to verify the data flow, then toggle it to Active.

Related Language Tools workflows

More from Jose Maurino

Need this deployed? We'll set it up for you.

Our automation experts deploy this workflow in your stack, connect your accounts, and verify it works — or build a custom solution from scratch.