All Projects
Voice AIFood ServiceRestaurant TechCustomer Support

Restaurant Order-Taking Voice AI Agent

Takes phone orders end-to-end — menu items, customizations, upsells, order total — and hands off a confirmed order to your kitchen or POS, with no staff member tied up on the phone. As little as 1-second response time. Self-hosted for lowest cost, or managed on ElevenLabs / Retell AI for fastest go-live.

Build a Similar AI SystemWatch Demo (3:18)

Free 30-min scope call · reply within 24h

Restaurant Order-Taking Voice AI Agent handling a phone order
Voice AI

Workflow & Architecture

How this system works

Step 1
Inbound call

Customer calls in to place an order for pickup or delivery.

Step 2
Speech pipeline

STT transcribes audio with noise isolation, turn detection, and interruption handling.

Step 3
Order reasoning

Agent matches menu items, handles substitutions and customizations, and offers relevant upsells.

Step 4
Voice response

TTS streams a natural reply back in real time (~1–1.5s on LiveKit STS).

Step 5
Order confirmation & handoff

Order is confirmed with the customer and routed to the kitchen or POS system.

Overview

End-to-end restaurant order-taking voice agents that handle menu questions, customizations, and upsells without a staff member on the phone. Built on the same pipeline as our solar sales agent — delivered across three platform approaches so clients can choose self-hosted control, ElevenLabs voice quality, or Retell AI's managed infrastructure.

The Problem

Restaurants lose orders and staff time to busy phone lines — calls go unanswered during rush hours, staff get pulled off food prep to take orders, and mistakes on complex customizations cost money. Voice AI can staff the phone line 24/7, but platform choice still affects cost per minute, latency, vendor lock-in, and deployment speed.

The Solution

Built the same order-taking and confirmation flow on three stacks — a custom speech-to-speech pipeline on LiveKit, plus managed agents on ElevenLabs and Retell AI — so clients pick the trade-off that fits their operations.

Platform options

How we deliver this use case

The same restaurant order-taking flow — built on LiveKit for lowest latency and cost, ElevenLabs for voice quality, or Retell AI when that platform is already in your stack.

PlatformLatencyCost modelWho owns the stackBest for
Self-Hosted · LiveKit~1–1.5sNo per-minute licensingClientLowest latency, cost, and full control
Managed · ElevenLabsReal-timePlatform pricingElevenLabsFast deployment and high-quality voice
Managed · Retell AIReal-timePlatform pricingRetell AIFast deployment for teams already using Retell AI
Recommended approach

Custom STS Pipeline + LiveKit

Ultra-low latency and lower operating cost — full stack ownership, no vendor lock-in.

Watch demo

Challenge

Restaurants want to avoid per-minute licensing and vendor lock-in, or need faster response times than managed platforms typically deliver.

What we built

Designed a custom speech-to-speech pipeline on LiveKit with self-hosted STT/TTS, voice isolation, noise suppression, and natural interruption handling — reused from the same architecture as our solar sales agent.

Key capabilities

  • Ultra-low latency: ~1–1.5 second response time
  • Lower operating cost — no per-minute third-party licensing
  • Voice isolation, noise suppression, and smooth interruption handling
  • Fully self-hosted — client owns the stack
LiveKitCustom STS PipelinePythonReal-Time Audio

Production-ready self-hosted alternative to expensive managed voice platforms

Key Features

  • Real-time order-taking across menu items, customizations, and upsells
  • Three platform options: self-hosted LiveKit available now; ElevenLabs/Retell builds available on request
  • Natural voice with substitution handling and order confirmation flows
  • Ultra-low latency option (~1–1.5s) on custom STS pipeline

What This Enables

  • Takes phone orders during rush hours without pulling staff off food prep
  • Handles overflow and after-hours calls instead of losing them to a busy signal
  • Delivers consistent order accuracy on every call, regardless of platform

Related Projects