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Voice AI for Restaurant Reservations

Handle inbound calls automatically across a national chain with sub-second latency and autoscaling on GCP.

Introduction

High call volumes during meal times were overwhelming front-of-house teams, leading to missed calls, lost bookings, and inconsistent guest experiences. We implemented a Voice AI layer that answers, understands, and books in real time—so every call is captured without adding headcount.

Built on GCP, the system scales elastically for peaks, routes edge cases to humans, and keeps latency low through regional load balancing and parallel speech-processing. Call summaries and outcomes are logged for continuous improvement.

24/7 automated call handling and reservation creation
Sub-second pickup with latency-optimized speech pipelines
Human handoff for complex requests and special cases
Structured logs/metrics for QA, training, and reporting

Outcomes

Higher booking throughput without extra staff
Zero missed calls during peaks

Approach

Regional load balancing
Parallel speech pipelines
Graceful agent fallback

Stack

GCP (Cloud Run, Load Balancing), Speech APIs, queueing, observability