All Case Studies / NOWAITN.COM
AI-Powered SaaS Platform 6 months 5 engineers

NOWAITN.COM

From Restaurant Waitlists to Enterprise Queue Intelligence — An AI-Native Platform

500K+
Customers Queued
42%
Wait Time Reduced
99.97%
Uptime SLA
< 2s
SMS Delivery

The Challenge

NOWAITN started as a restaurant waitlist tool but the vision was far more ambitious: an AI-powered queue management platform that could serve any industry — restaurants, healthcare clinics, government offices, events, barbershops. The system needed real-time capacity tracking across multiple zones per venue, an AI assistant ("Q") that could intelligently communicate with waiting customers via SMS, staff mobile apps for on-the-floor management, and an analytics dashboard that turns queue data into operational insights. The platform had to handle thousands of concurrent queues with sub-second SMS delivery and multi-tenant isolation.

The Solution

We built a multi-tenant Laravel SaaS platform with a microservices-inspired architecture. The core queue engine uses Redis for real-time state management with MySQL for persistence and analytics. The AI assistant "Q" integrates with OpenAI's API through a custom prompt engineering layer that understands queue context — position, estimated wait, venue-specific messaging — and communicates naturally via Twilio SMS. The staff mobile app is a responsive PWA with real-time updates via WebSockets. Each venue gets isolated data, custom branding, and configurable queue rules. The capacity tracking system uses zone-based modeling that accounts for table turns, service duration estimates, and historical patterns.

AI Queue Assistant "Q"

Smart SMS queue updates

Mobile Staff App

Manage from iPhone/Android

Capacity Tracking

Occupancy & zone management

Multi-Venue Support

Enterprise-ready platform

Platform Architecture

High-level overview of the system architecture powering NOWAITN.COM. Hover over components to see details.

Build Process

Phase 1 3 weeks

Discovery & Architecture

Interviewed 15 venue operators across restaurant, healthcare, and events verticals. Mapped queue workflows, identified pain points, designed multi-tenant architecture and AI assistant behavior model.

Phase 2 8 weeks

Core Platform

Built multi-tenant Laravel application with queue engine, real-time WebSocket infrastructure, Twilio SMS integration, and the Admin dashboard for venue management.

Phase 3 6 weeks

AI Assistant & Mobile

Developed "Q" AI assistant with context-aware messaging, staff PWA with real-time queue management, and the customer-facing queue status pages.

Phase 4 4 weeks

Analytics & Capacity

Built capacity tracking with zone modeling, analytics dashboard with historical trends, wait time predictions, and peak hour analysis.

Phase 5 3 weeks

Enterprise & Launch

Multi-venue management, white-label branding, SSO integration, load testing to 10K concurrent queues, and staged production rollout.

Total: 6 months from kickoff to production

Tech Stack

The technologies and services powering NOWAITN.COM.

Laravel 11
Backend
Vue.js 3
Frontend
Tailwind CSS
Styling
MySQL
Database
Redis
Real-time State
OpenAI GPT-4
AI Engine
Twilio
SMS
WebSockets
Real-time
AWS EC2
Hosting
Cloudflare
CDN/Security

Results & Impact

Processed over 500,000 customer queue entries in the first year of operation

AI assistant "Q" reduced customer no-shows by 38% through intelligent SMS engagement

Average customer wait time reduced by 42% through capacity optimization algorithms

Platform handles 10,000+ concurrent active queues with 99.97% uptime

SMS delivery time averages 1.8 seconds from queue event to customer notification

Expanded from restaurants to healthcare, events, and government services within 6 months

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6 months
Timeline
5 engineers
Team
2026
Year
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