AI-Powered Business Operations for Miami Beach Coffee & Ice Cream Kiosk
Devon Clemente | AI Automation | Sprint 5 - Final Project
The demo company operates a coffee and ice cream kiosk right by the beach in Miami, Florida. Weather in coastal cities changes quickly and directly impacts business operations.
Hot and humid mornings bring surges in iced coffee and gelato sales, while windy days mean fewer beachgoers and more locals grabbing comfort food.
The kiosk manager currently checks forecasts manually, then decides product and staffing plans. This manual checking wastes time and delays preparation.
An automated workflow that transforms weather data into actionable business recommendations:
Fetches the daily forecast for Miami, FL at 7:00 AM automatically
Uses AI to interpret the forecast and generate intelligent recommendations
Provides product mix recommendations (hot drinks, cold drinks, gelato, pastries)
Suggests staffing adjustments based on weather conditions
Creates two short customer promo messages tailored to the weather
Emails the manager with a comprehensive summary every morning
Every day at 7:00 AM Zapier automation starts
GET request via Webhooks Fetch Miami weather data
Google AI Studio (Gemini) Process weather into business insights
Gmail sends formatted report Product, staffing, & promo recommendations
Automates the time-consuming process of checking weather forecasts, analyzing conditions, and creating daily operational plans - saving managers 30+ minutes each morning.
Upgrades the manager's existing morning weather routine by automatically converting raw weather data into actionable business recommendations for inventory, staffing, and promotions.
Ensures daily business adjustments are made systematically and delivered reliably at 7 AM, preventing missed opportunities due to weather changes or human oversight.
Refine the prompt to include seasonal Miami tourism patterns and local event data for even more targeted business recommendations tailored to high-traffic periods.
Expand the system to manage multiple kiosk locations simultaneously, with location-specific weather data and customized product portfolios for different demographic areas.
Connect the system to point-of-sale data to automatically adjust recommendations based on actual product performance, creating a feedback loop that continuously improves AI accuracy over time.
Explore the technical implementation and see the automation in action