AITravelMate - your business trips managed by AI
The AI-native travel planning SaaS will leverage Generative AI to provide personalized and efficient travel itineraries. The system must support multitenancy, allowing multiple tenants to use the application independently with their own data, preferences, and policies. Each tenant’s data should be isolated and securely managed. The system needs to track a list of draft itineraries that are not yet booked, a list of completed bookings, the ability to remind users when their travel date is approaching, and store travel preferences for each tenant to inform itinerary decisions. Additionally, the system should provide analytics on past travel spends. Security and privacy are paramount; hence, the system must comply with data protection regulations and implement robust authentication and authorization mechanisms. Finally, the architecture should be scalable to handle high traffic volumes and flexible to integrate with third-party services for real-time updates on travel information.
PostgreSQL Schemas
1. tenants_preferences
This table stores various preferences for each tenant, which the AI uses to generate personalized travel plans. Preferences are stored as key-value pairs in JSON format.
2. user_travel_history
This table tracks the travel history of users per tenant. It includes details such as travel dates, destinations, activities, and total spend. This information is useful for generating analytics and improving future travel plans.
3. itineraries
Itinerary Schema:** This table stores draft and confirmed itineraries for users per tenant. It includes details like start and end dates, destinations, and a flag indicating whether the itinerary is a draft.
4. itinerary_details
This table provides detailed daily activities for each itinerary. It includes the date, type of activity, and specific details about the activity, stored in JSON format.
5. bookings
This table tracks travel bookings made by users per tenant. It includes details about the booking type (e.g., flight, hotel), booking details, and status.
6. booking_reminders
This table stores reminders for users about their upcoming bookings. It includes the reminder date, message, and a flag indicating whether the reminder has been sent.
7. travel_analytics
This table stores analytics data about past travel spends for users per tenant. It includes the travel date, total spend, and a breakdown of spends by categories stored in JSON format.
Full Script
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