Laudure
AI Management System for Restaurants
Overview
Laudure is a platform for fine dining restaurants. It features an agent system that automates reservation analysis. The platform answers critical questions: how much of each dish is needed today, when demand spikes occur, and what specific requirements each guest has.
Design
The design philosophy behind Laudure draws inspiration from high-pressure environments like restaurant morning huddles and basketball timeouts. Every design choice answers one question: how can we show what matters without overwhelming people with details?
User Flow
Overview Page
▼The overview page answers how much food needs to be prepared, with everything else intentionally abstracted away. It uses a treemap visualization where box area sizes indicate relative volume needs, maximizing information density at a glance.
Volume Page
▼The volume section introduces time as a critical variable, showing when dishes need to be prepared throughout the evening. An area chart was chosen over a stacked bar chart to better represent the fluid, unpredictable flow of orders.
Timeline Page
▼The timeline showcases back-of-house information in one comprehensive view, answering all the 'what' questions. It features compact guest cards with agent-generated service suggestions ranked on urgency.
Shape System
▼Courses are represented with shapes: triangles for appetizers, squares for mains, and pentagons for desserts. The increasing number of sides (3→4→5) intentionally mirrors both the dining progression and the growing complexity across the interface.
Agent System
A collection of specialized AI agents analyze restaurant diner data and provide insights through a modular, multi-agent approach.
Specialized Agents
Dietary Analysis Agent
Identifies allergies and dietary restrictions
Guest Experience Agent
Analyzes past impressions and preferences
Special Requests Agent
Handles explicit requests and time-sensitive needs
Personalization Agent
Suggests personalization and upsell opportunities
Coordinator Agent
Combines insights into a cohesive briefing
Sample Agent Output Structure
"agent_analysis": {
"agent_analysis": {
"dietary_analysis": {
"allergies": [
{
"item": "String - Allergen name",
"severity": "String - Severity level (e.g., mild, critical)",
"source": "String - Where this information was obtained"
}
],
"dietary_restrictions": [
"String - Array of dietary restrictions"
],
"preparation_instructions": [
{
"dish": "String - Name of the dish",
"instruction": "String - Special preparation instructions"
}
]
},
"guest_experience": {
"past_impressions": [
{
"type": "String - Positive or negative",
"aspect": "String - What aspect of dining was mentioned",
"source": "String - Source of this impression"
}
],
"service_preferences": {
"style": "String - Preferred service style (e.g., attentive, hands-off)",
"evidence": "String - Evidence for this preference"
},
"conversation_topics": [
{
"topic": "String - Topic of interest",
"context": "String - Context for this topic"
}
]
},
"special_requests": {
"explicit_requests": [
{
"request": "String - Specific request made by guest",
"priority": "String - Priority level (high, medium, low)",
"source": "String - Source of this request"
}
],
"service_modifications": [
{
"modification": "String - Service modification needed",
"notes": "String - Additional notes about the modification"
}
],
"time_sensitive": [
{
"need": "String - Time-sensitive need",
"timing": "String - When this need should be addressed"
}
],
"special_occasions": [
{
"occasion": "String - Special occasion being celebrated",
"details": "String - Details about the occasion"
}
]
},
"personalization": {
"personalization_opportunities": [
{
"opportunity": "String - Opportunity to personalize experience",
"implementation": "String - How to implement this opportunity",
"impact": "String - Expected impact level"
}
],
"upsell_opportunities": [
{
"item": "String - Item that could be upsold",
"rationale": "String - Rationale for this upsell opportunity"
}
],
"recognition_moments": [
{
"moment": "String - Moment for recognition",
"approach": "String - Approach for this recognition"
}
]
}
},
"coordinator_summary": {
"priority_alerts": [
{
"alert": "String - Alert message",
"category": "String - Category of alert",
"for": "String - Department responsible"
}
],
"guest_profile": {
"dining_style": "String - Guest's dining style",
"preferences": ["String - Array of preferences"],
"avoid": ["String - Array of things to avoid"]
},
"service_recommendations": [
{
"recommendation": "String - Service recommendation",
"timing": "String - When to implement",
"owner": "String - Who is responsible"
}
],
"kitchen_notes": [
{
"note": "String - Note for the kitchen",
"dish": "String - Dish this note applies to",
"tags": ["String - Array of relevant tags"],
"urgency": "String - Urgency level (e.g., red, orange, green)"
}
]
}
}