--- title: "AI Agent for Catering Coordination: Menu Selection, Headcount, and Event Planning" description: "Learn how to build an AI catering agent that guides clients through menu selection, handles dietary requirements, calculates pricing based on headcount, and manages event logistics." canonical: https://callsphere.ai/blog/ai-agent-catering-coordination-menu-selection-event-planning category: "Learn Agentic AI" tags: ["Catering AI", "Event Planning", "Agentic AI", "Hospitality", "Python"] author: "CallSphere Team" published: 2026-03-17T00:00:00.000Z updated: 2026-05-06T01:02:44.267Z --- # AI Agent for Catering Coordination: Menu Selection, Headcount, and Event Planning > Learn how to build an AI catering agent that guides clients through menu selection, handles dietary requirements, calculates pricing based on headcount, and manages event logistics. ## Why Catering Coordination Needs AI Agents Catering inquiries are complex, multi-turn conversations that involve menu selection across courses, dietary accommodation for diverse groups, pricing calculations with volume discounts, and logistics coordination for venue, timing, and staffing. A single catering inquiry can take 30 to 60 minutes of a coordinator's time. An AI catering agent handles the entire discovery and quoting process, freeing human coordinators to focus on execution. The agent must balance being consultative — recommending menus and packages — while collecting the structured information needed to generate an accurate proposal. ## Modeling the Catering Domain ```python from dataclasses import dataclass, field from datetime import date from enum import Enum class ServiceStyle(Enum): BUFFET = "buffet" PLATED = "plated" FAMILY_STYLE = "family_style" COCKTAIL = "cocktail_reception" BOX_LUNCH = "box_lunch" class DietaryTag(Enum): VEGETARIAN = "vegetarian" VEGAN = "vegan" GLUTEN_FREE = "gluten_free" NUT_FREE = "nut_free" DAIRY_FREE = "dairy_free" HALAL = "halal" KOSHER = "kosher" @dataclass class CateringItem: item_id: str name: str course: str # appetizer, main, side, dessert, beverage price_per_person: float dietary_tags: list[DietaryTag] = field(default_factory=list) description: str = "" min_order: int = 10 @dataclass class CateringPackage: package_id: str name: str description: str price_per_person: float includes: list[str] # list of item descriptions service_style: ServiceStyle min_guests: int = 20 @dataclass class CateringQuote: event_name: str event_date: date guest_count: int service_style: ServiceStyle selected_items: list[CateringItem] = field(default_factory=list) selected_package: CateringPackage | None = None dietary_requirements: dict[str, int] = field(default_factory=dict) notes: str = "" @property def food_cost(self) -> float: if self.selected_package: return self.selected_package.price_per_person * self.guest_count return sum( item.price_per_person * self.guest_count for item in self.selected_items ) @property def service_fee(self) -> float: multiplier = { ServiceStyle.BUFFET: 0.15, ServiceStyle.PLATED: 0.22, ServiceStyle.FAMILY_STYLE: 0.18, ServiceStyle.COCKTAIL: 0.20, ServiceStyle.BOX_LUNCH: 0.10, } return self.food_cost * multiplier.get(self.service_style, 0.18) @property def total(self) -> float: return round(self.food_cost + self.service_fee, 2) def volume_discount(self) -> float: if self.guest_count >= 200: return 0.15 elif self.guest_count >= 100: return 0.10 elif self.guest_count >= 50: return 0.05 return 0.0 @property def final_total(self) -> float: discount = self.volume_discount() return round(self.total * (1 - discount), 2) ``` ## Building the Catering Agent Tools ```python from agents import Agent, function_tool packages = [ CateringPackage("PKG1", "Corporate Lunch", "Professional lunch service", 28.00, ["Mixed greens salad", "Choice of 2 mains", "Seasonal sides", "Dessert", "Coffee and tea"], ServiceStyle.BUFFET, min_guests=20), CateringPackage("PKG2", "Elegant Dinner", "Full-service plated dinner", 65.00, ["Amuse-bouche", "Soup or salad course", "Choice of 3 mains", "Sides", "Dessert trio", "Wine service"], ServiceStyle.PLATED, min_guests=30), CateringPackage("PKG3", "Cocktail Reception", "Passed hors d'oeuvres", 42.00, ["6 passed appetizers", "2 stationary displays", "Bar service for 3 hours"], ServiceStyle.COCKTAIL, min_guests=40), ] current_quote = CateringQuote( event_name="", event_date=date.today(), guest_count=0, service_style=ServiceStyle.BUFFET ) @function_tool def browse_packages(service_style: str = "") -> str: filtered = packages if service_style: filtered = [p for p in packages if service_style.lower() in p.service_style.value] lines = [] for pkg in filtered: includes = ", ".join(pkg.includes) lines.append( f"**{pkg.name}** (${pkg.price_per_person:.2f}/person, " f"min {pkg.min_guests} guests)\n" f" Style: {pkg.service_style.value} | Includes: {includes}" ) return "\n\n".join(lines) if lines else "No packages match that criteria." @function_tool def set_event_details( event_name: str, event_date: str, guest_count: int, service_style: str ) -> str: current_quote.event_name = event_name current_quote.event_date = date.fromisoformat(event_date) current_quote.guest_count = guest_count style_map = {s.value: s for s in ServiceStyle} current_quote.service_style = style_map.get(service_style, ServiceStyle.BUFFET) return ( f"Event details set: {event_name} on {event_date}, " f"{guest_count} guests, {service_style} service." ) @function_tool def select_package(package_id: str) -> str: pkg = next((p for p in packages if p.package_id == package_id), None) if not pkg: return f"Package {package_id} not found." if current_quote.guest_count str: current_quote.dietary_requirements = requirements summary = ", ".join(f"{k}: {v} guests" for k, v in requirements.items()) return f"Dietary requirements recorded: {summary}" @function_tool def generate_quote() -> str: if not current_quote.event_name or current_quote.guest_count == 0: return "Please set event details before generating a quote." discount = current_quote.volume_discount() discount_line = f" Volume discount ({int(discount*100)}%): -${(current_quote.total * discount):.2f}\n" if discount > 0 else "" return ( f"=== CATERING QUOTE ===\n" f"Event: {current_quote.event_name}\n" f"Date: {current_quote.event_date.isoformat()}\n" f"Guests: {current_quote.guest_count}\n" f"Style: {current_quote.service_style.value}\n" f"---\n" f" Food: ${current_quote.food_cost:.2f}\n" f" Service fee: ${current_quote.service_fee:.2f}\n" f" Subtotal: ${current_quote.total:.2f}\n" f"{discount_line}" f" TOTAL: ${current_quote.final_total:.2f}" ) catering_agent = Agent( name="Catering Coordinator", instructions="""You are a catering coordinator agent. Help clients plan their events by understanding their needs, recommending appropriate packages or custom menus, collecting dietary requirements, and generating detailed quotes. Always ask about dietary needs and allergies. Mention volume discounts for groups of 50 or more.""", tools=[browse_packages, set_event_details, select_package, set_dietary_requirements, generate_quote], ) ``` ## FAQ ### How does the agent handle partial dietary information like "a few vegetarians"? The agent proactively asks for specific counts rather than accepting vague numbers. It explains that accurate dietary counts ensure proper food quantities — too few vegetarian meals leaves guests without options, while too many creates waste. If the client does not have exact numbers yet, the agent records an estimate and flags the quote as preliminary. ```mermaid flowchart LR CALLER(["Guest or Prospect"]) subgraph TEL["Telephony"] SIP["Twilio SIP and PSTN"] end subgraph BRAIN["Hotel Concierge AI Agent"] STT["Streaming STT Deepgram or Whisper"] NLU{"Intent and Entity Extraction"} TOOLS["Tool Calls"] TTS["Streaming TTS ElevenLabs or Rime"] end subgraph DATA["Live Data Plane"] CRM[("CRM and Notes")] CAL[("Calendar and Schedule")] KB[("Knowledge Base and Policies")] end subgraph OUT["Outcomes"] O1(["Reservation confirmed"]) O2(["Room service order"]) O3(["Front desk handoff"]) end CALLER --> SIP --> STT --> NLU NLU -->|Lookup| TOOLS TOOLS CRM TOOLS CAL TOOLS KB NLU --> TTS --> SIP --> CALLER NLU -->|Resolved| O1 NLU -->|Schedule| O2 NLU -->|Escalate| O3 style CALLER fill:#f1f5f9,stroke:#64748b,color:#0f172a style NLU fill:#4f46e5,stroke:#4338ca,color:#fff style O1 fill:#059669,stroke:#047857,color:#fff style O2 fill:#0ea5e9,stroke:#0369a1,color:#fff style O3 fill:#f59e0b,stroke:#d97706,color:#1f2937 ``` ### Can the agent handle multi-day events or conferences? Yes. The event model can be extended with a `days` field and per-day menu selections. The agent walks the client through each day's meals separately (breakfast, lunch, dinner, breaks), applies the pricing per day, and rolls up the total across the entire event. Volume discounts are calculated based on the highest single-day headcount. ### How does pricing work for custom menus vs. packages? Packages offer a fixed per-person rate that is typically 10 to 15 percent cheaper than ordering the same items individually. The agent explains this tradeoff: packages are simpler and more affordable, while custom menus allow precise control over every course. When clients want to modify a package (swap a dessert, add an appetizer), the agent calculates the difference as an add-on to the package price. --- #CateringAI #EventPlanning #AgenticAI #Hospitality #Python #LearnAI #AIEngineering --- Source: https://callsphere.ai/blog/ai-agent-catering-coordination-menu-selection-event-planning