An AI concierge that handles restaurant and nightclub bookings over WhatsApp and voice: it checks availability, makes the booking and recommends venues through MCP server tools.
Guests of a luxury concierge expect instant, personal answers on the channels they already use, at any hour. Staff were answering the same availability, booking and recommendation requests on WhatsApp and the phone, and a website chatbot would never reach guests where they actually message.
Built the concierge agent in PydanticAI on GLM models from Z.ai. It understands the request, extracts the booking details and manages the conversation.
Connected WhatsApp through the WATI WhatsApp Business API, and phone calls through RetellAI voice agents.
Exposed availability, bookings, venue information, guest preferences and notifications to the agent as MCP server tools.
Grounded answers about menus, venues, FAQs and policies in a RAG knowledge base, with conversation memory for context and preferences.
Confirms each booking and sends the details back to the guest on WhatsApp.
Built evaluation sets of guest conversations covering availability checks, new bookings, changes and cancellations, and recommendation requests.
Ran the evaluations after every iteration and against production conversations.
Traced every agent run and tool call in Logfire.
Concierge agent
WhatsApp channel through WATI
Voice channel through RetellAI
MCP tools for availability, bookings, venues, preferences and notifications
RAG knowledge base and conversation memory
Evaluation sets and Logfire tracing
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We can scope and build a system with comparable capabilities, shaped around your own workflows, data and integrations.
