Build a Custom AI Concierge for Your Resort

Many resorts adopt off-the-shelf guest messaging platforms like Medallia Zingle or chatbots included with their PMS. These tools are effective for simple, one-shot questions like "What time does the pool close?". They fail when a guest makes a complex, multi-part request that reflects a real vacation experience. The underlying technology relies on simple keyword matching, not a true understanding of conversational context.

Consider a guest at a 50-employee resort who texts: "Can you book a table for two at that little Italian place you recommended yesterday, around 8 PM, and also check if they have gluten-free pasta? And can we get a car service for 7:45 PM?" An off-the-shelf bot cannot handle this. It lacks the memory of "yesterday's recommendation," cannot query a third-party restaurant for dietary options, and cannot coordinate a separate car booking. The request is immediately escalated to a human, defeating the purpose of the automation and creating a disjointed guest experience.

The structural problem is that these products are built for horizontal scale, not vertical depth. Their data model is fixed to serve thousands of hotels generically. They cannot ingest your resort's curated list of local partners, understand the nuances of your spa packages, or query your PMS for a guest's loyalty status to offer a personalized perk. To achieve a unique guest experience, the AI must be custom-built around your specific operational data and brand identity.

The first step would be a workflow audit. Syntora would map every type of guest request, from simple FAQs to complex, multi-part bookings. We would analyze your PMS API documentation, whether it's the Oracle Hospitality Integration Platform or a smaller system like Cloudbeds, to understand exactly what guest and reservation data is accessible. You would receive a scope document detailing the request types the AI can handle and the required integration points.

The core system would be a FastAPI service running on AWS Lambda, ensuring it costs nothing when idle and scales instantly during peak season, typically under $50 per month. Guest messages are passed to the Claude API for advanced intent recognition and entity extraction. Claude's large context window is ideal for maintaining conversational memory. For external bookings, Python scripts using the `httpx` library would interact with partner APIs or perform structured data queries.

The delivered system integrates with your existing guest communication channel, such as SMS via Twilio or a web chat widget. When a request requires human intervention, the AI flags it and routes a complete summary to the front desk, so your staff has full context. You receive the full Python source code, a Postman collection for API testing, and a runbook for maintenance. The average response time for most queries would be under 2 seconds.