Automate Reservation Management for Your Hotel

Modern PMS platforms offer some rule-based automation, but they cannot handle the nuance of real guest communication. A guest doesn't fill out a form to change a booking; they send an email like, "Hi, we need to move our reservation for John Smith from the 14th to the 15th." The front desk staff must read the email, find the reservation, check availability for the new date, calculate the new rate, and then manually update the PMS. This takes 5-10 minutes per request and is prone to human error.

For a 20-room hotel with frequent changes, this manual work creates significant operational drag. Consider a guest wanting to shift a 3-night stay forward one day. The new date range includes a Saturday, which has a higher rate and a 2-night minimum stay policy. Your PMS's basic automation cannot handle this logic. A staff member has to manually check these rules, calculate the price difference, and email the guest for confirmation. If the request comes in overnight, the room may be booked by someone else before the staff can act.

The structural problem is that PMS platforms are databases of record, not conversational workflow engines. Their APIs allow for creating or updating a booking, but they do not provide the logic layer to interpret unstructured requests or navigate multi-step confirmation flows. Off-the-shelf chatbot tools fail here as well because they lack deep, real-time integration with the PMS availability and pricing engine. They can answer questions, but they cannot safely execute a state-changing transaction like a booking modification.

The first step is a technical audit of your existing systems. Syntora would connect to your PMS API and analyze your guest communication channels (e.g., a specific email inbox or SMS number). We would review 100-200 past booking change requests to map out the common patterns, edge cases, and your hotel's specific pricing and availability rules. This discovery phase produces a clear architectural plan before any code is written.

The proposed system would be an AI agent built as a FastAPI service, running on AWS Lambda for efficiency. When a new email or message arrives, the Claude API parses it to extract the guest's intent and key entities like name, dates, and number of guests. The service then queries your PMS API in real-time to check availability, rate changes, and policy constraints (like minimum stays). Pydantic models ensure all data exchanged with the PMS is correctly structured, preventing errors.

The delivered system operates 24/7. For simple changes, it can automatically update the booking and send a confirmation. For complex changes involving a price increase or policy issue, it drafts a response for front-desk approval, including all necessary context. The agent logs every action to a Supabase database, giving you a complete audit trail. The end result is a system that handles over 80% of change requests without human intervention.