Build Custom AI Automation for Your Hospitality Business

Many independent hotels and small chains rely on their Property Management System (PMS) like Cloudbeds or a legacy system like Oracle OPERA for core operations. For guest communication, they might add a generic chatbot like Tidio to their website. These tools are great for their primary purpose—managing rooms and basic web chats—but they do not connect in a meaningful way.

Consider a guest calling the front desk at 10 PM. They want to know the pool hours, book a shuttle for 6 AM, and order breakfast. The night auditor is busy handling a late check-in. The call goes to voicemail. Even with a tool like Tidio on the website, it can only answer pre-programmed questions about pool hours. It cannot access the PMS to book the shuttle or the POS to place a room service order.

The fundamental issue is that these systems are separate data silos. The PMS knows about reservations, the POS knows about food orders, and the website chatbot knows only what you manually program into it. Off-the-shelf chatbot platforms lack the deep integration hooks to perform actions inside a PMS. They can answer a question, but they cannot write data back to the core system to fulfill a request. This architectural gap is why staff still ends up as the human API between disconnected software.

The result is a strained guest experience and an inefficient front desk. Staff spends hours per shift answering the same 10-15 questions and manually transcribing information from one system to another. This increases the risk of human error in bookings and orders, and it pulls your most valuable people away from high-touch hospitality moments that create loyal guests. The problem is not a lack of software, but a lack of connective tissue between the software you already use.

An engagement begins with a workflow audit of your front desk and guest communication channels. Syntora would map the top 20 guest requests by volume and identify which can be automated. We'd analyze your PMS (e.g., Mews, Cloudbeds) and communication tools to document their API capabilities. You would receive a detailed automation plan that prioritizes the highest-impact workflows, like call routing and check-in processing, with a clear technical specification.

The core of the system would be a voice AI agent built on Python and FastAPI, using the Claude API for natural language understanding. When a guest calls, the agent parses the request. For simple queries ('What time is checkout?'), it provides an instant answer. For complex requests ('Can I get a late checkout?'), it queries the PMS API in real-time to check availability and update the reservation. We use AWS Lambda for hosting, ensuring the system handles call volume spikes without performance degradation.

The delivered system is a dedicated phone number or an integration with your existing VoIP system. It operates 24/7, capturing requests and logging them directly into your PMS. You receive the complete Python source code in your own GitHub repository, a runbook for maintenance, and a dashboard to monitor call volume and resolution rates. The system requires no new software for your staff to learn; it works behind the scenes to reduce their manual workload.