Build Production-Grade Automation For Your Hotel

Hotels often start with point-and-click tools to connect their booking engine to a PMS. This works for simple notifications. But when a workflow must confirm payment in Stripe, check loyalty status in the PMS, and then send a custom welcome text via Twilio, it becomes fragile. Each step is a separate task, and the per-task pricing model becomes expensive.

A 40-room hotel used a popular automation platform to sync their channel manager with their PMS. The 4-step workflow (New Booking -> Find Guest -> Update PMS -> Confirm) ran for every new reservation, about 25 per day. This resulted in 100 tasks daily, hitting a 3,000 task/month limit and forcing an upgrade to a $350/month plan. More importantly, if the PMS API call failed due to a network blip, the task would just error out. The front desk would only discover the missing reservation when the guest checked in.

These platforms are fundamentally stateless. They cannot easily manage complex logic like "try updating the PMS three times over 5 minutes, and if it still fails, email the front desk manager and add the guest to a manual review list." They lack persistent storage and custom retry logic, which are requirements for any process that handles revenue-critical data like hotel bookings.

Syntora would start by auditing your existing hotel automation workflows and systems. This discovery phase helps us map every required API endpoint, from your Property Management System (PMS) like Cloudbeds or Mews, to your communication tools such as Twilio or Postmark.

We would use the httpx library in Python to build asynchronous clients for each service. This design allows the system to make multiple API calls concurrently, for example, verifying a payment with Stripe while simultaneously checking room availability.

The core logic would be built as a FastAPI service. For guest communication, we have experience using the Claude API in similar document processing pipelines (for financial documents) and the same pattern applies here. We would integrate it to draft personalized pre-arrival messages or answer common questions based on booking details.

Every transaction, successful or failed, would be written to a structured log in a Supabase Postgres database using structlog. This provides a complete audit trail, offering more detail than the simple run history in no-code tools. A typical engagement for a standard booking confirmation workflow would involve a build cycle of approximately 4-6 weeks, following initial discovery.

The FastAPI application would be deployed as a serverless function on AWS Lambda. This architecture is designed for cost efficiency, often running for less than $30 per month for many hotel operations, compared to typical SaaS automation platform fees. We would configure CloudWatch alerts to send a Slack message to your operations team if the error rate exceeds 1% over a 5-minute window, ensuring immediate visibility into any issues.