Case Study
Supporting Hospitality Operations with Voice AI

About Client

Our client is a large, independently operated hotel located in Orlando, Florida, one of the most competitive hospitality markets in the country. With over 700 rooms, multiple dining venues, a full-service spa, and extensive meeting facilities, the hotel serves a mix of leisure travelers, families, and business guests year-round.

Known for its dependable service and strong local reputation, the hotel handles a high volume of guest interactions every day. The front desk and reservations teams are often the first point of contact, managing everything from booking inquiries to amenity requests and last-minute changes. As guest expectations continued to rise, the leadership team recognized a growing need to improve responsiveness across channels without adding more pressure to their staff.

They began exploring ways to streamline communication and deliver faster, more consistent support, while preserving the level of service guests had come to expect.

Challenges

Key Challenges:

  • High call volume during peak times, leading to long wait times and missed calls
  • Staff stretched thin managing both in-person guests and phone inquiries
  • Repetitive questions and simple requests consuming valuable staff bandwidth
  • Lack of after-hours coverage resulting in delayed responses or unresolved needs
  • Inconsistent follow-up due to limited logging of phone-based interactions

Background

As occupancy levels climbed and guest expectations grew, the hotel’s team faced increasing pressure to keep up with a steady flow of requests across multiple channels. Phone lines were often tied up, especially during check-in and check-out hours, and staff were constantly switching between in-person service and responding to routine questions or simple booking changes.

Many of the incoming calls involved predictable topics like restaurant hours, wake-up calls, parking details, or spa reservations. While important to guest satisfaction, these requests were eating into valuable time that staff could have spent creating more meaningful in-person interactions.

After-hours support was another growing concern. Guests arriving late or calling with questions outside of business hours were often sent to voicemail or faced long wait times. Leadership began to notice missed opportunities to capture and act on guest intent in real time.

The hotel set a clear goal: improve responsiveness and consistency in guest communications, while freeing staff to focus on high-impact, face-to-face service. They were not looking for a replacement for human interaction, but rather a way to extend the front desk’s capacity and maintain the level of service that had built their reputation.

Goals:

  • Reduce staff workload on repetitive, low-complexity tasks
  • Provide 24/7 support for common guest requests and questions
  • Ensure faster, more consistent responses across all touchpoints
  • Free up human staff to focus on personalized, in-person service
  • Capture and act on guest intent in real time, without delays.

That’s where we came in.

Solution

The hotel needed a way to handle more guest requests without overwhelming their team, especially during busy check-in windows and late-night hours. So we introduced a Voice AI Agent built just for their hotel, designed to take care of routine questions and simple requests quickly and reliably.

This wasn’t a basic phone tree or chatbot. It was a voice-first, conversational system capable of handling real-time guest interactions across a variety of scenarios, naturally and reliably.

The goal was to create an AI assistant that felt like an extension of the hotel’s front desk. It could respond instantly to inbound calls, manage routine requests, and escalate to staff only when human involvement was truly needed. By taking over the first layer of communication, the Voice AI Agent allowed staff to focus on what they do best: connecting with guests in person.

What the Voice AI Agent was designed to handle:

  • Answer incoming calls 24/7, including during late-night and high-traffic hours
  • Provide quick, accurate answers to common questions (e.g. check-out time, dining hours, parking info)
  • Take guest requests for wake-up calls, housekeeping, room service, and amenity bookings
  • Book spa or restaurant reservations directly into the hotel’s system
  • Route urgent or sensitive issues (billing problems, emergencies) directly to on-site staff
  • Log every interaction with full context into the property’s PMS system.

Behind the Implementation

1. Trained Around Real Guest Behavior
Hospitality isn’t just about answering questions — it’s about understanding what guests need and when. We worked closely with the hotel’s front desk and reservations staff to map out common scenarios: from booking spa appointments to asking about late checkouts. The AI was trained on real call patterns and service flows, so it could step in naturally and handle each interaction with the right timing and tone.

2. Smart Escalation That Respected Staff Workload
Not every call needed a human, and not every human was always available. We built in escalation rules that looked at urgency, request type, and time of day. If a guest was asking about billing or if frustration was detected in their voice, the AI handed things off right away. But if it was a simple “what time does breakfast start?” the agent handled it on the spot. That way, staff only got pulled in when they were really needed.

3. Designed for Voice, Not Adapted from Text
Phone calls are messy. Guests change their minds mid-sentence, pause, or ask three questions at once. We built the AI to handle all of that — not by following scripts, but by listening and responding like a real team member would. Every interaction was optimized for clarity, pacing, and natural flow, no matter how the conversation unfolded.

4. Consistent Service, Day or Night
Whether someone called at 3 PM or 3 AM, the experience stayed consistent. The AI didn’t rely on staff availability or shift changes — it was always ready with the same friendly, reliable service. That consistency helped build trust, especially for guests who were new to the property or arriving late.

5. Tied Directly Into Guest Systems
The AI didn’t operate in a vacuum. We connected it to the hotel’s booking tools, calendar, and guest services platform so it could schedule, log, and update in real time. Every request, from a wake-up call to a dinner reservation, showed up where staff needed it, with zero follow-up required.

By offloading repetitive and time-consuming tasks to the Voice AI Agent, the hotel’s staff could finally refocus on connecting with guests face-to-face. Instead of being stuck behind the phone answering routine questions, team members were available to greet arrivals, handle unique requests, and create moments of genuine hospitality. The result was more meaningful interactions, more satisfied guests, and a team that had the time and space to make a lasting impression.

Support

Results

The Voice AI Agent quickly became a valuable part of the hotel’s day-to-day operations. It handled a large portion of incoming calls, especially during busy hours and overnight, making sure guest questions and requests were taken care of right away.

With fewer distractions, staff had more time to focus on helping guests in person, solving unique problems, and creating the kind of experience people remember. Instead of juggling phone calls and basic tasks, the team could be fully present with guests and deliver the personal, high-touch service the hotel is known for.

Behind the scenes, things ran more smoothly, too. Requests were logged automatically, nothing slipped through the cracks, and teams stayed on the same page. The hotel was able to stay responsive and consistent, even as guest demand grew, all without needing to add more staff.

Results
highlights

  • 4.5x more guest requests resolved outside of business hours
  • Over 60% of incoming calls fully handled by AI
  • 91% guest satisfaction on AI-handled interactions (based on post-call feedback)
  • 100% of AI-handled conversations logged to the hotel’s property management system

Project Overview