Avaneo Hotels Case Study: AI Front Desk with Una

A hotel can have a highly digital guest journey and still depend on its Front Office team for dozens of repetitive interactions every day.

A guest calls to check availability. Another wants to compare room categories. A corporate booker needs five rooms under specific rate conditions. Someone arriving late needs check-in instructions. And between those requests, the phone keeps ringing.

At Avaneo Hotel Marktredwitz in Germany, the challenge wasn't a lack of technology. It was the amount of human attention still required to connect guest questions, reservation systems, booking decisions, and everyday hotel operations.

In June 2026, Avaneo began implementing Una by Polydom as a digital Front Office employee.

The goal was practical: let AI handle routine guest communication and supported reservation workflows so the hotel team could concentrate on situations where personal attention and human judgment matter most.

Within the first weeks, Avaneo began seeing how that approach could work in real guest conversations.

As Avaneo's Director, Alexander Herold, put it:

"For our Front Office, Una is an enormous relief."

The Challenge: A Digital Hotel Still Has a Human Workload

Avaneo Hotel Marktredwitz already operated with a digitally enabled guest journey. Its challenge was not to replace outdated procedures with a completely new system.

It was to reduce the repetitive work that continued to fall on employees despite the technology already in place.

Guest communication rarely follows a perfectly structured process.

One caller may ask about parking, breakfast, room categories, and cancellation conditions before making a booking. A corporate traveler may have fixed arrival dates and company-specific rates. A guest arriving outside reception hours may need help navigating the hotel's self-service check-in process.

Individually, these requests are manageable. Collectively, they can interrupt the Front Office throughout the day and require coverage beyond regular staffing hours.

Avaneo needed a solution that could do more than respond to frequently asked questions.

It needed an AI employee that could understand guest requests, use relevant hotel information, support actual booking decisions, and recognize when a person should take over.

That distinction shaped the implementation from the beginning.

Building Una Around How Avaneo Actually Operates

Rather than introducing a generic hotel chatbot, Polydom configured Una around Avaneo's existing operating procedures.

The implementation began with consolidating and reviewing the hotel's knowledge sources. German and English were established as the primary guest languages, while additional language support remained available.

Email-handling rules were also configured to distinguish genuine guest inquiries from automated system notifications, reducing unnecessary responses.

A particularly important part of the deployment involved Avaneo's Apaleo environment and corporate reservation procedures.

Corporate bookings were not treated as ordinary leisure reservations.

Una was configured to recognize the corporate booking context, work with the relevant rate logic, and support the conditions associated with different reservation types.

Payment and guarantee requirements were also considered within the booking workflows. Depending on the applicable rate and corporate agreement, a reservation might require a card guarantee, prepayment, or another authorized arrangement.

This matters because a hotel reservation is rarely just a question of whether a room is available.

A correct booking journey depends on the rate, dates, occupancy, guest requirements, payment conditions, and the rules under which the property operates.

Una's role was to help carry these conversations forward without requiring Front Office employees to reconstruct every request manually.

A Guest Asked for Five Rooms. Then Added Breakfast.

One of the clearest examples from Avaneo's early operations involved a guest who wanted five single rooms for four nights.

Una checked availability and presented Premium and Deluxe options, including flexible and non-refundable rates.

The guest then added another requirement: breakfast for all five people.

Instead of restarting the conversation or sending the guest to reception, Una calculated the breakfast supplement across the four-night stay and presented updated totals for the available options.

This was a relatively ordinary reservation inquiry. That is precisely why it matters.

Hotels receive requests like this every day. Guests compare several variables before they make a purchasing decision, and the information they need often changes during the conversation.

An automated answer stating that breakfast is available would have addressed only part of the request.

Una helped the guest compare the actual booking options with the additional requirement included.

The operational benefit is straightforward: a routine but detailed sales conversation can progress without demanding the immediate attention of a Front Office employee.

And from the guest's perspective, the experience remains conversational rather than turning into a sequence of disconnected searches.

From a Phone Inquiry to a Direct Booking Link

The same principle applies to incoming calls.

A guest calling Avaneo can ask about availability, provide travel dates, compare room categories, and discuss the conditions associated with available rates.

When a suitable option is selected, Una can guide the guest toward the relevant booking path and send a link through supported messaging channels.

In one actual evening interaction, a guest asked for a Premium Double Room for two people.

Una checked available rates, explained the options, confirmed the selected room, and sent the booking link through SMS and WhatsApp during the same conversation.

Another caller wanted the least expensive available room.

Una identified the lowest-priced option and provided the corresponding booking link. When the guest was unsure what had been sent, Una explained where to find it and how to proceed.

These examples illustrate two different aspects of operational value.

First, Una can support a direct booking journey while the guest's purchase intent is still active.

Second, the interaction can continue through the small follow-up questions that frequently require a human employee to intervene.

Sending a booking link is not the same as confirming a completed reservation, and these examples should not be counted as incremental booking revenue without transaction data.

But they demonstrate how Avaneo can move an inquiry closer to a transaction without automatically transferring every booking-related call to reception.

Corporate Reservations Needed Their Own Logic

One of Avaneo's most important implementation lessons concerned corporate travelers.

A leisure guest looking for a weekend stay may be willing to consider different dates if the requested room is unavailable.

A business traveler attending a meeting on a specific day usually cannot.

During live operation, Avaneo identified cases where suggesting alternative dates did not make sense for corporate inquiries.

The workflow was adjusted accordingly.

When suitable availability could not be found for a corporate request, Una could escalate the inquiry to the Front Office rather than continue offering alternatives that failed to address the traveler's actual need.

This example highlights something essential about introducing AI into hospitality operations.

Effective automation does not mean forcing every request through the same process.

It means recognizing when a standard workflow applies, when operating rules need to differ, and when a human colleague should make the next decision.

At Avaneo, operational feedback helped refine those boundaries after launch.

The Calls the Front Office No Longer Needs to Answer

Not every incoming call represents a complex service situation.

Many guests simply need reliable information about:

Check-in and check-out times
Reception hours and late arrival procedures
Parking and electric vehicle charging
Breakfast availability and pricing
Room categories and amenities
Payment and cancellation conditions
Pets, transportation, and other practical details

At Avaneo, Una can respond to these routine inquiries using the hotel's configured information and instructions.

A guest arriving late can receive guidance about the self-service check-in process. A caller asking about parking can obtain the relevant information without interrupting an employee. A prospective guest can compare available room options before deciding whether to book.

The individual interactions may be brief, but their cumulative effect on Front Office workload can be substantial.

A phone call interrupts the work already in progress. An employee must answer, understand the question, find the information, respond, and return to the previous task.

When similar inquiries arrive throughout the day, the operational challenge is not simply the duration of the calls. It is the constant fragmentation of employee attention.

By handling supported routine requests, Una gives Avaneo's Front Office a different way to allocate that attention.

Alexander Herold described the benefit clearly:

"Our team can therefore focus its time and attention on the cases where human involvement genuinely adds value."

Avaneo's testimonial establishes the team's experience of reduced routine workload. It does not, by itself, establish a quantified reduction in labor hours or payroll costs.

That distinction matters, but it does not make the operational benefit any less relevant.

For hotels, freeing employees from repetitive interruptions can be valuable even before the outcome is expressed as a financial metric.

Real Guests Don't Follow a Perfect Script

Some of the most useful lessons from Avaneo's deployment came from conversations that did not proceed as expected.

Guests changed requirements, corrected details, switched languages, or requested human assistance midway through an interaction.

In one call, a guest initially requested two rooms and then explained that five family members needed to be accommodated. When the requested occupancy required a different arrangement, the guest chose to speak with hotel staff.

In another conversation, a caller moved between German and English before requesting assistance from an employee.

A different caller repeatedly asked for "Rezeption" until Una confirmed the request and transferred the call.

These are not polished demonstration scenarios.

They reflect the uncertainty, incomplete information, and changing expectations that Front Office employees encounter every day.

They also demonstrate why escalation is a necessary part of practical AI deployment.

If a guest wants a person, or if the situation falls outside the configured workflow, successful automation may mean transferring the conversation rather than continuing to answer.

At Avaneo, Una's purpose is not to prevent human involvement.

It is to make that involvement more selective and useful.

A Corporate Customer Chose Una for Future Bookings

One of the most interesting results emerged from the guest side of the experience.

According to Avaneo's feedback, one of its corporate clients was so satisfied with Una's booking widget and the overall reservation experience that the company decided to use the widget for its future bookings.

For the hotel, this was an important signal.

The AI-assisted experience was not simply reducing internal workload. A real customer had found it convenient enough to choose it as a preferred booking channel.

This is customer-reported evidence of booking-channel preference, not a measured increase in direct booking revenue.

Still, the implication is commercially meaningful.

Corporate reservations can involve repeated stays, specific rate arrangements, multiple travelers, and recurring booking requirements.

When the booking experience is easy to understand and use, there is a practical reason for a corporate customer to return to that channel.

The lesson extends beyond the widget itself.

Guests do not choose a booking method because of the technology behind it. They choose it because it helps them accomplish what they came to do.

For Avaneo, Una demonstrated the potential to improve that experience while simultaneously supporting the Front Office.

One Guest Journey, Multiple Communication Channels

The Avaneo implementation also illustrates why guest communication cannot be treated as a collection of unrelated channels.

A guest might discover the hotel online, ask a question through its website, call to clarify room options, receive a booking link through SMS, and then complete the reservation through the hotel's booking infrastructure.

From the guest's perspective, these interactions are all part of one decision.

From the hotel's perspective, they may involve different systems and operational rules.

Una supports that journey by providing a conversational layer connected to the relevant hotel information and eligible actions.

At Avaneo, the implementation covers guest-facing workflows across phone, website interactions, and configured email handling, alongside reservation support through Apaleo.

The supported workflows include room availability inquiries, rate comparisons, corporate booking assistance, multi-room requests, booking links, payment and guarantee information, booking extras, pre-arrival questions, and operational guidance.

The exact actions available depend on the relevant integration, permissions, and property configuration.

The value is not the number of individual features.

It is the ability to support a guest's next step without treating every new question as a separate task for reception.

What Changed for Avaneo's Front Office?

After several weeks of live operation, Avaneo described its experience with Una positively and highlighted both the range of supported workflows and the responsiveness of the implementation process.

The hotel team also identified situations that required refinement, particularly around corporate booking conditions and human escalation.

That feedback became part of the operating model.

This is important because deploying AI into a live hotel is not a one-time configuration exercise.

Real conversations reveal exceptions that scripted tests may miss.

Operational rules need to be validated against the way guests actually behave, and the boundaries between automated handling and human responsibility must remain clear.

For Avaneo, the outcome can be understood in three connected ways.

Routine guest inquiries require less direct employee involvement. Una can handle supported questions about rooms, rates, hotel policies, and arrival procedures.

Booking conversations can progress further before a human handoff becomes necessary. Guests can compare options, add requirements, and receive appropriate booking links within the interaction.

The Front Office retains responsibility for situations that need judgment. Complex corporate requests, exceptions, and guests who prefer personal assistance can still reach the team.

These are operational changes supported by Avaneo's reported experience and real conversation examples.

The published case does not provide a controlled before-and-after measurement of labor hours, conversion rates, or incremental revenue. Those outcomes should be measured separately rather than assumed.

The Real Result: More Time for Human Hospitality

Hotels do not become better at hospitality simply by automating more conversations.

They become better when routine work is handled reliably and employees have more capacity for the interactions where their experience makes a difference.

At Avaneo, the strongest evidence of Una's role is not a headline automation percentage.

It is the combination of real booking conversations, refined operational workflows, positive guest feedback, and the Front Office director's assessment of the relief Una provides.

A guest who needs breakfast pricing can receive it without waiting for reception.

A corporate booker can follow a reservation path that reflects the hotel's commercial rules.

A traveler who wants a human colleague can be transferred rather than forced through an automated conversation.

And a Front Office employee can spend more attention on guests and situations that need personal service.

That is what makes Avaneo's experience relevant to other independent hotels and hotel groups considering AI.

The goal is not to introduce another system that employees must constantly operate.

It is to give the team practical support with the everyday work that already consumes its time.

For Avaneo, Una has become part of that Front Office operating model.

And perhaps that is the most useful measure of an AI Digital Employee: not how many things it claims to automate, but how effectively it helps the people around it do their best work.

See How Una Could Support Your Front Office

If your hotel's Front Office spends much of its day answering repetitive calls, explaining reservation conditions, and helping guests navigate routine requests, Avaneo's experience offers a practical starting point.

Explore Una by Polydom to see how a voice-first AI Digital Employee can support guest communication, eligible booking workflows, and human handoffs within your existing hospitality technology stack.

The next step is to identify which of your Front Office workflows could be handled consistently by AI—and where your team should remain directly involved.