[Liberius Technology Co., Ltd.] Overcoming the Hospitality Crisis: Empowering Hotel Staff with \"Hotelwee,\" an AI Partner Preserving Practical Expertise

Executive Board Cleaning Rooms: The Severe Labor Collapse in the Hotel Sector

Hello, everyone. My name is Hiroyuki Nagimitsu, Representative Director of Liberius Technology Co., Ltd. Today, I am excited to present our AI companion platform, \"Hotelwee,\" which supports the daily operations of hotel staff. Thank you.

Before building our platform, we interviewed numerous operators across the hotel sector. What we discovered was a severe crisis: labor shortages are pushing hotels to the brink of collapse. At one major railway-affiliated hotel chain, the shortage of frontline staff was so critical that corporate executives from the headquarters had to visit the property daily to clean guest rooms.

Despite inbound tourism doubling guest inquiries, hotels lack the time to train part-time workers, leading to a turnover rate of 27%—more than double the national average across all industries.

I believe the core issue exhausting frontline hospitality workers lies in three critical gaps:

1. Unable to Train: 45% of the hotel workforce consists of non-regular employees with high turnover. However, experienced staff are too overwhelmed with daily tasks to train new hires. As a result, new staff cannot deliver quality service, creating a vicious cycle of declining hospitality standards.

2. Unable to Share: Hotel operations rely on countless unwritten rules and tacit knowledge—such as drying restaurant trays faster by placing them in alternating directions. Because these tasks are not documented, training is left entirely to individual properties, leading to inconsistent standards.

3. Unable to Monitor: Managers cannot track who is working where in real time. Consequently, a worker's performance (such as cleaning speed and accuracy) goes unrecognized, which dampens morale and drives high turnover.

To bridge these gaps, we developed an AI partner that learns from veteran employees to preserve and share operational knowledge.

AI Learning from Hand-Written Notes: Instant Solutions for Guest Requests

Hotelwee is an AI partner that learns from handwritten notes, photos, and standard procedures of veteran staff to digitize and preserve practical expertise.

With Hotelwee, even inexperienced part-time workers can deliver veteran-quality service by simply following step-by-step instructions delivered on their smartphones.

For example, when a guest scans a room QR code and messages \"the air conditioner is making a strange noise,\" it immediately appears as a task on a staff member's smartphone. By opening the AI assistant, the worker instantly receives troubleshooting steps based on the AC model—such as \"first inspect the filter\" or \"contact the desk to initiate room-change protocols.\" Staff no longer need to dial internal extensions to find someone who knows the solution.

We do not aim to just replace existing software. Our ultimate goal is a fully automated vertical AI agent that minimizes human intervention and limits touchpoints.

As performance data accumulates, the platform will enable objective employee evaluations, predict hotel room demand, and forecast equipment failures (such as predicting when an AC unit needs to be replaced).

25 Years of DX Expertise: Advancing PoCs with Major Railway Hotel Chains

I have spent the last 25 years leading digital transformation (DX) initiatives, specializing in omni-channel systems that merge online and offline operations. Having built hotel inventory systems in the past, I noticed that hotel back-offices have remained unchanged for twenty years. This realization drove me to create Hotelwee.

Hotelwee's infrastructure is built on AWS, integrating the n8n API integration platform and multiple specialized AI agents. While the underlying technology is established, our core advantage lies in our proprietary data annotation, which maps hotel-specific terms and tacit workflows to maximize AI response accuracy.

While existing Property Management Systems (PMS) are complex and require over a week of training for new staff, Hotelwee offers an intuitive mobile UX that connects with PMS to streamline daily workflows instantly.

We are currently in the seed stage. We are negotiating concrete Proof of Concept (PoC) agreements with major railway-affiliated hotel chains, including Seibu Prince Hotels, Odakyu, and Keio Plaza Hotels. We are also seeking independent hotels that can execute quick decisions to initiate PoCs.

Our immediate focus is Japan's 17,000 business and city hotels, aiming to build an infrastructure that supports frontline workers amid the post-pandemic tourism surge. We are raising seed capital and look forward to connecting with investors and hotel partners. Thank you.

Q&A and Feedback

Mr. Ito (Commentator): Thank you, Nagimitsu-san. Your 25 years of DX experience has clearly given you a deep understanding of the practical challenges in hotel operations.

With so many industries needing DX, why focus specifically on hotel back-offices?

Mr. Nagimitsu: According to Cabinet Office data, the food and accommodation sector ranks lowest in productivity and labor growth, dropping even below construction and postal services.

While restaurants are automating via mobile ordering, hotel back-offices have not evolved. In a sector where 45% of the staff are temporary workers, training them on complex PMS platforms is a universal pain point shared by Hilton and Ritz-Carlton. I started this because if we do not solve it, no one will.

Mr. Ito: Providing a mobile UX that bypasses training and replicates veteran performance is highly logical for a temporary workforce.

How do you protect your intellectual property? What prevents competitors from copying your approach of digitizing tacit workflows?

Mr. Nagimitsu: While we use standard tools like AWS and n8n, our proprietary advantage is our domain-specific data annotation. We have built custom datasets mapping hotel terminology and unspoken physical processes to our AI model. The accumulation of this customized data is our primary competitive moat.

Mr. Ito: Being in the seed stage while negotiating PoCs with major railway chains is very promising. Securing your first case studies should be your priority. I wish you the best.

Mr. Nagimitsu: Thank you. We will focus entirely on transforming frontline operations.