Step into the back office of a hotel, and you’re likely to encounter a somewhat fragmented technological scene.
The front desk operates on one system for check-ins, the housekeeping department uses another software to schedule cleaning tasks, restaurant transactions are recorded in a POS system, and membership data sits in a CRM. These systems often come from different vendors and rarely integrate seamlessly.
For many hotels, digitalization has not led to real efficiency gains; instead, employees spend their days switching back and forth between different software.
As one industry insider jokingly remarked, the problem with hotel digitalization isn’t a “lack of systems,” but rather “too many systems.”
Against this industry backdrop, the hotel technology company Mews, founded in 2012, set out to do something more radical: integrate all core hotel operations into a single and unified platform, transforming the PMS from a standalone management tool into a true operating system for hotels.
Over a decade later, Mews serves more than 15,000 hotels across 85 countries.
Following its recent USD 300 million Series D funding round and a valuation of USD 2.5 billion, Mews is now betting on an even more ambitious direction: reengineering hotel systems as an AI-native platform.
The software dilemma in the hotel industry
The technological structure of the hotel industry is largely shaped by legacy systems.
As Mews CEO Matt Welle told TravelDaily CEO Charlie Li in an interview:
"Many people underestimate the complexity of hotel systems. Truly transforming them requires a deep understanding of hotel operations themselves."
Over the past few decades, hotel systems have evolved by layering on new tools over time: whenever a new operational need arose, a new software was introduced. As a result, a medium-sized hotel may run several to a dozen systems simultaneously—PMS for room management, revenue management software for pricing, operational management software for housekeeping, POS systems for F&B transactions, and banquet systems for event orders.
While each system performs its function, they rarely truly share data.
This means that employees often have to enter the same information repeatedly across systems, and management struggles to gain real-time, holistic insights from scattered data. Even tasks that could be automated still require manual work.
Founder Richard Valtr grew up in a family with a strong hotel background and personally worked on the front lines, including at the front desk. This experience gave him a deep understanding that the software widely used in the hotel industry at the time was largely developed in the 1990s—outdated in technology and inefficient in practice. It was this realization that inspired him to create software better aligned with the real needs of the industry.
When preparing to open their first hotel, they envisioned a property without a front desk—guests would check in, open doors, and pay entirely via their phones.
Reality, however, quickly set in: existing PMS systems were almost all built around traditional front desk models, with many functions requiring fixed computer terminals to operate.
So, they decided to build their own system.
How Mews differs from traditional PMS
Globally, the PMS market has long been dominated by a few established players.
Oracle’s OPERA system is the standard for most large hotel groups worldwide, while in China, local vendors like Shiji have created an alternative technical ecosystem.
These systems have massive client bases but carry historical baggage, with many architectures dating back decades.
Mews chose a different path.
From the start, the company did not adopt traditional PMS structures but designed the platform as a fully unified cloud-based system. Check-in, payments, revenue management, housekeeping, and even event management all operate within the same interface.
For hotel staff, this change is more than just a simplified interface.
More importantly, previously fragmented workflows are now automatically connected. For example, the online check-in system can automatically recognize passport and credit card information; housekeeping tasks update in real time based on room status; and the revenue management system can directly read order data to adjust pricing.
According to Matt Welle, the main limitation of traditional PMS is that they are merely data-entry systems:
"Staff need to input passport information, credit card details, but the system itself does not truly understand hotel operations."
Mews aims to change that. Rather than making employees shuttle data between multiple systems, Mews wants the system itself to understand the entire operation and automatically drive task flows.
AI moves into the hotel back office
With the rise of generative AI, the hotel technology sector is undergoing a new transformation.
In Mews’ vision, AI is not an isolated feature but a capability embedded at the system’s core.
For instance, if the system detects a sudden increase in demand for a room type, the revenue management module can automatically adjust pricing. If a guest makes a request via a chat tool, AI can directly generate a work order and push it to staff.
In this model, the system no longer merely records information—it proactively triggers operational actions.
Building a unified platform through acquisitions
Over the past few years, Mews has expanded its product scope through acquisitions, including revenue management, conversational AI, and hotel POS systems.
Examples include the revenue management software Atomize, the housekeeping management system Flexkeeping, and the generative AI analytics company DataChat. But these acquisitions are not simply product add-ons.
Mews typically redesigns these systems to fully integrate them into a unified architecture. This is the “semantic layer,” a business-friendly abstraction that sits between raw data and end users, translating complex database structures into familiar metrics such as “revenue per available room” or “guest nights sold.”
This layer serves as a critical foundation for AI applications, providing a reliable map of what the data means so that systems can answer business questions accurately rather than relying on guesswork. On top of this, Mews can also deploy an “agentic layer,” where AI agents leverage the semantic layer’s context to perform tasks such as operations, staffing, housekeeping, and revenue management actions.
As a result, communication between different systems no longer relies on complex interfaces—they are natively interoperable.
A simple example: when a guest sends a “need a towel” message via the hotel app or social platform, the system can automatically generate a housekeeping task and push it to staff mobile devices. This automated workflow reduces manual coordination and significantly improves operational efficiency.
Mews’ early clients were mostly independent hotels and B&Bs. For these smaller properties, cloud systems are typically more flexible and easier to deploy than traditional software.
As the product matured, the company began to target larger customer segments, including hostels, campsites, and medium-sized hotel chains.
Today, Mews’ system supports hotels ranging from 20 to 700 rooms. Some large European hotel groups are also adopting the platform; for example, the Nordic group Strawberry Hotels uses Mews to manage hundreds of properties.
This expansion reflects a broader trend: more hotels are reevaluating their technology architecture rather than relying solely on traditional systems.
According to Matt Welle, this shift is irreversible:
"The technology architecture of the hotel industry is undergoing a true rewrite.
"Market expansion and the challenge of China
Initially, Mews focused primarily on Europe. In recent years, growth in the U.S. market has been significant, with the American team expanding from a few dozen employees to 150.
The company has also begun operations in the Asia-Pacific region, currently active in Japan, Australia, and New Zealand, and is considering opening an office in Japan.
The Chinese market, however, is more complex. On one hand, it has a massive hotel base; on the other, local vendors have already established mature technical ecosystems. Data localization requirements, payment systems, and operational habits further raise entry barriers.
As a result, Mews is taking a cautious approach to China, seeking the right partnership model. For a company built around cloud architecture and an open ecosystem, local integration and regulatory compliance represent higher hurdles.
For a long time, PMS was merely a back-office management tool.
But with the development of AI, cloud computing, and data platforms, it is gradually evolving into the core infrastructure of hotel operations.
For next-generation companies like Mews, this is not just a software upgrade—it is a fundamental rewrite of the industry’s operational architecture.
