The Startup Founder Rethinking How Hotels Know Their Guests

Priya Nair spent eight years in hotel operations before founding a guest intelligence platform that now serves over 400 independent hotels across Asia and Europe. Her company sits at the junction of data, AI, and the deeply human question of what it means to be recognised as a guest. We spoke with her about the gap between what hotels know about their guests and what they could know, and why that gap is still so wide.

What problem were you actually trying to solve when you started the company?

I had managed a 180-room boutique hotel in Singapore for three years. We had repeat guests who came four, five times a year. They had preferences, a particular floor, a particular pillow type, a preference for still water over sparkling, a habit of ordering room service at 10pm. None of this information was captured anywhere useful. It lived in the memories of individual staff members. When those staff members left, the knowledge left with them.

The guest arrived, and we essentially met them for the first time again. There's something profoundly disrespectful about that, if you think about it from the guest's perspective. They've trusted you with their time, their money, their travel experience, and you've learned nothing from it.

Why is this still a problem in 2026?

Because the systems don't talk to each other. A guest books through an OTA, and you get a name and a credit card number. They interact with your spa booking system, which is a different vendor. Their restaurant preferences are in a POS that exports nothing. Their loyalty programme is managed by a third party. The data exists, it's just siloed. Most hotels have the information to know their guests well. They just don't have the infrastructure to use it.

What does your platform actually do?

We sit on top of the existing systems. We ingest from the PMS, the POS, the CRS, the spa booking system, the concierge system, whatever exists. We build a unified guest profile that travels with the guest across every interaction. When a returning guest checks in, the front desk agent sees not just their name but a curated brief: their last three stays, their known preferences, any notes from previous interactions, whether they've had any service issues. In sixty seconds, an agent can greet that guest in a way that makes them feel genuinely remembered.

What's the resistance you encounter from hoteliers?

Cost is one. But the deeper resistance is cultural. There are general managers who believe that personalisation is the job of the front desk team, not the technology. And they're not entirely wrong, technology is a tool. But when you have 40 staff members serving 200 guests, you cannot rely on individual memory and intuition alone. The technology extends human capability. It doesn't replace it.

Where do you see this heading?

Predictive service. Not just knowing what a guest has done but anticipating what they want before they ask. We're training models on hundreds of thousands of guest interactions to identify patterns, not just "this guest prefers quiet rooms" but "this guest's satisfaction score correlates with these specific touchpoints and deteriorates when these specific things happen." That allows properties to intervene proactively, before the guest even registers a dissatisfaction. That's the frontier.