Phunware, Inc. Common Stock LD Micro 20th Annual Main Event Conference

All right. Good morning. Thanks for coming. I'm Dmitry. I am the CEO of Phunware, and we want to take you through what we're calling Phunware 2.0, how we are resetting the business and moving forward. These are the customary forward-looking statements. They're available on the investor site, and this presentation is there as well. I'm not going to go through them. You probably know them better than I do. I want to talk a little bit about Phunware 2.0 and why we're calling it 2.0. It's a transition from what we used to do, which was apps and wayfinding, into the future, which is AI forward and intelligence driven. We're going to mainly focus on hospitality, which is the category that provides the lowest hanging fruit, but I'll get into healthcare a little bit as well, where we have several marquee brands that we work with.

The technology translates extremely well into healthcare, and it allows us to leverage all of the investment we've done in wayfinding to date. The other transition that we're doing is, as I said, we're moving out from apps into a core platform with modular components. Previously, we only spoke with spatially complex resorts. That was a fairly narrow SAM because especially not every urban hotel needs wayfinding or mapping. We've updated our positioning and our technology to enable us to expand into a far broader market. What is the problem that we're solving today? In hospitality in particular, you have very disintermediated technology silos, the PMS, the POS, multiple POSs for a spa, for a cabana, for a restaurant, for a poolside bar. These systems don't speak to one another.

Especially now for properties are moving away from an ADR, an average daily rate, into TRevPAR, which is total revenue per available room. It means that they need to connect the dots on all of their ancillary incremental revenue in ways that they haven't before. I think some of the history is important. I'm not going to drone on too long, I promise. If you think about hospitality, you had the old days where you walk into a property, the property says, "Hi, Dmitry, great to have you here." The bellman shows you up to the room, shows you what all the buttons are. Somebody maybe unpacks your luggage. You're met with a glass of champagne. Today, as most of you have experienced, this check-in process is a lot different, and then that relationship that properties used to have with their guests is gone.

Part of why it's gone is online travel agents, evolution, right? We've moved from having this word of mouth and direct relationship into having value and choices. OTAs allow customers, guests to look at 400 properties in Jamaica. It allows for a property to get discovered by consumers. That all works, but that relationship is lost. When you get to the property and you start, whether it's you're in the booking journey or whether you're looking for a place to eat or you're looking for an activity to do when it's raining, all of that's disconnected. The property's no longer really providing that to you. We're connecting those dots, and we are translating them into TRevPAR so that properties can measure what that incremental performance lift is and how much of a share of wallet they're gaining. I'm going to try this remote.

So far, they've had technical challenges. I like to say that if Phunware were running this, we wouldn't have any, but we probably would with Microsoft. That did not land. It's okay, I'm trying. I want to explain what we mean by guest intelligence, what we mean by Phunware 2.0, and I'm going to bring a software example. In software, we moved out of customer service into customer success more than a decade ago. The reason we did that is we figured out that the more that a guest or a customer activates on a product, in the case of a property that's going to the spa, going to the restaurant, going to the golf course, hitting balls with a tennis pro, the more they activate on that property, the better their guest satisfaction is, the more that property is retaining that revenue.

And then what we're doing is we're learning from that, and we're feeding that back into our intelligence so that we can begin to anticipate that guest's needs. We can begin to give them the things that they didn't even know they wanted, collect that revenue, and that loop continues and the knowledge continues. And then operators are going to learn from what we're learning. And because we're not focused so much on the transaction, we're more focused on the engagement. We're able to get a much more direct and natural set of data out of that customer. So one example is we have something called AI Concierge. We launched that officially in January. We have extremely high adoption. Guests are asking questions. We're capturing that information.

So even if the property doesn't know that the guest is into burgers over sushi, we're learning that when they ask us that question, and then we're able to tailor our recommendations based on that. It creates this feedback loop where as we talk to that guest more, as we learn more about their preferences, as we feed that back to the operators, the entire chain of that guest's journey and that entire experience improves. And we capture that revenue, and we share that revenue, and we eventually get into what's called RGI, which is the measure that allows properties to compare themselves to others in their cohort. And we're much more data focused today than when we were doing apps. How does this work in practicality? Man, I don't know if this pointer works. Okay, it doesn't. That's fine. Who needs it? What our intelligence does is it connects a couple of different components.

So there are pieces that you know about your guest when they book that reservation. If they have loyalty information, you're capturing it. If they've stayed on the property before, you probably know whether they prefer a suite to a room, or if they want an ocean view to a city view. You're learning about if they're in a loyalty program, you understand what's passed over there. And then there are the things that the properties aren't seeing that only we see. We're connecting the dots on the POS. We're not crunching those numbers a month later and using them for a marketing campaign. We're using what they're buying, where they're eating, what they're seeing in real time to implement these recommendations. And then we're looking at third-party data.

You're staying in Cancun, it's going to rain tomorrow. That probably puts a damper on what you wanted to do. We're anticipating that, and we're sending you a notification that says, "Tomorrow's a rainy day. Can we redo your itinerary together?" Imagine the work that this would take in a property. We have one property with 3,800 rooms in the Bahamas. Imagine on a rainy day, 2,000 guest rooms going down to the concierge asking, "What are we going to do tomorrow?" We're solving that problem for them. All of this is being fed into intelligent profiles that we recalculate in real time on the fly. The output of that is today we already have distribution in the form of apps. In the absence of apps, modules such as push notification, AI Concierge, Itinerary Planner, that allow us to really directly impact this guest experience.

We can also do things on property, connected digital signage. We can enrich that property's or that operator's CRM, and ultimately push it to an external marketing stack, because if the guest is having a good time, the guest is an avid golfer. What's the sweet spot for most people coming back for vacation to rebook? It's usually that first week. You've come back. In my case, I live in N.Y. When I come back in February from anywhere sunny, I'm miserable automatically. That's the best time to get me to book again. You want me to book again, how do you personalize it? Sometimes the CRMs aren't even catching up to what that guest did on property, especially in that first week. We have the data, and we can push it.

Some of the proof points, and one of the things I mentioned is AI Concierge. We were beta testing in 2025. We rolled out in January of 2026. Out of our app users, we saw about 70% of them interacting with the guest, and we got 40% more interactions than we thought we would get at best. That's contributing to a very high retention rate that we have with all of our customers, and not just in hospitality, also in healthcare. We're able to provide value. They're seeing very good ROI numbers, and so they're staying with us. Then, of course, we have this massive investment that we did historically into wayfinding. That continues to be a big data differentiator.

Now, whether we use that as mapping, meaning how do I get from my room to the Shake Shack 15 minutes away, or whether we're doing it with location-based services, such as you just used your key card to go in the room, so I know that you're on property, or you're connected to the property Wi-Fi. We can use location as a way to say, "Hey, this guest is here." Take what you know about them and make sure that you're recommending a path forward. I'm using Wailea Beach Resort. I was joking earlier that I cannot mention the flag name because in hospitality, people are very circumspect about their brand coming up. Wailea Beach Resort, fairly well known. We've had our app there for a while. We're releasing AI Concierge with them. They've also signed up to be piloting Itinerary Planner.

They see 70% adoption of our app with their guests on property. They are also one of the highest, I believe, actually, they are the highest performing in ancillary revenue, that incremental revenue that is beyond the room, in that flag on the Hawaiian Islands. We were talking about how we compare, and we always need to show you what the competition is doing. I think the thing to take away here is, yes, wayfinding differentiates us, location-based services monetization, meaning, "Hey, I know they are in the room. Now is a good time to hit them up with an offer." Or, "I know that they have been by the spa 12 times. Maybe we should give them a discount so that they convert." Yes, we do that.

I think what this chart doesn't show is that almost all of the AI Concierge and messaging employed today by sort of the competition is very transactional minded. "Hey, send me up a toothbrush. I need room service." None of it is really aware of what that guest wants. None of it is really aware of that guest's preferences. It is a glorified chatbot. There are a couple of apps. Again, I do not know that I can say them out loud, but I can certainly say them when we are not recording that you can download and you can play with our concierge yourself and see that it goes far more than that. You can tell it what you are interested in, it will help you find it. We do not think that there is really anybody that is a direct competitor as much as there are people converging into our space.