AIR DATE:
March 26, 2026
LENGTH:
36:27 minutes
NOAH GLASS:
And I'll say as a founder and CEO of a software company that I've been running for over 20 years, I feel like I have been tapped into the rising Top Gun class. I have Orlando Bravo in the front row, Maverick as my guide.
ORLANDO BRAVO:
Welcome to Thoma Bravo's Behind the Deal. I'm Orlando Bravo, founder and managing partner at Thoma Bravo. For today's episode, we're going back to our 2025 AI summit, where we brought together industry leaders to discuss innovation and the future of technology. What you're about to hear is one of those conversations recorded live at the event. In this session, Thoma Bravo partner, Hudson Smith, sits down with Noah Glass, founder and CEO of Olo, a leading restaurant technology platform serving more than 750 enterprise brands. Together, they discuss how Noah built Olo into a category leader, why the company was so compelling to us, and why Thoma Bravo taking Olo private in September 2025 created a great foundation for its next phase of growth. It's a story of a founder who survived and built his business through multiple technology eras and a conversation about how AI could help power the restaurant of the future.
I'll pass the mic to them.
HUDSON SMITH:
One of my favorite things about working in private equity at Thoma Bravo is working with founders. And what is extremely rare is to find a founder who started a company right out of college and has now scaled it as a growth equity backed company, then as a public company, and now as a private equity company. So very rare. Excited to introduce you all to Noah.
His story's incredible. And coming out of Yale, he moved to Wall Street about 22 years ago, 2003, with a few college friends. And he was frustrated waiting in line for coffee in the morning, right? Everyone coming from Wall Street going to get coffee at 9:00 AM, going into work. He's a very efficient guy, obviously. Pushes very hard. And he said, "Geez, in high school, I worked as a pizza delivery guy and as a cashier." He really understood restaurants and how they do it and said, "Gosh, it'd be a lot better if you could actually order this via text." And he was an early adopter of a PalmPilot. The iPhone wasn't out yet. That wasn't out for, I think, two more years. And so he met some developers while he was in South Africa and got them to build a prototype of a simple text ordering solution. He happened to meet an investor. The investor said, "Hey, if you're willing to quit your job and go at this full-time, I'll give you $500,000 and get going."
And so he launched effectively Olo, it was named something else in the beginning, as this text message ordering business. At a time that was very early, similar to where AI is, it was very early in the transition to mobile phones, with only 5% of the population, I think at the time, having phones. But Noah was early and said, "Hey, I want to get in front of this and people will start using their phones for this."
16 years later, he's a market leader. He took the company public in 2021, right out of COVID, when restaurants were desperate to change their processes and embrace technology. It was growing incredibly rapidly, started off as a public company in that period. And we started tracking Noah in 2022 when the stock market corrected a bit, growth had slowed a little bit post the COVID boom. But he consistently, every two to three quarters we called him and he said he loved being a public company. He loved his board situation, and he wanted to keep going. But we kind of convinced him that, "Hey, there's another way of creating value. In the private markets, you'll have currency to do M&A, which hopefully will get done soon. You can get to much higher margins because what the public markets were focusing on weren't necessarily the right things. And much faster decision making than a public board." So we finally got the Olo deal done, and so that's a little bit of Noah's background.
So before we have Noah come up, wanted to share a quick video of what Olo does, Noah's vision for the company.
NOAH GLASS:
What will the restaurant of the future look like? Perhaps a better question is, what will guests expect in the years ahead? As I look at the landscape today, I know there is so much more work to be done. With every interaction, our restaurant brand customers get one step closer to having a 360 degree view of each guest, including purchase behavior, dietary restrictions, preferred payment method, favorite marketing channel, lifetime value, and more. The service enhancements and guest insights gained by harnessing every transaction have become a key competitive advantage for Olo restaurant brand customers.
So when we imagine the restaurant of the future, an Olo-powered drive-through will immediately identify you by your license plate. A personalized greeting will appear on the screen and ask if you'd like to order the hamburger you got last time or try the chicken tenders, a data-driven recommendation based on the purchase history and dietary preferences of guests just like you. As we think about the dining experience, we imagine a reality where you're escorted to your preferred table, where your favorite wine awaits. And though you've never met this host, she wishes you a happy anniversary.
A server with a handheld ordering device suggests the filet mignon with sautéed mushrooms and without rosemary, based on the past orders, likes, and dislikes in your guest profile. And the wine list has been personally curated based on your preference for Italian reds. And because your payment method is securely saved after dining, you're free to get up and go without waiting for the check. The borderless account tied to your reservation already took care of your payment and tip using your default settings. A follow-up text reminds you that you can adjust your tip within 24 hours. In those moments when making dinner isn't an option, what if you got a perfectly timed push notification from your local pizza restaurant prompting you to place a pickup order for your favorite vegan pizza for $5 off? With just a handful of taps, your order's fired off to the kitchen. Once you park at the curb, a Bluetooth beacon detects that you've arrived. And within two minutes, a runner is at your car with your pizza. The restaurant knows you're in a white Mazda thanks to your saved settings. An automated survey arrives in your inbox two hours later, prompting you to review your experience in exchange for a free dessert with your next order.
Lunch with coworkers is less than perfect when you're waiting for a table, waiting for a menu, waiting to place an order, and managing to take only a few bites before rushing to get back to the office. When you can order and pay at the table, controlling the entire dining experience, that allows lunch to be a little more about lunch rather than the struggle to get it. And when you're ready for dessert, use your phone to scan the QR code on the table and order one of the custom selected suggestions. If you want to split the check or add a coffee to go, we think that should be quick and easy too.
When you want to order in for a group of friends with varying dietary preferences, what if you could share the link to your chosen restaurant with the group, allowing them to order whatever they want and taking you out of the middle? Once the unique link is shared, everyone can place their order. With the guesswork taken out of the equation, checkout is seamless and the food is scheduled to be delivered just on time. When food is on the way, you get real-time information on location and ETA. And after the delivery, you get an optional text survey so you can rate the entire experience.
What if instead of waiting in line, you could simply head straight to a kiosk. As you approach, you're automatically logged into your account using facial recognition that you previously approved. After the instant verification, your order history and favorites pop up, making the order entry process fast and easy. Once you place your order, you get an alert on your phone with your receipt and wait time. After a few minutes, your meal is ready and you're on your way.
Leveraging the ideal blend of Olo products and integrations, restaurant brands of all sizes can build solutions that help both their front and back of house staff operate as productively and profitably as possible, while increasing hospitality, not eroding it. With a growing network of more than 84,000 restaurant locations and 85 million guests.
HUDSON SMITH:
And now, Noah Glass.
NOAH GLASS:
Thanks, man. Yeah, I just wanted to start out with some gratitude. On behalf of all of team Olo, I am so thrilled that we are part of this community and part of the Thoma Bravo portfolio. And I'll say as a founder and CEO of a software company that I've been running for over 20 years, I feel like I have been tapped into the rising Top Gun class. I have Orlando Bravo in the front row, Maverick, as my guide. But really, I mean, I have taken so much from this event. Every interaction that I've had, every session that we've had has been so enlightening to me. And one of the things that I've always felt about our investors is they really are the wind beneath our wings. And I want to extend my gratitude to this group because of course, as investors in Thoma Bravo, you are the wind beneath Thoma Bravo's wings. And I'm just so thrilled to be on this journey that we're on together. So thank you.
HUDSON SMITH:
Awesome. Well, with that, let's jump right in and understand the impact of AI. So the idea for Olo, as we talked about, it was a text ordering system very early in the mobile phone time period. And I guess it's kind of similar to where we are with AI in a way. And I wonder, are we in the text ordering phase of AI and it's going to evolve into that vision over time in the AI world? What are your thoughts on that?
NOAH GLASS:
I think that's right. I like the question of, what inning are we in? I'll answer it, but I'll also say an observation that I'm having being with this group, working with Orlando and the partners and all of you, is that, yeah, every SaaS company is going to have to figure out where we are in AI and how we're going to use AI to either further empower our customers or reach new markets or build new products. But it also feels a little bit like we've been through this movie before. And so it feels a little different now, being at the scale we're at with the maturity we have both as a company, as a management team, as a set of investors, that it's exciting, but it's not scary. It feels like it's an opportunity. It doesn't feel like a threat to the core business we have today.
And as you saw in that video, some of the things that we showed, there are some AI elements at play today in a limited form to help guide the agent experiences that we're trying to deliver. But a lot of it is just thinking ahead to how we integrate that into the core product. So I think it is very much like that early stage when only 5% of consumers had phones and it felt like, "Okay, is this going to be a thing or not? Are consumers really going to start putting things on their phone? Are they really going to trust the phone with payment information?" Now mobile is the primary device for ordering and engaging digitally with restaurants. And I think AI will similarly evolve to be a deeply embedded part of all of these experiences. But I think it's a really early stage just like it was when we got started.
HUDSON SMITH:
Yeah, so you mentioned that the early days of Olo, there was 5% phone penetration. Curious, what was the sales pitch like? Because I would assume that you're selling to restaurant owners who also didn't have phones and weren't necessarily the most tech savvy people, and you're trying to get them to adopt something that's brand new in an industry that's slow to adopt technology. What was that sales pitch like? How did you convince these people to buy your product when only 5% of Americans had phones?
NOAH GLASS:
So it is not an exaggeration to say that 100% of the sales conversations we had in the first—I'll call it two to three years—started with a skeptical restaurant brand saying, "So you're telling me consumers are going to order food on their phone?" That was the sales objection. It was not like, "I don't trust you to build the software," or, "I don't think your software's good." It was fundamentally the premise that the software was built on. They just were like, "I just don't see it." And so we had to do a lot of education. We had to share a lot of data. We had to show them the trajectory of smartphone adoption. We had to make the case that this was the future.
And we actually got a lot of our early adopters not by convincing them that consumers were ready, but by convincing them that they should be first movers, that there was a competitive advantage to being early. And so a lot of the brands that adopted Olo early on, and many of them are still customers 18, 19 years later, they did so because they wanted to be ahead of the curve. They wanted to be the brand that was known for innovation. And so that was really the sales pitch. It was less about "buy this because consumers are demanding it today" and more "buy this because consumers are going to demand it tomorrow and you want to be ready."
HUDSON SMITH:
And so you mentioned that during COVID, which we all experienced—I think everyone in this room probably ordered a lot more food delivery during that time period—there was this massive acceleration of digital ordering. What was that experience like for you building Olo through that? And I'm curious, coming out of COVID, what was the hangover like? Because I would assume a lot of these restaurants that were forced to adopt technology during COVID, maybe they went back to their old ways. What was that experience like?
NOAH GLASS:
Yeah. So COVID was obviously a really challenging time for everyone, including restaurants. And what we saw was this massive acceleration of digital adoption. Restaurants that had been on the fence about whether or not they needed digital ordering suddenly realized, "Oh, this is mission critical. This is how we stay in business." And so we saw a huge surge in demand for our platform. We onboarded more brands in 2020 than we had in any previous year. We saw transaction volumes spike dramatically.
The interesting thing coming out of COVID was, we were worried—and I think rightfully so—that as restaurants reopened and people could go back to dining in person, would they stick with digital ordering or would they revert back to the old ways? And what we've seen is that the habits that were formed during COVID have largely stuck. People got comfortable with the convenience of digital ordering. They got comfortable with curbside pickup. They got comfortable with delivery. And so what we've seen is that while transaction volumes did moderate a bit as we came out of COVID—they didn't maintain that crazy growth rate—they settled at a much higher baseline than where they were pre-COVID.
And so COVID was really an accelerant for the digital transformation of restaurants. It brought forward probably three to five years of adoption in the span of about six months. And that's been a huge tailwind for our business.
HUDSON SMITH:
That's great. So you mentioned delivery. And I want to talk about the competitive landscape a bit. So there's companies like DoorDash, Uber Eats, that offer both the technology platform and the logistics of actually delivering the food. You all just do the technology platform. Why is that a better model? Why shouldn't restaurants just use DoorDash or Uber Eats for everything?
NOAH GLASS:
Yeah, it's a great question. And I think it's important to understand the fundamental difference in the business models. So DoorDash, Uber Eats, Grubhub—these are marketplaces. And in a marketplace model, the marketplace owns the guest relationship. So when you order through DoorDash, you're a DoorDash customer, not a customer of the restaurant. The restaurant is effectively a supplier to DoorDash. And DoorDash takes 20% to 30% of the transaction as their commission.
Now, that can make sense for restaurants in certain contexts. If you're a small restaurant that doesn't have a brand, doesn't have a customer base, being on DoorDash exposes you to millions of consumers who might not otherwise find you. So there's a customer acquisition benefit. But for large enterprise restaurant brands—brands like Chipotle, brands like Wendy's, brands like Five Guys—they already have a brand. They already have customers who know them and want to order from them. And so what Olo enables them to do is facilitate digital ordering through their own channels—their own website, their own app—where they own the guest relationship and they're not paying a 20% to 30% commission.
And so what we've seen is that large restaurant brands have increasingly said, "We want to own our digital presence. We want to own the guest data. We want to own the relationship. And we want to use third-party marketplaces for incremental demand, not as our primary channel." And that's really where Olo fits in. We're the platform that enables them to own their direct digital channel.
And I'll also say, if you think about the analogy to other industries—if you think about hotels, for example—hotels don't want all of their bookings to go through Expedia or Booking.com. They want to drive direct bookings because the economics are so much better. And the same is true for restaurants. The economics of direct digital ordering are dramatically better than going through a third-party marketplace.
HUDSON SMITH:
That makes a lot of sense. So you're basically saying that for large brands with existing customer bases, it makes more sense to own that relationship directly rather than ceding it to a marketplace. And Olo provides the technology to enable that.
NOAH GLASS:
That's exactly right.
HUDSON SMITH:
So I want to shift gears a bit and talk about AI specifically and how you're thinking about integrating AI into the product. What are some of the use cases that you're most excited about?
NOAH GLASS:
Yeah, so there's a few areas where we're really focused. One is in the agent experience—so think about a conversational AI interface where a guest can interact with a restaurant's menu, get recommendations, place an order, all through a natural language conversation. We're starting to see that today in limited form, but I think that's going to become much more prevalent.
The second area is in personalization and recommendation. So using AI to analyze a guest's past order history, their preferences, their dietary restrictions, and proactively suggesting menu items that they're likely to enjoy. And not just at the individual level, but also thinking about cohort-based recommendations—so, "Guests like you who have ordered similar things tend to also like this new item that just launched." That kind of thing.
The third area is in operations and optimization. So using AI to help restaurants better predict demand, optimize their labor scheduling, manage their inventory more effectively. There's a lot of operational complexity in running a restaurant, and AI can help streamline a lot of that.
And then the fourth area—and this is something that we're really excited about—is in fraud prevention and security. As digital ordering has grown, fraud has become a bigger issue. And so we're using AI and machine learning to detect fraudulent transactions in real time and prevent them before they go through.
So those are kind of the four main areas where we're focused. But I think the broader theme is that AI is going to be embedded throughout the entire stack, throughout the entire guest experience, throughout the entire operational workflow for restaurants.
HUDSON SMITH:
Yeah, that makes a lot of sense. And I think one of the things that's interesting about your business is you have this massive data set—85 million guests, 84,000 restaurant locations, billions of transactions flowing through your platform. That's a huge competitive advantage when it comes to training AI models and making these kinds of recommendations. Can you talk a bit about how you're thinking about leveraging that data asset?
NOAH GLASS:
Yeah, absolutely. I mean, the data is really the foundation of everything we're doing with AI. And I think one of the things that's important to understand is that we have both breadth and depth of data. So breadth in the sense that we have data across hundreds of brands, thousands of locations, tens of millions of guests. And depth in the sense that for individual guests, we may have years of transaction history—every item they've ever ordered, every time they've ordered, every location they've ordered from.
And so what that enables us to do is build models that are trained on this massive corpus of data but then can be personalized at the individual guest level. And I think that is a really powerful combination. And it's something that individual restaurant brands, even large ones, can't do on their own because they don't have the scale of data that we have across our entire network.
Now, the flip side of that is we have to be really thoughtful about data privacy and data security and making sure that we're using this data in a way that is respectful of guests' privacy and compliant with all the relevant regulations. And so we've invested a lot in our data governance, in our security practices, in our privacy policies to make sure that we're doing this the right way.
But I think the fundamental insight is that the more data you have, the better your AI models can be. And we're in a really fortunate position of having a truly massive data set that we can leverage to build best-in-class AI capabilities for our restaurant brand customers.
HUDSON SMITH:
That's great. And you mentioned data privacy. I'm curious, one of the questions that we sometimes get when we're evaluating restaurant technology companies is, "Are restaurant brands comfortable with a centralized platform like Olo having all of this data?" Do they worry that you're going to use it to compete with them or share it with their competitors? How do you navigate that?
NOAH GLASS:
Yeah, it's a really important question. And I think the short answer is that our restaurant brand customers trust us because we've been very clear and very consistent about how we use data. So first and foremost, the data belongs to the restaurant brands. It's their data. We're a service provider. We store the data, we process the data on their behalf, but they own it.
Second, we have very strict policies against using one brand's data to benefit another brand. So we're not taking Chipotle's data and using it to help Qdoba, or taking Wendy's data to help Burger King. That would be a huge breach of trust and it would destroy our business.
Now, what we can do—and what our restaurant brands want us to do—is use aggregate, anonymized data to build better products and better models that benefit all of our customers. So for example, if we see that across our entire network, guests are increasingly ordering plant-based items, that's a trend that we can surface to all of our restaurant brand customers so they can think about how to respond to that trend. But we're not sharing individual guest-level data or brand-specific data across brands.
And I think the other thing to understand is that restaurant brands—especially large enterprise brands—are increasingly realizing that they have more to fear from the third-party marketplaces than they do from platforms like Olo. Because the third-party marketplaces actually do own the guest relationship, and they do use that data to compete with restaurants in various ways. Whereas platforms like Olo are aligned with the restaurant brands. Our business model is based on helping them succeed, not competing with them.
And so I think there is a growing recognition that having a centralized, neutral platform that aggregates data in a privacy-preserving way and uses it to build better products for everyone is actually a good thing for the industry.
HUDSON SMITH:
That makes a lot of sense. So you're basically saying that you're acting as a trusted intermediary—you own the technology, you store the data, but you're very careful about how you use it and you're aligned with the success of the restaurant brands.
NOAH GLASS:
That's exactly right. And I would also say that we're increasingly being asked by our restaurant brand customers to do more with data, not less. They're saying, "Can you help us understand our guests better? Can you give us benchmarks against other brands in our category? Can you help us identify trends?" And so we're actually expanding our data and analytics capabilities in response to customer demand.
HUDSON SMITH:
That's great. So I want to ask about one more thing, which is just your operating philosophy. You've been running this company for over 20 years. You've been through multiple technology cycles, multiple business cycles. You've scaled it from a startup to a public company and now a private company again. What are some of the key principles or lessons that have guided you as a founder and CEO?
NOAH GLASS:
Yeah, it's a great question. I think the first thing I would say is just staying very, very close to customers. I mean, that sounds obvious, but I think it's easy as companies scale to lose that connection to the customer. And I've always made it a priority to be in front of customers regularly, to understand what they're dealing with, to understand what their pain points are, to understand where they want us to invest. And I think that customer intimacy has been really foundational to our success.
The second thing I would say is building a great team and a great culture. I mean, software is a people business. And the quality of the people you have, the culture you create, the values you instill—those are the things that enable you to execute over the long term. And so we've invested a lot in recruiting, in retention, in building a culture of excellence and customer focus.
The third thing I would say is being willing to evolve and adapt. I mean, the market that we're in today is very different from the market we were in 20 years ago. The technology has evolved dramatically. The customer needs have evolved. And we've had to evolve our product, our go-to-market, our pricing, our partnerships. And I think being willing to constantly learn and adapt has been critical.
And then the fourth thing I would say is just resilience and persistence. I mean, building a company is hard. There are ups and downs. There are moments of doubt. There are setbacks. And I think having the resilience to push through those moments and stay focused on the long-term vision has been really important.
So those would be the four things I would highlight: customer focus, team and culture, adaptability, and resilience.
HUDSON SMITH:
Those are great lessons. And I think one of the things that stands out about your story is just the longevity—22 years building the same company through multiple technology eras. That's incredibly rare in the software world. Most founders either get pushed out or they burn out or they sell the company. What has kept you motivated and engaged for over two decades?
NOAH GLASS:
You know, I think it's a few things. One is I genuinely love what I do. I love the problem we're solving. I love the customers we serve. I love the team that I get to work with every day. And so it doesn't feel like work in the same way that I imagine it might for someone who's less passionate about what they're doing.
The second thing is, I feel like we're still so early in the journey. I mean, digital ordering in restaurants is still only about 15% to 20% of total transactions. There's so much white space, so much opportunity to continue to grow and innovate. And so it still feels like we're in the early innings, not the late innings.
And then the third thing is, I think being part of the Thoma Bravo portfolio has re-energized me. I mean, having access to the resources, the expertise, the network that Thoma Bravo brings—it feels like we're entering a new chapter. And I'm as excited about the next five years as I was about the first 20. So it's really a combination of passion for the work, belief in the opportunity ahead, and excitement about the partnership we have with Thoma Bravo.
HUDSON SMITH:
That's great. Well, before we open it up to questions, I just want to ask one more thing. You mentioned earlier that you feel like you've been tapped into the Top Gun class and Orlando is Maverick. If you had to give advice to other founders or CEOs in the audience about how to succeed as a private equity-backed company, what would you tell them?
NOAH GLASS:
I think the first thing I would say is, be really thoughtful about choosing the right partner. I mean, not all private equity firms are the same. And I think taking the time to understand their investment philosophy, their operating approach, their track record, their reputation—that's really important. And I feel like we did our homework on Thoma Bravo and we felt really confident that they were the right partner for us.
The second thing I would say is, embrace the partnership. I mean, there's a lot of expertise and resources that a firm like Thoma Bravo brings to the table—whether it's around M&A, or go-to-market, or product strategy, or operational excellence. And I think being open to that input and leveraging those resources is a huge advantage.
And then the third thing I would say is, stay focused on what matters. I mean, it's easy when you go from public to private to feel like, "Oh, now we have some breathing room, we can relax a bit." But I actually think we need to run harder now than ever. We have a huge opportunity in front of us. We have the capital, we have the support, we have the resources to really accelerate our growth. And so my mentality is, let's take full advantage of this moment.
So those would be the three things: choose the right partner, embrace the partnership, and stay relentlessly focused on execution.
HUDSON SMITH:
That's great. Well, I think we're at time for some questions. Let me open it up to the audience.
AUDIENCE MEMBER:
Great. Maybe we'll turn to Slido. "How will AI affect employment in the restaurant industry as Olo has the data points to provide a more efficient experience?"
NOAH GLASS:
I'll give you a great case study, not necessarily in AI, but just in technology and how it's impacting jobs. So this was from our customer conference. I think it was two years ago now. We had Danny Meyer, who was a longtime board member at Olo, founder of Shake Shack. People here probably know him for that and a lot of high end New York restaurants. At Shake Shack, they converted what was a standard three cashier lanes into kiosk lanes. And what they did was—he said, "We did not all of a sudden lower the number of roles we were staffing for by three. What we did was we kept one cashier there and that person would sort of act as a cashier and we'd spin the kiosk around. They would take an order in the traditional way. We had another person who was no longer a cashier. We call them a hospitality helper." He had some name like that. "And they would come out, and if people needed a little bit of help to show them how to use the kiosk, that was their role. And then we did eliminate one of those roles."
So I think that's a good illustration, and I think it's a good anecdote. I don't see this removing humans and the human layer of hospitality in totality from restaurants. What I see it doing is helping the humans in the restaurant really do the human things and deliver hospitality. I think it's much nicer to hand somebody their order and smile and talk about what they ordered and what they might like next time or give them a free sample of something that you know they're going to like because of the massive data set than it is to be taking their order, mis-entering it, making change for them. Those are kind of rote tasks that technology is better at doing, AI included, than humans. And a human should really deliver that human layer of genuine connection with guests.
AUDIENCE MEMBER:
That's great. Why are the POS systems or kitchen systems not able to or not trying to accomplish some of these same goals?
NOAH GLASS:
So POS was really built as a staff-facing technology. It is the ability for the staff to build up an order on behalf of the guest, take payment on behalf of the guest. It is inherently not a guest-centric technology. Digital ordering with its origins in e-commerce, that is an inherently guest-centric technology. And so that's sort of how we think about our role as the guest-facing tech stack versus the point of sale's role as the staff-facing tech stack. Fun fact, we do have, now I know of two brands that are customers of Olo who are emerging brands launching, but they're launching without a traditional POS. They are using Olo full stack and they're connecting in other software services into Olo for things like purchasing and inventory and labor and scheduling, things that aren't inherently guest-facing technologies, not things that we do. I neglected to mention this, but we have a network of 400 technology partners as an open platform and the largest open platform of its kind that plug into Olo.
And a lot of them do that kind of back of house, staff-facing technology sort of thing. Now we have these restaurant brands showing the way that the future will be, I believe, a future that does not involve the POS as we've come to know it. Because if you can use AI to order or use your own interface to order and have accuracy go up and speed go up and convenience in general go up, why would a restaurant insist that you go and speak to somebody to mishear your order, mis-enter your order, and then send it back to the kitchen when you can just skip that hop and go straight from the guest interface directly to the kitchen interface.
HUDSON SMITH:
On your phone interface as well.
NOAH GLASS:
Yep.
AUDIENCE MEMBER:
That's great. Noah, you've lived through many multiple technology hype cycles. Looking out over the next decade, what gives you confidence that the core economics of software—recurring revenue, scalability, and high margins—remain intact even as AI reshapes how products are built and delivered?
NOAH GLASS:
I guess my main confidence comes from the fact that over 20 years of operating the company, we've been so aligned with restaurants and adding so much value to restaurants, and we've seen restaurants—we've experienced brands leaving the platform and trying to build something on their own to replicate what we do. And we love those stories because they all wind up as what we call boomerangs, where they leave and then they come back because they realize it's not just really expensive to build software. It's really expensive to operate software. Yeah. It's not the CapEx, it's the OpEx. When we look at what big, big brands who built before we were even a company and an option for them to consider are spending on this, without exception, it is more than double on a per transaction basis what our platform costs.
And so I think we have such an inherent advantage as a SaaS platform at scale that we can deliver a world-class product at a fraction of the cost, and that has been true for our entire history, and it becomes more and more true as we grow and scale and offer more capabilities to our customers.
AUDIENCE MEMBER:
It already feels like restaurants push you out the door. How do you ensure that this efficiency doesn't affect the experience?
NOAH GLASS:
I think restaurants also have to choose how much of this do they want to do. We've come a little bit into this future, but there are still restaurants that are doing some things like this today. Some fine dining restaurants really don't want it to feel automated or enriched by technology at all, but a big part of the inspiration for some of the experiences you saw there is from studying really fine dining restaurants and one in particular, Eleven Madison Park in New York. So one of the keynote speakers is a guy named Will Guidara, who was one of the owners and the front of the house, maître d' at Eleven Madison Park. And a lot of the things that they did to become the number one restaurant in the world were things that we drew inspiration from in building out this vision. And a lot of the things that Danny Meyer did with keeping track of guests and keeping track of their preferences and remembering them and using technology to remind the hostess stand, the servers who this guest was, what they liked, when they were last in, which restaurant they came to.
All of those were kind of the source material that we then used to go and build out a lot of these capabilities or that have inspired future capabilities. So I think even the finest dining restaurants see attributes of what we're doing that they can apply to augment the hospitality they offer, and not every restaurant is going to put kiosks in. That's appropriate for some restaurants. It's not appropriate for others, just like not every restaurant has a drive-thru. I think there's a lot of different ways to play here, but what is fundamentally true of every restaurant is they want their guests to feel known, to feel seen, to feel like they remember them and are personalized in their experience, and that is their best way for time immemorial to grow guest lifetime value and increase the number of times that a guest comes back to their restaurant. And that's everything that we do in software form.
AUDIENCE MEMBER:
Great. Maybe one last question. Do you find that restaurant chains are concerned that you might empower their competitors with data from people they consider to be their customers?
NOAH GLASS:
I think that there is a span of perspectives on that. But I'll say that this is not happening in a vacuum. There are these marketplaces like DoorDash, like Uber Eats, that are a growing percentage of overall transactions where the restaurant is not only in one place with all of their competitors, but when an order comes in, they don't know who that guest is and they effectively, or their franchisees make no money on the transaction. And an alternative where restaurants can kind of have strength in numbers and band together to better serve their guests when they come in by sharing data about their guests across different experiences is something that our restaurants are asking for. They're saying, can Olo step into this role as this scaled platform, as a network of restaurants to help us fight back against these third party marketplaces?
It's very similar to hotels versus OTAs or airlines versus OTAs from a decade ago. The direct relationship with the guest is essential, and that's what we are aligned to help restaurants to do. And they're asking us to do more of it. And over the years, the best product launches we've ever had are when we're hearing from our customers, from our product advisory council, we need help. Can you help us? And the answer is yes. And we go and build something for them.
HUDSON SMITH:
Yeah. And most restaurant chains don't have large IT staff to do this.
NOAH GLASS:
No, no. Restaurants are not only shrinking the number of people inside the restaurant, they're shrinking the number of people at headquarters to get profitability at the franchise level. Profit margins at the franchisee level are low.
HUDSON SMITH:
That's right. Great. Thank you very much, Noah.
NOAH GLASS:
Thank you.
Thanks everybody.
ORLANDO BRAVO:
Listen to Thoma Bravo's Behind the Deal season four on Spotify, Apple Podcasts, YouTube, or wherever you get your podcasts.