Qualtrics’ $6.75B Acquisition, E-comm Startup Revival, Reflection AI Raises $2B | Oct 10, 2025

0:13Welcome, everyone, to the Informations TI TV. My name is Akash Pasricha. It is Friday, October 10th. We have got a jam-packed show for you today. We are bringing on the CEO of Qualtrics, the CEO of Reflection AI. Both those companies have made big news this week with acquisitions and with funding rounds. We're also going to talk about the profitability of stablecoin businesses and a quiet revival in the e-commerce sector. And finally, we are bringing on the founder of an AI startup who has decided to wind down his operations for what I know is going to be a great conversation about his reflections on the current startup landscape.

0:51Qualtrics made a big acquisition this week, buying Press Ganey Forsta for$6.75 billion. These aren't two names that we've talked about too much on this show just yet, but Qualtrics is a software giant that helps companies collect feedback from their customers and their employees. And Press Ganey Forsta helps healthcare companies collect similar feedback from doctors and for patients. I want to bring on Zig Serafin, the CEO of Qualtrics, to talk more about this deal. Zig, welcome to TITV. It's great to have you. Nice to be here, Akash, and you have a nice jam-packed show today. So thanks for having me.

1:24Nice to be here. Well, we are happy to have you leading us off here and starting us off strong. Look, I want to talk about this deal. It's one of the biggest deals in the software market that we've seen as of the past few weeks. Why did you do it? Well, I think in understanding it more clearly, I think it's important just to give you some background context. We're a critical, cutting-edge partner to market leaders, especially some of the best of brands and companies that are leading with experience. The ones that are focused on their customers or employees, or if you step back and say, okay, what's powering that brand technology-wise and how they connect with their customers?

2:04It's often it's Qualtrics that's there in the middle. And we have significant impact on how we help companies get closer to their customers. And over the last year, we have seen an extraordinary level of adoption in the AI capabilities that we put into our product suites. Since the launch, we've had more than a third of our customers. So, oh gosh, more than a third of 17 ,000 customers we have around the world have adopted capabilities under the market around AI. About 90 % of our top 50 customers have adopted. And so what we found and what we've learned is when you have AI that is purpose-built for the people that it's designed to serve, it delivers better experiences.

2:50It actually drives greater business impact. It drives real returns on the investment that they're making. And what we're finding is people want business that's, you know, ultimately want technology that's backed by focusing on the expertise within that industry and understanding the domain specific things that they're trying to do. So this clearly demonstrates the opportunity that we saw in making the$6.7 billion investment. Right. So I want to talk about sort of the strategy here. Press Guinea Forrester, I mean, this is a company that has really centered itself around healthcare and learning from doctors and patients that are in the many healthcare companies that it serves.

3:27From your end, was this an acquisition that you made to acquire the customer base and sort of expand into healthcare more broadly? Was this a deal that gave you technology that you didn't have? What exactly was the strategic logic here behind the acquisition? Yeah, I mean, first off, PG Forsta is very credible and has a wonderful track record in healthcare. They've also expanded into other areas and have been enabling market research capabilities as well. But in healthcare, they've got decades of experience in understanding how to drive predictive and analytics, being able to provide expertise to healthcare organizations to drive better healthcare outcomes for patients and how providers serve patients.

4:17And for several years now, we've had customers in the healthcare community that have come to us and said, why don't you actually put the best of the best together in Qualtrics proven technology and AI platform more recently and combine that if there were a way with the expertise, predictive analytics that Preskini has had in the healthcare space. And so at the end of the day, the focus is on outcomes, you know, purpose built for their industry, for their customers, for their employees, ultimately makes a lot of sense for what we're trying to enable in the market. And it's been driven by what customers have been asking for us.

4:56So from what I'm hearing, it was more for the products and not so much the customer base. So it wasn't so much of a, hey, you know, we want to gain market share in the healthcare segment. It was that they have products that we needed. expertise, predictive analytics, data that when you put it together with Qualtrics actually helps to create a one plus one plus, you know, equals five equation for customers. Right. It was a big deal. It was a$6.7 billion deal. Qualtrics, of course, went private a couple years ago for, I think it was just north of$12 billion was the takeout valuation. What was the multiple on this deal?

5:36You know, I'll let our finance guys speak to that, But we felt like it's a very healthy acquisition that makes sense. And I think a lot of it has to do with just the right next way in which we can actually provide value to the marketplace. And I do want to talk to you about Qualtrics has had a really fascinating history, right? It was once a public company. It's gone through many different ownership structures. But you are a private company now with Silver Lake and with CPPIB. I wonder, you know, what is it that you've been able to do perhaps as a private company over the past two years that you may not have been able to do as a public company?

6:15And how has being owned by private equity firms, how has that sort of changed the way in which you've been able to operate? Well, I think first off, just the mission of this company. I've been with Qualtrics for nine years, left after Microsoft, being at Microsoft for almost 18 years. And, you know, we're a very mission-purpose-led company. Our focus is around helping to heighten or elevate the human experience by partnering with organizations around the world to help them understand how to better support and care for their own customers in a more proactive and personal way. And every chapter of this company, we filed to go public, we were acquired by SAP.

6:53We then went public after that within SAP, and then we went private. Every single one of those milestones, which, by the way, Akash, as you know, is an extraordinary story. You don't see that typically. has been guided by people who are all in on that purpose and that mission in the organization. So when Silver Lake and the investment groups came to want to partner with us, the goal was to go and create an extraordinary company that actually helps to enable more organizations to innovate around experiences, to get closer to their customers in real time, to build an AI platform that helps to be able to innovate on these relationships and these partnerships that we have.

7:34So since we went private, we've actually been able to double down, we've become more effective, we've been able to scale on a global level, and it's actually given us the opportunity to make these types of investments such as the one that we just announced. And so what sort of changes have those been? Because we sort of know the private equity playbook traditionally has been to make companies more efficient, reduce costs, optimize headcount, as they say. So what has been happening at Qualtrics as a private company that has enabled it to make this acquisition financially? All of it's been on a focus on a customer.

8:08So speed in which we actually are able to operate the company on a global level, to connect with customers, making sure that the cash flow of the company is dedicated to what we're doing in R &D, advancing some of the core, core investments for making in AI. You know, one of the unique things about Silver Lake Partners and the other investors, BDT, MSD, the board of directors, CPPIB, who are also investors in the company, is they're playing the long game. They, you know, they take pride of ownership in building a company that will be a legacy to live on for long term. And they built, you know, they had amazing investments over the years.

8:47You know, example, Dell VMware, I work with Broadcom, you know, and more recently, some of the other investments have been talked about in the marketplace. So we have a group of partners who have, you know, sincere interest in building an amazing company that actually provides a lot of value to the marketplace. And especially at a time where, you know, you know, the market's changing, technology is going to change. And we're seeing software companies. I mean, AI has certainly, you know, it's certainly changing the game for software companies. And I'm excited to see how it's changing, how you operate Qualtrics in the marketplace.

9:21Thank you so much, Zig, for coming on and talking about this big acquisition you've done. I'm excited to see how it evolves. And we'll have to have you back again to talk more about how you're pushing even further into the healthcare market. That is Zig Serafin, the CEO of Qualtrics. Okay. Well, a few months ago, the information reported that Reflection AI was in talks to do a major funding round. And this week, the company announced that it has raised$2 billion at an$8 billion valuation. The company is backed by a number of big names, including NVIDIA, Lightspeed, and Sequoia. I want to bring on Misha Laskin, the CEO of the company, to talk more about what he has in store for Reflection AI.

10:00Misha, welcome to the show. It's great to have you. Hi, Kosh. Thanks for having me. Well, it's an exciting week for you. There are some really big numbers that are sort of coming to light about Reflection. I do want to talk about the business model broadly. So you sort of positioned Reflection AI to be the DeepSeek of the U.S. What is the vision for the company? Let's start there. Well, it's a great question. I mean, I think that what happened with DeepSeek in December of 2024 when it was launched is that it was a massive wake-up call for us in the U.S. in the ability to produce frontier open models and export them to the rest of the world.

10:42So we are building the frontier open model intelligence that will punch with the best of them, and it will be the kind of model that both the states and the world externally can build on top of for their intelligence needs. Now, from a commercial perspective, the kinds of customers that gravitate most towards this are the ones who have the largest AI workloads. And so this would be large enterprise customers or large startups that are consuming a lot of intelligence and want to own some of their own destiny and post-training their own models. That's kind of the commercial territory where we operate.

11:17And so, Misha, is the idea here that open source models are cheaper to use? I mean, what is the advantage there financially? I think the advantage is that once you become a big consumer of intelligence and you're a large enterprise, You want to own your intelligence. You want to run it on your infrastructure. You want to have access to the weights, so you can customize it for various applications. So you want control over your intelligence to drive both higher performance on tasks where it might not be working as well for you or drive down costs where things are working, but you want them to be more performance.

11:49So it's really about control, customizability, and full ownership of the model. So it's not about it being cheaper then. I mean, the whole idea with DeepSeek that came up was the idea that, oh, they might not have had to use as much compute, but then there were some more findings that, hey, well, maybe that wasn't really true. And the question really I'm trying to get at is a big problem for application layer companies, for example, or enterprise software companies that are using AI is that the models are expensive to use, right? And so we've talked about this, the cost of the models hasn't seemed to come down the way people thought.

12:24And my thought was maybe open source AI could be the solution to that. Yes. So you're definitely right that it is about cost performance. It's about when you have control over the model, then you're able to customize it for various tasks. And so there is a cost performance argument for maybe you're able to train the model more efficiently. And like DeepSeq, it's more cost performance out of the box. That's one thing. But the other part is you being able to take that model and customize it for your various workloads. And that enables it to be more cost performance as well. And so on top of that, then there's ownership and security and compliance and all these other things that enterprises care about.

13:03In addition, that make it the default way in which they want to consume intelligence. Right. Why couldn't you have built this at a Meta, for example? You were previously at Google. Meta is working on their own open source models. Why not go to a company like Meta? Maybe Mark Zuckerberg called you up and said, hey, just build what you're building here. I mean, can you ever think about that? Well, it's a really good question, Akash. And I think the fundamental thing here is that you need to be in a position where the commercial incentives are aligned with the research incentives of staying open.

13:38Without such a thing, when they're misaligned, then you're in a tail-wagging dog situation where there's nothing about being an open company that actually correlates with your commercial objectives. And so what I think has happened with previous iteration of companies is that they've had different commercial objectives than what's required to build out an open intelligence company. And so the reason to do this in a standalone is that to have those two things be entirely aligned so that you can continue seeing your mission through and being an open model company rather than starting off as an open model company and then having to pull the rug at some point because your product is taking you in a different direction.

14:17I want to talk about the fundraising round that you just did. NVIDIA was a big part of it. Who was the lead investor for this funding round? So obviously, NVIDIA played a very big role. We've had a number of major investors come in. Disruptive played a big role. DSC did, 1789, D Capital. Our existing investors, Lightspeed, Sequoia, CRV. So we've had a number of investors support us in the mission here. It was obviously a large round. I just want to understand because lead investor conceivably means they put in the most money and it's been reported that NVIDIA put$800 million into the round $800 out of$2 billion is a pretty big chunk so does that imply that one of those other investors put in more money than NVIDIA?

15:06It's not so much about other investors putting in more money it's more around in order for a round like this to materialize you have to have multiple points of support, right? It's not just all coming from one place. And several investors came in there in a big way. Okay, but there was no lead. No lead investor. Well, as I said, a number of investors came in there in a big way. Last question I do, I just want to talk about sort of the chip element to building these models. NVIDIA, of course, is a company that everyone relies on. And as you develop your models, are you only using NVIDIA's chips?

15:47Are you using AMD's chips as well? What does your sort of portfolio of compute look like? So, you know, we are going to be using the best chips on the market. And right for, you know, the cluster we're setting up now, the best chips on the market that are going to be coming out, right, are the next generation of black holes that are coming from NVIDIA. So we are working closely with NVIDIA. We will be partnering with them on getting the compute required for us to do our large-scale training runs. But fundamentally, what this company is, is building a thriving AI ecosystem and working with the best chips to do so.

16:28Right. Great. Well, thank you, Misha, for coming on the show. It is an exciting week for you, and I trust you are going to find some time at least to rest this weekend. We appreciate you coming on. That is Misha Laskin, the CEO of Reflection AI here on TITV. Okay, it's been just over two months since the passage of a new stablecoin law called the Genius Act, and it's already having a big impact on crypto markets, giving rise to new competitors looking to seize control from stablecoin giants Tether and Circle. I want to bring on Yueqi Yang, our crypto reporter who published some great reporting on the topic this week.

17:04Yueqi, welcome to the show. It's great to have you back. Hey, Akash. Thanks for having me. So let's talk about stablecoins. The Genius Act. So look, it was passed, okay? That was a couple months ago. There was a big song and dance about it. And the message was, I mean, the floodgates are going to open for startups, companies being able to dive deeper into stablecoins. What have we seen over the past few months to that respect? Yeah, so we immediately saw a lot more companies launching stablecoins. I would say that the first movers are definitely crypto companies. And these are crypto exchanges, wallets, and even blockchains that are launching their own stablecoins.

17:45And the reason for that is that they already have a lot of users that are currently using stablecoins like Tether and Circle. So they are highly motivated to reduce their own dependency on outside stablecoins. And they can do so by launching their own so that they themselves or their users can benefit from the revenue generated from the reserve assets from stablecoins. And who are some of the major companies that have started to wade deeper into the stablecoin space over the past few months, whether it be issuing them or, you know, even starting to talk about supporting the ecosystem? Sure. So the new players, I would say, include Stripe, which is issuing stablecoins for other companies using Bridge, a startup that they acquired this year for$1.1 billion.

18:40And Anchorage is another player that's making moves in the market. They are the only crypto company with a national trust charter at the moment. And they most notably got a partnership with Tether to issue the new stablecoin for Tether in the U.S. market. And I think one thing that's different for this new generation of players is that they are in the business of what they call stablecoin issuance as a service. So Stripe is not launching its own stablecoin. It is launching stablecoins on behalf of their clients. And they make it very easy and quick for other companies to do so. And they only charge a small fee for doing that.

19:21And what about the companies that the stablecoin as a service company is a very interesting category of startups. What about the companies, I guess, their customers? Who are the people that are the companies that are issuing the coins themselves? So StripesBridge is launching stable coins for a few crypto companies, and that includes crypto wallets, Metamask, and Fanton. Both are very highly popular crypto wallets that have a lot of users. And they're also launching stable coins for Native Markets, which is a partner for Hyperliquid. which is currently the fastest growing perpetual exchange. And they also have a lot of users that could potentially use these new stable coins.

20:06And so all these companies that have their own stable coins now, do they not pose competition to one another? Yes, they do. And that's what we expect. But all the new launches are still very early. A lot of them are in the tens of millions of dollars of market cap right now. So that's quite small at the moment, comparing to Tether and Circle's stablecoins. So we'll need to see how quickly they can gain ground. And for all these companies that are deciding that they want to issue stablecoins, how profitable is the business of issuing stablecoins? Because I know companies like Circle, for example, have a very big partnership with Coinbase where you have to pay for distribution, essentially, of these stablecoins.

20:53Is this a challenge that these newer companies are starting to sort of realize as they move into the space? Yes, it is not a problem for them at the moment. And I think that naturally raises the question how sustainable the business model is. If you consider it only as a standalone service, and obviously Strive and Anchorage, they could make money through other add-on services that they provide for their clients when they issue their stable coins. But what we see is that the stablecoin market is quickly becoming a commodity business with very low margin. Stripe says it will pass along all the revenue from the stablecoin business to their partners, minus a very small fee of 50 basis points.

21:40And we also saw the same trend with Spicco, which is issuing the stablecoin for the Trump family's World Liberty project. and their financial record showed that they made about 15.7 million revenue in the first half of this year from this service, but they paid out the majority of them,$15.2 million to their partner. And so last question for you, Aichi, if it's not a profitable operation, why do it? Well, it is a risk at the moment. And I think the priority for these companies is to gain market share first and then figure out how they can make money from it later. And a lot of these startups are funded by VC money.

22:23So they do have quite a lot of cash to cover that. I mean, I more just think about sort of the long-term profitability prospects of this business and how reliant they are on the exchanges to sort of facilitate the transactions here. It's kind of interesting to think about if they could become profitable in the long run, because so far it feels like we haven't quite decided on the business model. that actually works. Anyway, Yuechi, thanks so much for coming on the show. We really appreciate it. I encourage everyone to read that story that we published this week. I'm sure there's more news to come, so we look forward to having you on again.

23:03That is Yuechi Yang, our crypto reporter here at The Information. On this show, we talk a lot about the companies that are really thriving, but the reality of startups, of course, is that they are really hard, and not every company pans out the way founders initially expected they would. And so today, we're bringing on one founder who had to make the difficult decision to wind down operations at his company. Aaron Dignan co-founded a company called Plum. It was an AI company that he's been working on for five years. And as you can imagine, Aaron has a ton of reflections on why things may not have worked out the way he initially expected.

23:39Aaron, welcome to TITV. It's great to have you. Hey, thanks. It's good to be here. So you've had a big week. I mean, it's been a big week of decisions for you, it looks like. Yeah, or a half decade, depending on how you count. There you go. Yeah, well, that's true. It's all part of the big story. Look, before we talk about the week that you just had and the decision, what was the original vision for Palm? Yeah, the core vision here is you see tools like N8N, the OpenAI Agent Builder that just came out, you know, Gumloop and others automating processes and tasks and work with AI. And our thesis was, while there are many people in the world that will take the time to learn how to do that, it's quite technical, no matter how no code it is.

24:25And it would be amazing if there were kind of a sub stack for AI workflows where you could subscribe to someone else's creation that would then automate and customize something in your business life. And so that's kind of the mission that we ran against. Got it. And so you had that mission. Why did you decide ultimately to wind things down this week? I think we have decided that we're either early or wrong and probably early. But the reality is the number of people who can actually automate like full agentic workflows in work that actually work, right? Because there's a lot of hype and then there's the reality is a small number.

25:01And of those, a lot of those people benefit greatly by charging a lot of money to customize and consult and kind of go inside organizations and fix that. So we really had an inability to build a creator economy side of this equation. Lots of people want to subscribe to solutions, but there weren't enough people that were willing to create something that they share at a low enough price point to create a whole marketplace effect right now. So I think we're just still in the early innings of what agents and agentic workflows are going to do. And we think that that marketplace may come to fruition later down the road.

25:39And so from your end, as you reflect on this, was this more of a technical challenge that really dominated? Or was it a business model challenge? I think it's a business model challenge. We were able to invent the technology. I mean, things like meta JSON schema that allow you to actually share a workflow with thousands of other people. but the challenge was more, you know, is the market there? Is the business model right? How do you kind of optimize those lines? And while we felt like we were very close, it, you know, from a like line of sight to venture scale perspective, we just couldn't quite see it.

26:15And so we're still really committed to the space. We're still really interested in AI automation as a valuable place to play. We just felt like we needed to like wipe the slate clean and think about it fresh. How many employees did you have at the company? Seven people, really like a lean kind of zero to one team. Yep. Okay. And what's in store for the team now? Are you guys going to try to start a new startup? I mean, have you started talking about who's going to hire these people? What's the response been? It's been a very weird week. So I tweeted about our lessons learned and about the shutdown, you know, day before yesterday.