In this interview from theCUBE + NYSE Wired: AI Factories – Data Centers of the Future event, Glean co-founder and CEO Arvind Jain joins theCUBE’s John Furrier to unpack what’s really working in enterprise AI today and what comes next. Jain explains why knowledge access remains the first successful AI use case at scale and how Glean’s enterprise search brings AI into everyday work. He details the past year’s lessons with AI agents – from the need for guardrails, security, evaluation and monitoring to democratizing agent building so business owners (not just data scientists) can create production-grade agents.
The conversation dives into Glean’s vision of the enterprise brain powered by an enterprise graph, highlighting the importance of deep context, human workflows and behavior to reduce “noise” and drive outcomes. Jain outlines core building blocks – hundreds of enterprise integrations and a growing actions library – that let agents securely read company knowledge and take actions across systems (e.g., CRM updates, HR tasks, calendar checks). He discusses how organizations are standing up AI Centers of Excellence, prioritizing “top 10–20” agents across functions like engineering, support and sales, and why a horizontal AI data platform that unifies structured and unstructured data – accessed conversationally and stitched together via standards like MCP – sets the foundation for AI factory-scale operations. Looking ahead, Jain says Glean’s upgraded assistant is evolving from reactive tool to proactive companion that anticipates tasks and accelerates productivity.
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Jan Goetz, IQM Quantum Computers
In this interview from theCUBE + NYSE Wired: AI Factories – Data Centers of the Future event, Glean co-founder and CEO Arvind Jain joins theCUBE’s John Furrier to unpack what’s really working in enterprise AI today and what comes next. Jain explains why knowledge access remains the first successful AI use case at scale and how Glean’s enterprise search brings AI into everyday work. He details the past year’s lessons with AI agents – from the need for guardrails, security, evaluation and monitoring to democratizing agent building so business owners (not just data scientists) can create production-grade agents.
The conversation dives into Glean’s vision of the enterprise brain powered by an enterprise graph, highlighting the importance of deep context, human workflows and behavior to reduce “noise” and drive outcomes. Jain outlines core building blocks – hundreds of enterprise integrations and a growing actions library – that let agents securely read company knowledge and take actions across systems (e.g., CRM updates, HR tasks, calendar checks). He discusses how organizations are standing up AI Centers of Excellence, prioritizing “top 10–20” agents across functions like engineering, support and sales, and why a horizontal AI data platform that unifies structured and unstructured data – accessed conversationally and stitched together via standards like MCP – sets the foundation for AI factory-scale operations. Looking ahead, Jain says Glean’s upgraded assistant is evolving from reactive tool to proactive companion that anticipates tasks and accelerates productivity.
In this conversation from theCUBE + NYSE Wired: AI Factories – Data Centers of the Future, IQM Quantum Computers Chief Executive Officer and co-founder Jan Goetz joins theCUBE’s Gemma Allen at the NYSE Studio to unpack quantum computing’s “20-year overnight success story.” Goetz traces IQM’s journey from an Aalto University spinout to a European quantum champion, explaining how a strong academic base, an early focus on commercial products and selling full systems into supercomputing centers helped the company scale. He breaks down Europe’s unique mix of sover...Read more
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What is the history and development timeline of quantum mechanics and its applications in technology?add
What motivated the decision to spin out IQM from Aalto University?add
What is the current state of quantum startups and commercialization in Europe compared to the US?add
What are your thoughts on the potential impact and future of AI technology?add
>> I'm Gemma Allen here with theCUBE live at our NYSE Studio connecting Silicon Valley to Wall Street, and today, we're connecting European quantum leaders to Wall Street. Joining me in studio I have Jan Goetz, CEO and Co-Founder of IQM Quantum Computing. Welcome, Jan.
Jan Goetz
>> Well, I'm super happy to be here.
Gemma Allen
>> Thank you. So quantum computing, I think a lot of people hear that term, gives a little bit of inertia, a little bit of fright, perhaps a little bit of hope. Let's maybe unpack that. You say this is a 20-year overnight success story. Talk to me about the journey you've been on and what you're building at IQM.
Jan Goetz
>> Yeah, well actually, quantum is not a new idea. We are celebrating this year, a hundred years of quantum mechanics by the United Nations. So on the scientific side, this idea and the theory and now also the technology has been out there for quite a while, but technology takes some time until you get a product out of it. And it was really, I think in the early 2000s or so when first prototypes have been built on the university side. So mainly academic efforts both here in the US but also in Europe. And it became more and more clear that you can actually build real computers out of it that solve commercial problems. And this really sparked a development around maybe 2015 when first startups were created, companies like Google and IBM got into the field and the whole effort moved out of the universities more towards the private side, and the same is true actually also for our case. So I was doing my PhD, I was doing my postdoc, and then we realized, "Okay, if you really want to build a large scale computer, you're not going to do this in the university, actually, you need to do this in a proper setup." And we decided to spin out IQM from Aalto University, which is the leading tech university in Finland. And this was around 2018. We got the first investment round together in 2019 with the ambition to build really a global leader for quantum computing. And fast-forward to today, I think we're on a pretty good track there.
Gemma Allen
>> For sure. Right? You are a unicorn. Congratulations. And you've raised a lot of money and from a European perspective, you guys have been on a real trajectory. Let's talk a little bit about that because I think a lot of us here in the US, we all know the MIT, Stanford success story, right? The college dropouts that create multi-billion dollar business in their dorms. The European narrative is maybe a little bit less well-known. And you say you're on a mission to make quantum, to make Europe a leader in quantum computing. Talk to me about that kind of academic to lab to commercial spin out and raising money in this landscape, especially as a European.
Jan Goetz
>> Yeah, in Europe, we do have a very strong academic foundation. There are very good universities out there and quite a number of them as well. And in quantum in particular, we have been seeing that basically each university created their own spin out. So if you just look at the bare numbers, I think there are more quantum startups in Europe compared to the US, but what we are kind of not so good at is to scale them up really, to become a global company and to scale also then on the commercial side, and this is a challenge that we really particularly addressed. So from day one, we said, "Actually we are going to build products and we are going to commercialize those products and sell even these very early stage computers." And this is something that really makes us different is that we are meanwhile the company that has sold most quantum computers globally more than anyone else. And this really helped us create commercial traction and then bring in more and more investors from around the world. Meanwhile, actually also US investors. But it's really the question how to scale companies in Europe, both from a capital perspective, but then also from a team perspective because there's just not so much experience like you have here in the US, very experienced people who have been building and scaling companies over and over again. We don't have that so much in Europe and we think we do need examples and we want to be one of those examples where we say, "Hey, it's actually possible to do this out of Europe." And I think you need to be a little bit creative in the way you do it, but actually in the end, there is a path to succeed.
Gemma Allen
>> Well, I love to hear that, right? As an Irish woman, I want to see Europe on that map. So I think when you think about comparative advantage and competitive advantage, differentiators are a big part of that story in the quantum space and in super computing in general, you're competing against some huge players, Google, IBM, so I'm sure there's a level of inertia that comes with that. But you guys started with a differentiator, which was this on-prem offering. I know that has kind of pivoted somewhat. Talk to me a little bit about that, about how you came at this from a compete angle and what's happening right now at IQM with cloud-based services.
Jan Goetz
>> Yeah. So we had a little bit the advantage that we were kind of a fast follower because when we started in 2019, a lot of effort was already going on here in the US and this effort was mainly targeting the cloud. So basically, you sell computing time on your machines and back then, I think it's fair to say that the computers and the products were not yet ready. So the quality of the systems wasn't really great and the uptime and stability wasn't that great. And this is why we said, "Okay, we go actually a different way and first, we develop a product that works really reliable."
So a quantum computer that can stay online 24/7 basically, and that is of very high quality and then we bring them to the cloud. So we have been developing the product and at the same time we have been selling it out to computing centers, which are a bit more forgiving because they actually themselves want to co-develop with us on the systems. And now, I think we have a very strong offering there. So our quantum computers which are in the cloud, meanwhile actually they are online almost 24/7 and they operate at very high qualities, and our customers really are happy with this. So they really say, "Okay, it's great that you can offer us such kind of a solution where we don't have to wait all the time when the computers go offline to recalibrate or things like this." So I think it was the right strategy to first focus on on-prem computing and now to ramp up the cloud business at this point in time.
Gemma Allen
>> Love it. And tell me, it seems to me as though every five years somebody says quantum is five years away, you obviously have some very specific high-value use cases around this. For those non-physicists amongst us, myself included, tell us a little bit about the utility aspect of this, where it's having impact, what type of clients and customers you guys are engaging with in a very measurable way on a day-to-day basis.
Jan Goetz
>> I would agree that still some years ago maybe we had this effect that you also have infusion and other technologies where it's always five years away and over five years away. But in quantum, I think this is really changing now and there are quite many reports out there which kind of estimate how long it still takes. And just to give you one example, we make progress of course on the hardware side of things, but actually also there's huge development on the software and algorithmic side. So one of the use cases, which is always the elephant in the room is the code breaking. And until just one or two years ago, the estimation was that you would need 20 million of those qubits, the quantum transistors to do the code breaking. And then Google came about with a paper to reduce this number from 20 million to 1 million. So there are huge developments both on the algorithmic side and also on the hardware side, which we do think that the first use cases actually can be unlocked in the next couple of years. And it's not that black and white that all of a sudden everything is going to work, but it is like in semiconductors where we have roadmaps and we have something like Moore's Law and semiconductors is going to happen for quantum as well where we just see steady progress and the computers that we build are getting better and better. And we do think that the first use cases that will be unlocked are probably in the field of quantum chemistry. So material science, pharmaceuticals, battery development, things like this where we actually have a very strong effort also ourself, but then we also see use cases coming up in the optimization field. So especially in places like this, you can do option price and portfolio optimization, things like this. And then we focus a lot on quantum machine learning, so using quantum computers for AI. And this is something that actually we do with a very strong effort of combining our quantum computers with GPUs and CPUs, so with other providers in the supercomputing space and really bringing those technologies together because we do think that ultimately, it's not a standalone solution, but it will be a hybrid approach where part of the problem will be solved, for example, on GPUs and other part of the problem will be solved on a quantum computer.
Gemma Allen
>> Well, speaking of GPUs, and speaking of places like this, you're here at the NYSE this week and you're here in the US I think you have some news that you're going to announce. Can you share a little bit about what has you in the US what the global growth plans are? Are you doubling down on this market, fill us in.
Jan Goetz
>> Yeah, of course. We're super excited about the US market, especially since the two business models that we are following, selling on-prem computers to data centers and selling through the cloud. So data centers and cloud are the kind of two big markets here in the US and we are not doing this alone and we are doing this in strong partnerships. And one of those partnerships actually is with Nvidia in integrating our quantum computers with their GPUs. And at the GTC event in DC, it has been announced that actually we are strengthening this collaboration and we are going into what we call real-time connection between the two systems for air correction. So this is really a much deeper level of integration now that we are doing together with Nvidia. And we are super excited about it because this will unlock actually the use cases that we have been talking about in pharma or in finance, and in many other industries. And actually, it shows also the strong commitment of the rest of the industry players like Nvidia actually doubling down in quantum shows that there's really something behind. And also that there's a very clear path actually to get there.
Gemma Allen
>> Wow. Well, congratulations, my co-host Don Furrier is actually there this afternoon. So look forward to that news coming out. So in terms of these global partnerships, Nvidia is obviously a very big global player. It's been a lot of geopolitical strife this year. It certainly gets a lot of news coverage here in the US. Europe has always been seen as somewhat of a regulatory challenge, maybe a little bit more guard railed for certain than other parts of this globe is here included. Tell me a little bit about that element of quantum and the regulatory, I guess this position in Europe versus rest of world and how you approach that even especially from a partner angle.
Jan Goetz
>> Yeah, quantum computing has this sovereign aspect because some of the use cases are very sensitive, especially when we talk about code breaking and things like that. And this is why there's a strong belief in Europe, but also in the US that there also need to be local champions, and it's clear that we are the European champion. And for us, this is of course also a very strong signal from all the European governments who all the time tell us, "Okay, we are going to make sure that we support you on the way forward."
And I think having this security at home, so to say, I think it's great for us and we have been really leading in Europe and deploying quantum computers to data centers. I think there are more installations of quantum computers and supercomputing centers in Europe than in the US for example. US I said is very strong on the cloud side of things. But for us, this has really been a key driver of the business and selling there, but meanwhile actually we go much beyond this. So we have been selling also here in the US Oak Ridge, one of the biggest supercomputers in the US gets one of our quantum computers as an accelerator. We have been selling systems in APAC as well, countries like Korea or Taiwan for example. So we are really now on this growth trajectory based on the infrastructure that we have built up in Europe. So we are running our own chip factory, we are running our own assembly line, our own data center there. We are now expanding globally actually to bring the technology to the world and make sure that we have the best quantum computers out there wherever they're needed.
Gemma Allen
>> And tell me a little bit about the funding element of this because I think some of your public competitors have had mammoth years in terms of the stock market and their price valuations, you've seen like 1,400% growth in quantum companies. I won't name them, but I think you know who I mean. How has that been from the perspective of raising money, right? Nvidia is a phenomenal partner. It's obviously another titan of industry. How have you approached that from the perspective of raising in Europe versus the US? Those conversations you have with investors. Tell us a little bit about what that's like.
Jan Goetz
>> So I think we have a good mix of European and US investors just in the recent series B round that we announced a couple of months ago. We have a US lead investor there who's really helping us to grow here in the US. But then as I said, we also have the strong support locally in Europe. I think the challenge is to raise these growth rounds in Europe. There's not so much of this growth capital there. And the developments that we have seen, the public markets, the very strong position that some of the quantum players have in the public markets have surely helped us raising also on the private side because it shows that there's confidence in the technology and it shows the private investors as well actually that there's a path forward and there's very strong backing. So for us, this has been very strong signal actually from the public markets, which has helped also our private fundraising.
Gemma Allen
>> And I guess there's also so much financial aptitude for something that is futuristic, that is conceptual at one point in that kind of conversation. Let's talk a little bit about AI and the hype cycle/world we're in right now, right? Whether it's hype cycle or not, I guess it's debatable, but tell me about how you think about AI and its kind of mass utility and as an academic, as somebody who's an academic background in particular, how you think about the impacts on learning and staffing and the tech world of great minds and geniuses in general. Is it something that you feel is being missold or what are your thoughts?
Jan Goetz
>> No, I believe that AI is a very transformative technology and it will open up all kinds of new markets and use cases. And this is great, and it will drive the demand for compute more and more. And this is something that we are seeing, right? People are building huge data centers worth billions of dollars and they consume gigawatts of power. And I think this is again where quantum comes in because at some point, it's really hard to scale further in this conventional way just building bigger and bigger data centers. They're already reaching sizes of whole towns, and from this perspective, it is clear that we need also a new paradigm when it comes to compute. And I think this is where quantum then plugs in because quantum can be this accelerator also for AI algorithms. And for us actually, it has been, again, a very strong sign from the AI wave that is currently out there that we need more compute and that we need alternative compute resources. And we think that we have a very good offering actually there. So I think it's a nice symbiosis between AI and quantum because also on the other side then quantum can benefit from AI. We are already using some machine learning methods when we do the chip design or when we tune up our computers and stabilize our computers. So we are benefiting from AI on the one hand side, but then also AI will be accelerated by quantum computers and hopefully the whole compute will be made much more energy efficient because quantum computing can actually help there as well.
Gemma Allen
>> And what about its impacts on academia? You're somebody who at one point had I think a hundred PhDs in the company or maybe certainly a significant amount of very talented, very qualified people. How do you think about it when you hear people say things like AI is potentially a threat to tech jobs or to people's future careers in that space? What do you say in those academic conversations?
Jan Goetz
>> Well, I think I said it's a transformation. So of course, jobs can be transformed from doing one thing to another. I think if you look at the history of technology, there have always been these discussions, whether robots take away human jobs or production lines take away.
Gemma Allen
>> When man made the machine, he made himself redundant, right?
Jan Goetz
>> But in the end, truth is basically because of the technology that was developed, new jobs get created, and I'm a strong believer that especially for innovation, we still need humans. We need creativity. We need to come together and think outside of the box. So I don't think that AI will take away all of this, and we still need the best scientists also out there to develop new technologies like quantum, and I think we are very proud having one of the strongest teams out there. As you said, we have way more than a hundred PhDs in quantum. We have a very strong team supporting then also with all signs of other functions. And I think it's this team dynamics that you get and everyone pulling in the same direction to really deliver then on the roadmaps and or milestones. So from this perspective, I'm not afraid that AI takes over. I think it's a huge opportunity and we should just use it in the right way to develop our technology further.
Gemma Allen
>> I love it. So Jan, tell me, what's ahead? Are we going to see you back here at the NYC ringing the bell?
Jan Goetz
>> Well, of course, we just raced around, so we are now in a good position from a financial perspective, but we are watching the scene quite carefully and we do see what's happening on the public market and we will kind of take our conclusions from that.
Gemma Allen
>> Well, we wish you all the best of that journey and hope to see you in New York more often.
Jan Goetz
>> Thank you.
Gemma Allen
>> Thanks so much for coming on. I'm Gemma Allen here at the NYSC with theCUBE. This is our AI Factory Series. Thank you for watching.
Gemma Allen