Andy Hock, senior vice president of product & strategy at Cerebras Systems Inc.; Shehram Jamal, chief product officer for data & models at HUMAIN (Al-Mustaqbal Lil-Thaka Al-Istinai Company, also known as Future Artificial Intelligence Company); Kevin Cochrane, chief marketing officer at Vultr, a registered trademark of The Constant Company LLC.; and Joseph S. Spence, chairman, chief investment officer at NativelyAI, join theCUBE’s John Furrier at theCUBE + NYSE Wired: Robotics & AI Infrastructure Leaders 2025 event. The panel explores how robotics and AI infrastructure are reshaping global innovation and sovereignty in the AI era.
The panelists examine regional approaches to AI deployment, emphasizing sovereign strategies and compute accessibility across economic divides. They discuss the cultural and geographic nuances shaping infrastructure choices and development priorities.
From scaling compute capacity to redefining AI as a public good, the conversation highlights the sector’s high stakes and even higher potential. The discussion offers a grounded take on building equitable, globally competitive AI ecosystems.
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Axel Lönnfors, Metabob
Andy Hock, senior vice president of product & strategy at Cerebras Systems Inc.; Shehram Jamal, chief product officer for data & models at HUMAIN (Al-Mustaqbal Lil-Thaka Al-Istinai Company, also known as Future Artificial Intelligence Company); Kevin Cochrane, chief marketing officer at Vultr, a registered trademark of The Constant Company LLC.; and Joseph S. Spence, chairman, chief investment officer at NativelyAI, join theCUBE’s John Furrier at theCUBE + NYSE Wired: Robotics & AI Infrastructure Leaders 2025 event. The panel explores how robotics and AI infrastructure are reshaping global innovation and sovereignty in the AI era.
The panelists examine regional approaches to AI deployment, emphasizing sovereign strategies and compute accessibility across economic divides. They discuss the cultural and geographic nuances shaping infrastructure choices and development priorities.
From scaling compute capacity to redefining AI as a public good, the conversation highlights the sector’s high stakes and even higher potential. The discussion offers a grounded take on building equitable, globally competitive AI ecosystems.
Metabob revolutionizes AI code analysis and optimization through innovative applications of cutting-edge technology. In this insightful session, Dave Vellante of SiliconANGLE Media hosts Axel Lönnfors, chief operating officer at Metabob, at the Rosewood for theCUBE + NYSE Wired event. Lönnfors discusses advancements in AI code analysis, providing a glimpse into Metabob's use of graph neural networks to streamline code optimization and refactor substantial legacy systems.
The Metabob platform leverages AI by integrating graph neural networks with lar...Read more
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What is Metabob and what does it do?add
What capabilities does the technology offer in relation to analyzing and fixing code?add
>> Hi, everybody, welcome back to the Rosewood. This is Dave Vellante in for John Furrier and the whole theCUBE team, theCUBE + NYSE Wired. This is an extension of our AI robotics leaders, our media week that we've been running out of Palo Alto with the NYSE Wired + theCUBE community. We've taken it poolside to the Rosewood here and I'm really excited to have Axel Lönnfors, who's the COO of Metabob. I don't know if you've heard of Metabob. Welcome.
Axel Lönnfors
>> Thank you. Thank you.
Dave Vellante
>> What's Metabob?
Axel Lönnfors
>> So we're an AI code analysis tool that connects graph neural networks to large language models, to essentially enable large language models to take in a full legacy code base written in any of the old languages that you would name from COBOL, VB.NET to the modern ones like Python. And along the way, with C and C++, you can dump your whole code base with millions of lines of code. And without losing any context or hallucinating with LLM, our graph neural network is essentially able to detect problematic areas in the code, as well as areas for improvement in optimization and refactoring along your code base. And helping organizations to cut their technical debt by a lot.
Dave Vellante
>> So using that GNN to automate the modernization of that code, which used to be a highly manual process.
Axel Lönnfors
>> Yes.
Dave Vellante
>> And one that was problematic because let's say you're trying to migrate from COBOL, you would have to freeze the code, and it might have to freeze it for a long time. Meanwhile, your business is trying to run, and so what's the enabler that allows you to do that? Obviously AI, but give us some color on that piece.
Axel Lönnfors
>> Right. So we don't yet focus on migrating code from a language to another, even though theoretically with our technology, it is also possible. What we want to focus on is using our proprietary analysis model to flag problematic areas from basically a bird's eye view on the graph of the code. Because the graph represents how different code chunks connect to each other along the code base.
Dave Vellante
>> Okay, I see.
Axel Lönnfors
>> And we then can do an anomaly detection of problematic areas. We can narrow down the relevant context space. And then pass that information to a fine-tuned large language model that can be used to generate a more detailed description of the problem, as well as to generate the fix for the detected problem.
Dave Vellante
>> So just to put a finer point on it, you are converting the code ultimately, are you not? Or are you just sort of identifying the anomalies? Is it both?
Axel Lönnfors
>> We are identifying the anomalies and we are fixing the anomalies.
Dave Vellante
>> Yeah, okay.
Axel Lönnfors
>> So we do generate code.
Dave Vellante
>> Okay, but you'll fix them in COBOL or whatever language is needed to run?
Axel Lönnfors
>> Yes, we can analyze COBOL and fix them in COBOL.
Dave Vellante
>> Interesting, okay. Because there are a lot of tools that will convert the code, that's not what you're doing.
Axel Lönnfors
>> That's not what we're doing.
Dave Vellante
>> Your superpower is identifying those anomalies and fixing them in an automated way.
Axel Lönnfors
>> Correct, that's what our business currently is. Our clients, they range from government agencies to Fortune 500 companies, so we really went headfirst into the enterprise space as a young startup. And currently, when everyone is talking about agentic AI, we're also able to act like as a control tower. So let's say that you use an agentic AI, you use it to build a larger application. It runs into a problem because it's starting to lose the context and the intent of the application and introducing some 502 errors when you're trying to deploy it. Essentially, when that happens, we can integrate into the agentic flow that when it runs into a problem, it automatically calls an analysis from our back end. We analyze the whole repository, we come up with a list of problems. And then we match the right problem to the problem that the agentic AI is currently experiencing, helping it to overcome that problem.
Dave Vellante
>> And you sell to the head of application development or developers? Who do you sell to?
Axel Lönnfors
>> Yeah. We sell depending on how large of an organization we're working with, but it would range from head of software engineering, to VP of software engineering all the way to CTO, depending on the size of the company.
Dave Vellante
>> Okay. And you guys, have you funded, are you seed round?
Axel Lönnfors
>> Yeah. So we have raised our first round a few years ago, after which we have already become profitable for a while, as well as got funded by the National Science Foundation of the United States. And now we're just gearing up to raise a little bit more money to also work on newer integrations into the more modern space of agentic AI, while continuing to serve our customers and expanding the legacy code base analysis side.
Dave Vellante
>> Do you feel like you have product market fit?
Axel Lönnfors
>> We're close to product market fit. We have great customers. The feedback is good. To have product market fit, I would always, I'm a critical person, I want to have hundreds of customers in-
Dave Vellante
>> More maturity, okay.
Axel Lönnfors
>> More maturity. But for a young company, we're on a good way.
Dave Vellante
>> So you're not scaling your go-to-market quite yet, is that right?
Axel Lönnfors
>> We're trying to scale in specific verticals, including finance, manufacturing and government.
Dave Vellante
>> Government, yeah.
Axel Lönnfors
>> But also looking to do POCs in new verticals, such as healthcare, gaming, et cetera, for our tool.
Dave Vellante
>> What's the North Star of the company? How would you describe that?
Axel Lönnfors
>> North Star is customer satisfaction with the tool, that's the only thing we care about. How much value can we provide? How much time can we save from maintaining their legacy code bases? That's what we want to provide for our customers.
Dave Vellante
>> Yeah, because nobody wants to do that.
Axel Lönnfors
>> Yeah, everyone wants to do that.
Dave Vellante
>> Axel, thanks so much for coming to theCUBE.
Axel Lönnfors
>> Thank you.
Dave Vellante
>> We appreciate it.
Axel Lönnfors
>> I appreciate it.
Dave Vellante
>> All right, and thank you for watching. Keep it right there for more action from the Rosewood, you're watching theCUBE + NYSE Wired Media Week, AI and Robotic Leaders. We'll be right back, right after this short break.
Dave Vellante