In this insightful discussion, Allen Salmasi, Chairman and Chief Executive Officer of Veea Inc., joins the conversation with the co-founder and co-CEO of SiliconANGLE Media Inc. on theCUBE at NYSE Wired. Together, they explore the transformative role of artificial intelligence (AI) factories in the development of future data centers, emphasizing the convergence of AI with network infrastructure at the edge.
Salmasi, renowned for pioneering work with Qualcomm and its Code Division Multiple Access technology, shares expertise on the trends shaping the integration of AI into edge networks. The video delves into how Veea addresses challenges of a hyper-converged edge with innovative wireless solutions catering to logistics, healthcare, and transportation industries.
The conversation highlights key takeaways such as the inevitable shift of AI becoming context-aware and the need for low latency applications. Salmasi explains the collaboration between Veea and leading tech companies such as Nvidia on open Radio Access Network architectures and the implications for telecom operators. According to Salmasi, the convergence of communications and cybersecurity is critical, providing a zero-trust architecture essential for secure AI deployments at the edge.
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Allen Salmasi, Veea Inc
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 edition of theCUBE + NYSE Wired: AI Factories – Data Centers of the Future, John Furrier sits down with Allen Salmasi, chairman and chief executive officer of Veea, to examine how artificial intelligence is moving beyond hyperscale data centers and into the wireless edge. From hyperconverged infrastructure to distributed compute, Salmasi outlines why low-latency, context-aware AI is becoming essential for real-world use cases in healthcare, logistics and transportation. He explains how Veea is building network architectures that merge radios, compute ...Read more
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How should one respond to the idea that AI factories moving to a hyper-converged edge will transform wireless infrastructure, given the complex, fragmented "soupy" mix of spectra, vendors, and edge environments?add
How does your architecture leverage NVIDIA’s Open RAN work to create distributed radio networks and a compute/microservices mesh at the edge for industrial or factory deployments (especially as terahertz radios proliferate)?add
What supply agreement did the company announce with América Móvil/Telcel, and how is the company pivoting to scale via telco partnerships — including what products or solutions will be deployed to the operator's network?add
>> Welcome back. I'm John Furrier, host of theCUBE. Here at our NYSE studio, of course, we have Palo Alto in Wall Street, in Silicon Valley. Part of our CUBE and our NYSE Eired brand, a CUBE original where we merge capital market coverage with technology, our AI factory series. Allen Salmasi's here, Chairman, CEO of Veea, Inc, a distinguished legend in the industry. Really pioneered the Qualcomm business around CDMA, among other things. NextWave bought by AT&T, wireless guru, expert. Great to have you on here on theCUBE. Thanks for coming in.
Allen Salmasi
>> Thrilled to be with you. Thank you, John.
John Furrier
>> One of the things we've been talking about here in theCUBE in the past three months is this notion of a hyper-converged edge, and the idea that AI factories will come to the edge. And it's pretty easy to connect the dots when you see all the AI factory conversations, the big data centers. But when you go to the edge, you got to play in the wireless world. Your company, Veea, is doing wireless. It's at the edge, it's connections. There's multiple spectrums involved. It's kind of a soupy mess, because you have different companies doing different things, different infrastructure. If that all collapses with an AI factory, it changes wireless. What's your reaction to that? What would be your commentary around this scenario?
Allen Salmasi
>> Yeah. I totally agree with you that this is probably the soupiest mess that anyone is going to tackle anytime soon. But we think that we have addressed it to a large degree, because at the macro level, there are five structural type of trends that are effectively converging. And the most important one is the fact that, effectively, AI needs to become context aware and low latency in order to have real world applications for many of the use cases. So, we have designed a network architecture and implemented a number of solutions that allows for AI to be applicable to many, many different use cases, regardless of if it's for logistics or healthcare, or transportation. Really customize around those use cases with the right chip sets and ultimately, the right AI factories.
John Furrier
>> Nvidia had a special event. A GTC, which is their main conference, which is next month here. Not here, but in San Jose. But they had one in DC a couple months ago. And they announced the Nokia relationship around 6G, but there's some other things going on. I had some briefings from the Nvidia folks. It's clear that they're coming out with some reference architectures. So, Nvidia sees AI, their AI. Basically, I call it Nvidia. They're bringing the AI to the edge and in my opinion. They can see the tell signs AOA. They kind of talk about it, but they talk about Nokia 6G. But if Nvidia is AI, they're bringing AI to the network. How do you see that evolving and how are you thinking about it with Veea? Because you've got the network architecture, you have your radios, wireless, access, device, multifunction. Are you thinking be ready for the AI factory? Are you building it that way? How are you viewing your vision?
Allen Salmasi
>> Yeah. We are completely aligned with that vision that Jensen articulated at GTC in Washington, D.C., and discussed it on the panel or on the stage with Nokia. Effectively, they developed a Open RAN type of architecture roughly about four years ago, that was first tested by my colleagues at Vapor in Las Vegas. And what they've done since that trial, they have completely opened it up and made it open source. So, effectively, we are piggybacking off of the work that Nvidia had done on Open RAN, to extend it all the way to the edge. Because when you get into terahertz range of frequencies, now effectively every room, every small room is going to have some type of a radio head. So, it's fully distributed in terms of radio communications, but that has to be aligned with... completely in sync with a distributed compute type of capability. So, our architecture supports a compute mesh, as well as microservices mesh on top of this radio.
John Furrier
>> So, the radios are forming their own networks, architecture-
Allen Salmasi
>> Exactly....
John Furrier
>> compatible with where factories are going?
Allen Salmasi
>> Exactly.
John Furrier
>> Is that what you're saying?
Allen Salmasi
>> Dynamically and real time.
John Furrier
>> Okay. So, I know Cole Crawford, who's your colleague, you mentioned that head Vapor is working with you. He and I have talked about on theCUBE, securing the network in a post-agentic AI world. Now, agents are coming, so you got agents working. How do you see that playing out? Security, all those things, throughput with compute and security with the radios.
Allen Salmasi
>> Right. That's essential. So, that's the second element of this structural change that we see at the macro level, because effectively you have communications, and cybersecurity fully intertwined, and integrated as one fabric. And is totally embedded into all of the connections that you make on a zero trust basis. Because frankly, unless you can trust the AI agents that you're connecting to, you are not going to really have physical AI introduced at the edge.
John Furrier
>> I have to ask you, since you're here, since you're an expert, one of the things about AI effects that got my attention right away was the fact that they really focused on networking. Networking as the key to success of bringing all these interconnects together, these resources. You're in the networking world. I mean, you get radios, you got the edge. What's the opportunity for telecom and Nvidia? And how do you see your relationship with Nvidia evolving?
Allen Salmasi
>> Right. So, I really believe that this is a huge opportunity for telcos to effectively come out of this dump pipe type of service offering, and really provide for a lot of value added into the use cases that are running at the edge. And effectively for that, there are a number of architectures that they can integrate into their telco infrastructure, especially given the fact that we used to have these huge SS7 switches at telco aggregation points, that are no longer the case because the core network has shrunk into smaller racks of equipment. Now, they have a lot of facilities.
John Furrier
>> So, their network access points are going to be very compatible with compute?
Allen Salmasi
>> Absolutely. This is a huge play for telcos to effectively introduce-
John Furrier
>> And they got the data and they got the network, so they shouldn't make money on this.
Allen Salmasi
>> Absolutely.
John Furrier
>> If they don't, they're idiots. You can't say that. I can.
Allen Salmasi
>> I'm sure there are a lot of smart people thinking about it.
John Furrier
>> Well, I'll be banging my fist at MWC, because they missed the wave with the cloud. Telcos cannot miss this wave. Do you agree?
Allen Salmasi
>> Yeah, I totally agree with you. And they have the facilities, they have the cooling, they have all the wiring in these thousands of locations that are referred to as telco aggregation boards. But it's just really a question of how they architect it and how they effectively integrate that into their existing infrastructure.
John Furrier
>> Well, Allen, deals are happening here on theCUBE. You're getting all kinds of phone calls. I have to ask you to wrap up. I know we got a tight time today. I'm glad I could squeeze you in. I really wanted to talk about the edge. Talk about your business, your vision, what's new. Give a plug for you what you're working on.
Allen Salmasi
>> So, we announced a supply agreement with America Mobile and their subsidiary, Telcel back in August of last year. And we had nine million revenue the year before, but we totally pivoted to focusing on businesses that can scale very rapidly, primarily through telco partnerships. So, Americsan Mobile is the largest operator in the world at the moment, with Telcel, Telmex in Mexico, Claro throughout Central and South America, and A1 Networks in Europe, 200 million subscribers. And what we have brought to the edge of their network is fixed wireless access with cybersecurity, AI driven use cases and applications, including surveillance cameras, a number of IoT solutions all bundled into one small device, roughly about the size of a Apple TV.
John Furrier
>> So, the new radios are going to get smaller, connect to systems with compute, connect these aggregation points with this power, cooling? So, the infrastructure's there for all the telcos and all the providers?
Allen Salmasi
>> Exactly. Right. Absolutely.
John Furrier
>> Allen, great to see you. Thanks for coming on. And I really think what you're onto is super relevant. The hyper-convergence at the edge will happen. It's obvious. The question is, will the incentives be there? Will people figure it out? Will the companies align around data centric architectures that are AI enabled with AI factories or equivalent devices? I mean, DGX box is this big. That's AI factory, in my opinion. And you're seeing startups already doing that now with their AI on their desktops. They're already buying-
Allen Salmasi
>> AGX store with two pedaporms of AI acceleration.
John Furrier
>> The new AI factory PC is coming. It's here.
Allen Salmasi
>> Exactly.
John Furrier
>> Thanks for coming on. Appreciate it.
Allen Salmasi
>> Really appreciate it. Thank you, John.
John Furrier
>> Again, the wireless is a key part of the network at the edge. Networking is what makes AI factories work today. And there's plenty of networks in the edge, a lot of data, a lot of use cases. It should be an explosive area of opportunity, wealth creation, value creation and extraction, all going to be happening at the edge, I think in the next 12 to 24 months. We're doing our part to keep an eye on that. I'm John Furrier. Thanks for watching.
John Furrier