Lee House, Founder and CEO at IoT83, lends his visionary insights with a track record of recognizing technology trends in delivering game-changing enterprise solutions. Lee also brings deep operational pragmatism and business growth experience to IoT83.
Lee’s leadership spans GM and VP positions at GE, IBM, 3Com, and various Silicon Valley companies, backed by an MSEE and MBA from Duke University. Lee’s role as a thought leader in the IoT domain positions him to guide OEMs into a future where connectivity and innovation redefine the industrial landscape.
Company: IoT83
We are thrilled to have you join us today, welcome to ValiantCEO Magazine’s exclusive interview! Let’s start off with a little introduction. Tell our readers a bit about yourself and your company.
Lee House: Thank you, Jed. It’s a pleasure to be here. I’m Lee House, CEO of IoT83. I “grew up” at IBM building all sorts of networking solutions, moved to Silicon Valley, working in telecommunications, and then shifted my focus on IoT quite a while back leading to my role as a GM at GE, working on industrial IoT solutions. Really this is what led to IoT83, as it started to become clear that there was a better way to build powerful, flexible, secure and scalable IIoT solutions.
And, at IoT83, our mission from the start has been to fundamentally accelerate and de-risk digital transformation for Original Equipment Manufacturers (OEMs) and industrial enterprises. We do this by providing a unique software model that enables them to own their differentiating application IP, while leveraging our secure, scalable, and pre-built foundational platform, ‘Flex.’ We are essentially helping them leapfrog years of development and millions in investment, allowing them to focus on the unique solutions that set them apart in the market. We’re not just selling software; we’re enabling them to become market leaders in their own right, faster and more efficiently than ever before.
What emerging technology trends do you believe will have the most profound impact in the next 5-10 years?
Lee House: From our vantage point at IoT83, the trends with the most profound impact will center around three converging areas, particularly within the industrial and enterprise space:
1. Hyper-Personalized & Predictive AI at the Edge: Beyond just cloud AI, we’ll see a massive surge in AI models that are trained and refined closer to the data source – on devices and in factory floors. These models will enable truly personalized machine performance optimization, predictive maintenance with near-zero false positives, and adaptive automation. The ability to act on intelligence instantly without roundtripping to the cloud will be a game-changer for efficiency and safety.
2. Industrial Digital Twins & Simulation at Scale: The creation and widespread adoption of highly accurate, real-time digital twins of physical assets, processes, and even entire factories will become standard. This won’t just be for visualization; it will be for rigorous simulation, ‘what-if’ analysis, predictive operational adjustments, and even virtual commissioning, dramatically reducing physical prototyping and downtime.
3. Autonomous Operations & Human-Machine Collaboration: This is longer terim, but goes beyond simple automation. It’s about systems that can self-optimize, self-heal, and make complex decisions in dynamic environments, with humans providing oversight and strategic guidance rather than manual intervention. Think of factories that largely manage themselves, or fleets of industrial vehicles making real-time routing decisions based on live data, all while ensuring human safety and productivity are enhanced.
But for us at IoT83, we are leveraging all of these mega-trends to drive a convergence in IIoT and AI. Our view is that at this point, AI should not be an afterthought, but pervasive in an IIoT deployment. So, our focus is squarely on IoT, but also on pulling the value from Large Language Models, Agentic AI, and ML/AI model building into IIoT solutions that drive powerful predictive/preventative maintenance and dramatic service and service cost improvements across the entire structure of an OEM’s portfolio.
Can you share a specific technological breakthrough from your company that has the potential to reshape your industry?
Lee House: Historically, building an IIoT or AI solution meant a tight coupling of unique business logic with generic platform components. This was immensely costly, time-consuming, and created vendor lock-in. Our breakthrough was the clean, API-driven separation of the ‘Flex Foundation’ and ‘Core Services’ – which includes elements like secure device connectivity, data ingestion, common analytics services, and robust security – from the client’s application layer. We now complement this with source code delivery of our Flex Catalyst Code. This Application layer solution contains a ton of IIoT and AI features that any OEM will need, that can be morphed into a solution that exactly matches their unique and strategic needs – with minimal new lines of code. Taken together this is completely transformative.
This fundamentally reshapes the industry by:
1. Democratizing IIoT & AI Innovation: OEMs no longer need to spend millions building this foundational layer; they can license our robust, maintained Flex platform and focus their entire R&D budget on their differentiating applications.
2. Accelerating Time to Market by Years: We’ve seen clients go from concept to market in months, not years, because they start with a proven, enterprise-grade foundation.
3. Ensuring IP Ownership & Flexibility: They own their unique application code, which is their true differentiator, and can integrate with our cloud-agnostic Flex middleware.
It’s akin to how IaaS revolutionized infrastructure – we’ve done it for the IIoT and AI application layer, abstracting away the undifferentiated heavy lifting so clients can focus on the real value.
How do you approach innovation while balancing the need for practicality and market readiness?
Lee House: Our approach to innovation is deeply rooted in client problems and market readiness. We don’t innovate in a vacuum.
1. Problem-First Approach: We start by rigorously understanding the core challenges our OEM clients face in their digital transformation journeys. This means extensive discovery, ‘voice of the customer’ feedback, and a deep dive into their operational pain points. But, given our years of focus in this market we also make “strategic bets” on where the market is going and invest there, because this is what market leaders have to do!
2. Layered Innovation: Our innovation is two-tiered:
Flex Platform (Foundation & Core Services): Here, innovation focuses on enhancing scalability, security, performance, and introducing generic capabilities that all IIoT/AI applications need (e.g., new data protocols, advanced security modules). This is driven by anticipating industry needs and technological advancements.
Catalyst (Application Accelerators): This layer innovates on reusable components and features that accelerate specific IIoT/AI use cases for our clients. This catalyst, delivered as source code is transformed to fit our customer’s specific needs via re-use of our robust building blocks – making development far faster, improving maintainability, and minimizing the new lines of code needed. Ultimately this “Catalyst” is transformed into their Application IP.
What challenges do you face in integrating cutting-edge technology into existing business models?
Lee House: Because at our core we are a product and technology company, we pretty quickly embrace new innovations, so I see this as an advantage for us versus a risk going forward. As an organization, we try out new technologies all the time in the lab and in prototypes – and if they make the cut, they get introduced into our Flex Platform to deliver new customer value but they have to fit into the real needs of customers – and that is always a litmus test for us.
1. Some OEMs have fairly entrenched processes and can have a conservative culture, especially around operational technology (OT). Moving from a hardware-centric mindset to a software-and-data-driven one requires significant leadership buy-in, cross-functional collaboration, and a willingness to embrace new ways of working. This is often more complex than the technology itself.
2. Also, some OEMs operate with fragmented data systems, often siloed across different departments or even different generations of equipment. Integrating cutting-edge IIoT platforms and AI models requires connecting these disparate data sources, often cleaning and structuring messy legacy data, which can be a big change as well as a big task.
3. In some cases there is also a shortage of talent with the specific blend of operational technology (OT) and information technology (IT) skills required for successful digital transformation. OEMs need data scientists, cloud architects, and IIoT specialists, and competing for this talent is a challenge. We mitigate this for our clients by providing a platform that abstracts away much of that complexity.
4. And Security Concerns are always present. Integrating connected technologies introduces new attack surfaces. OEMs are rightly cautious about cybersecurity risks to their intellectual property, operational integrity, and customer data. We address this head-on by building security into the core of our Flex platform, but it remains a primary concern for adoption.
Our role is to help navigate these challenges, not just provide the technology. We act as strategic partners to help them bridge these gaps.
But maybe even more important – we show them IIoT / AI proven platform solutions that already work and already address these concerns. Often as a first step we build a customer specific PoC that uses their device data and showcases how our Flex Platform – as is – handles all of these concerns. This goes a long way to bridging these gaps.
How do you foster a culture of innovation within your organization to stay ahead in the tech race?
Lee House: Fostering a culture of innovation at IoT83 is central to our DNA. It’s not just about what we build, but how we build and think:
1. It Starts with a Team-Wide Sense of Mission: Where the entire team understands the core IoT83 mission and our goals for the Flex platform – to make creation of context-specific enterprise-class IIoT and AI solutions that are highly secure, reliable, flexible and built for cost-efficiency running at scale – teams can be more empowered.
2. Team Ownership & Autonomy: Our Engineering teams and product owners are empowered to explore, experiment, and own their solutions long-term. This fosters a sense of responsibility and creative problem-solving, but also drives cross specialty collaboration to build complete and valuable platform components.
3. Innovate to Win: Innovation is key to our success, and because inherently involves risk, we encourage experimentation to drive informed judgements about future investments. New technologies or innovations that “make the cut” we invest in. Those that don’t, we learn from.
4. Cross-Functional Collaboration: Our teams work closely with sales, marketing, and directly with clients. This constant feedback loop ensures that our innovation is always grounded in real-world problems and that our solutions have immediate market applicability.
5. Purpose-Driven Innovation: Our team is passionate about the impact we have on our customers and the IIoT/AI industry. This shared purpose—helping OEMs innovate and thrive—is a powerful motivator that fuels our drive to stay ahead and continuously push the boundaries of what’s possible with our Flex platform.
