In this candid conversation, Lee House, Founder & CEO of IoT83, sits down with media communications leaders Joel Miyazawa and Marley Peters, joined by Ankush S Rana of IoT83. The discussion covers Lee’s journey, the evolution of IoT, major industry paradoxes, what makes IoT83 different, and practical insights for OEMs embarking on digital transformation.
Ankush Singh Rana: Welcome everyone, we have Lee House, Founder & CEO at IoT83. Today, we’re here to discuss two main things: to learn more about Lee’s professional journey and to identify stories that resonate with his experience working with global OEMs and enterprises. Over to you, Lee, and welcome to the Coffee & Connected Things!
Lee House: Great to meet you all. I’m looking forward to this conversation. We have a great product Flex83 as an IoT middleware platform. Now it’s about creating a drumbeat and solving more complex challenges faced by OEMs.
Joel Miyazawa: Thanks, Lee. I’ll quickly introduce myself. I’m Joel, the head of marketing at dontbealittlepitch, working closely with Ankush. Marley is our campaign director, making sure everything stays on track, and we get the best coverage for your IIoT story. We have some questions in the queue and are eager to get your perspective on IoT macro trends and how IoT83 is solving the real-world challenges.
Lee House: You guys are the pros here—Just let me know how should we proceed?
Joel Miyazawa: We’ll start with some background and run through a set of questions, aiming to draw out both industry insights and IoT83’s positioning. Marley, anything to add?
Marley Peters: No, that’s perfect. Let’s dive in.
Joel Miyazawa: Lee, could you share your journey in the connected systems space and what led to the founding of IoT83?
Lee House: My background goes back to the SCADA era—Supervisory Control and Data Acquisition—back in those days we weren’t calling it IoT, where I worked on hardened industrial edge devices. At GE, I was involved in business turnarounds and major IoT initiatives, including their big monolithic Predix system. These platforms worked well if you were already deep in that ecosystem, but for most OEMs, they were too rigid and expensive.
I was having conversations with our other Founder and CTO, Deep Nayar, and as we observed IBM, Siemens, Hitachi, and others rolling out mega IoT solutions, it was clear there was a gap for OEMs and enterprises that needed scalable, reliable, secure, yet predictive insights into the IoT platform. That’s what led us to form IoT83—democratizing enterprise-grade IoT, but with real cost, risk, and time-to-market predictability.
Joel Miyazawa: What did you see as the biggest gap in the market, and how has the ecosystem evolved?
Lee House: After the “mega IoT” era, hyperscalers entered with IoT-as-a-Service, which helped people quickly prototype but didn’t solve the hard problems at scale—like multi-tenancy, robust security, and real application logic. No-code and low-code solutions then emerged, offering faster customization but limited real differentiation. OEMs were left with two tough options: either go custom (with high cost and risk) or choose simplicity (with limited strategic differentiation).
IoT83 was founded to break that paradox. Our goal is to give customers industrial “Lego”—a scalable, secure foundation, reusable building blocks for device onboarding, analytics, scheduling, and more—so they can assemble solutions tailored to their needs without unpredictable cost or risk.
Marley Peters: How did you anticipate the rise of AI and ML in IoT?
Lee House: Since inception, our engineering team was eager to bake machine learning and AI into the platform. We built that into the architecture from day one, even when most customers weren’t ready for it. Now, in the past year, demand for AI and ML has exploded, and we’re prepared—we already have these capabilities deeply integrated.
The lesson is to keep pace not just with technology, but with what customers are ready for. Now, as AI/ML, agentic AI, and large language models converge with IoT, we’re seeing new classes of services emerge.
Joel Miyazawa: How does IoT83 solve the uncertainty and risk that many OEMs face in IoT projects?
Lee House: OEM leaders are bombarded with solutions, but the real competitor is often their own internal engineering team, which gets excited about prototypes. But industry data shows most in-house IoT projects overrun or fail. Our model is different: new lines of code are the enemy. We let customers build on a solid, field-tested foundation, reusing as much as possible. Instead of hundreds of thousands of new lines of code, they might write 8,000—just the surgical customization needed.
This means rapid proof-of-concept (in days), MVP (in weeks), and even a production-ready solution in a few months—versus 18 months for a traditional custom build. We also engage deeply with customers, helping define KPIs and product requirements, and advise them to start small and expand based on proven success.
Marley Peters: You’ve delivered solutions across many verticals. How do you address the unique needs of each?
Lee House: We’re more of a horizontal platform than a vertical one. We’ve worked in smart buildings, utilities, refrigeration, HVAC, logistics, and more. The common need is always asset visualization, optimization, uptime, and predictive maintenance. The first step is always to identify valuable data sources and target business outcomes.
We advise customers: don’t try to boil the ocean. Prove value with a targeted use case, then expand—add assets, new verticals, or deepen functionality as needed. Because you’re building on a solid foundation, nothing is wasted, and growth is incremental.
Joel Miyazawa: How do you explain IoT83’s business model—enabling SaaS for OEMs and Enterprises, but not being SaaS?
Lee House: We license the Flex platform to OEMs and enterprises, who then deploy it on their infrastructure—cloud, on-prem, you name it—and use it to serve their own customers. So, we’re not a SaaS company, but we enable our customers to deliver SaaS solutions under their brand, “secretly powered by IoT83.”
Interestingly, we didn't build Flex83 with low-code or no-code tools; it’s all pro-code under the hood. But we enable our clients to deliver low-code and no-code features—like drag-and-drop dashboards and configurable business rules—for the end-users (their consumer-base), because that’s what they expect.
Marley Peters: What’s your approach to working with customers’ subject-matter experts?
Lee House: We’re experts in the platform, big data, AI/ML, and analytics—but our customers are experts in their own domains. For example, we don’t know the critical failure temperature of oil in a capacitor, but their engineers do. We help translate those insights into scalable models, business logic, and analytics.
Flex83 is fully documented, so some customers move fast on their own, while others leverage our development services. It’s always a partnership—especially early on, as they get up to speed.
Joel Miyazawa: How do you tackle security, especially as the threat surface expands with more devices?
Lee House: Security is fundamental. Whether it’s in factories or fielded devices like power utilities or aircraft engines, a breach could have catastrophic consequences. We insist that nothing connects to our platform unless it’s authenticated, authorized, and encrypted. This applies to everything—from devices to software modules communicating internally.
OEMs understand the stakes, and so do we. We scan for vulnerabilities, enforce access controls, and ensure security is updated continuously. The more devices, the greater the threat, and it’s non-negotiable.
Marley Peters: What has been the biggest challenge in scaling an IoT application?
Lee House: Our first major deployment needed to handle 50 million devices and over 4 million streams for a telecom. Reliability, security, scalability, and cost to run were non-negotiable. That challenge forced us to get the architecture right from the start, and those lessons shaped every iteration since.
Building flexibility into the application layer was the next challenge—we’re now on version six, always iterating, always listening to customers, and staying on the technology treadmill.
Joel Miyazawa: How has working with US and India-based teams contributed to IoT83’s success?
Lee House: My founding team member Deep and I have worked with Indian teams our whole careers. When we built IoT83, it wasn’t just a business decision—it was about passion, trust, and the skills we knew would drive success. Sure, there are late nights and time zone challenges, but our shared commitment to customer success overcomes any friction.
Joel Miyazawa: What excites you most about 2025 and the future of IoT?
Lee House: We’re rolling out new drops (features) of the platform every few months, with more AI, large language model integration, and deeper business integration on the way. Customer demand is aligning with our technical roadmap, and it’s exciting to see our vision becoming reality at exactly the right time.
Also see: Why Industrial IoT Projects Keeps Failing and What Needs to Change
