From Telemetry to Intelligence: What Cumulocity’s IIoT Platform Actually Does
(Our topic. Our tone. Sponsored by Cumulocity *)It’s episode 50 (🎉) of the podcast, and we’re only now getting to IIoT platforms. We sat down with Jürgen Krämer, Chief Product Officer and Managing Director at Cumulocity. Cumulocity is an IIoT platform with currently more than 25 million connected devices, three billion messages processed per day, and a roster of customers that includes wind energy operators, healthcare devices, and crane manufacturers.Jürgen has been in the IoT and analytics space for over 20 years, which means he’s lived through every wave of the hype cycle and that made our conversation another super interesting one! He also knows that the term “IoT” is notoriously elastic: it gets applied to everything from smart lawnmowers to offshore wind farms, and that ambiguity is a genuine problem when you’re trying to make a technology decision.So time to demystify some concepts around (I)IoT Platforms!IIoT Platform vs HistorianWe’ve written before about the power of the process historian, and in a typical manufacturing or process plant, the historian is genuinely well-suited. It is designed for high-density time-series capture in a controlled, physical environment where you own the network, the devices are close together, and the architecture is well understood.The moment you move to distributed assets out in the world: in customers’ facilities, on wind farms, on construction sites, in buildings, data centers, and so many others… the picture changes entirely.Because in those cases, you don’t own the network. You have no physical access. You’re managing connectivity across 30,000 turbines in a dozen countries. Firmware updates need to happen over the air. Security is paramount because the device is sitting inside someone else’s infrastructure.That is where the IIoT platform becomes the right tool. As Jürgen puts it:“You need to connect and manage devices you don’t control, in environments you’ve never seen, at a scale that makes manual management impossible.”The M2M → IIoT → AIoT evolutionTime for a history lesson!The first wave, around 2010, was M2M (machine-to-machine). It was essentially about connectivity: get the device online, manage the firmware, enable remote access. Useful, but narrow.The IIoT era, roughly 2015 to 2024, added the layer above: dashboards, analytics, edge computing, application enablement. Operations became more optimised, but the work was still largely human-centric. An alert would fire, and a technician would spend hours diagnosing the situation (reviewing log files, cross-referencing documentation, forming a hypothesis).AIoT (what Cumulocity now positions itself as) is the next step. The vision is that the agent does the diagnosis. The technician receives a package: probable bearing failure on Pump 4, replacement part ordered, repair guide attached, shutdown recommended at 14:00, awaiting your approval. The human is still in the loop, but the cognitive labour of diagnosis shifts from the person to the system.We’ve used the term “virtual operator” in previous articles. This is what it could look like in practice (obviously given the availability of enough data, context and the right understanding of the physical reality!)The part most people still skip: ContextContext is the most important thing to get right today. It’s the answer to scaling, it’s the answer to UNS, it’s a necessity for AI. And thus we’d encourage you to slow down here.Every AI initiative in industry eventually runs into the same wall: raw telemetry is not enough. A value arriving every second from a sensor labelled “Reg_004” means nothing to an LLM, and very little to a human who didn’t configure that tag. Feed that data stream to an AI agent without context, and you will get hallucinations. Jürgen’s team has run this experiment directly: same query, without and with a semantic layer. Without it: plausible-looking KPIs that are simply fabricated. With it: accurate, actionable results (take a look at the result in this video).What does context actually mean here? Jürgen describes three layers:* The first is the system of record — the secure, scalable, mission-critical foundation. This is not exciting, but it is load-bearing. You do not rebuild it from scratch.* The second is the semantic layer. This is what makes industrial data AI-ready. It includes the metadata (is this temperature reading in Celsius or Fahrenheit? what are the normal ranges? when was the sensor last replaced?), the alarm history, the maintenance documentation, and critically: the asset hierarchy. This sensor belongs to this component, which is part of this pump, which sits in this production line, in this plant. Without that hierarchy, you cannot roll up to a meaningful OEE calculation. Without that context, the AI agent is just pattern-matching on noise.* The third layer is the agentic layer — where the AI agents operate, with access to the semantic layer as their knowledge base.There is a parallel here worth naming. We’ve argued for years that industrial DataOps — getting data clean, contextualised, and accessible — is foundational work that pays off for humans first and AI second. Jürgen made the same point: companies that invested in a proper semantic layer years ago, for human operators, got a head start. They built the infrastructure that now, with AI on top, is worth considerably more than they probably expected.Should you vibe-code your own IIoT platform?The short answer is no. The longer answer is: it depends what you mean.David raised the question that’s circulating everywhere right now: with AI-assisted development, can’t we just build our own platform? It’s a reasonable thing to ask, given that a motivated developer with a good LLM can now scaffold something that looks functional in a weekend.The problem is in the word “looks.”The system of record layer — the part that manages tens of thousands of devices, handles over-the-air firmware updates, maintains security compliance in a post-NIS2 world, and operates at 24/7 SLAs — is mission-critical infrastructure. Generating a million lines of code with an AI framework and then being responsible for operating it against contractual uptime commitments is not a viable strategy. As David put it: “Who takes responsibility when things go sideways — not just on availability, but on cybersecurity and supply chain risk?”Jürgen’s distinction is worth keeping: AI-assisted development is genuinely useful at the application layer — building custom dashboards, tuning models on your own data, accelerating vertical use case development. It is not a substitute for a proven platform at the foundation.We’ve watched this cycle before. The Excel macro era, the Access database era, the no-code/low-code era — each one produced a generation of fragile, undocumented tools that someone had to maintain long after the person who built them had moved on. AI-assisted development is the new version of this pattern. Some of what gets built will be excellent. Much of it will become technical debt.The strategic question remains the same as it always has: where does your competitive advantage actually live? (Probably not in having built your own secure, scalable data foundation from scratch)Finding the right use case is harder than it looksCumulocity has seen hundreds of deployments — predictive maintenance, asset performance management, remote service operations, cybersecurity compliance — and the consistent failure mode is enterprises that start by playing with the technology rather than by defining the business outcome.The right starting point is not “what can we do with AI?” It is “where do we get the most leverage from our investment?” Those are different questions, and the second one is harder to answer without experience.Cumulocity is offering a free one-day consulting workshop for organisations that want to identify their best starting point for an AIoT journey. If you prefer to get your hands on the platform directly, there is also a free trial at cumulocity.com. On our side, the workshop assessment framework we use in our own engagements is available at itotinsider.com.About CumulocityCumulocity is the leading independent AIoT platform, built to bridge the gap between IT and OT. We empower equipment manufacturers and distributed asset operators to securely connect, manage, and extract value from millions of devices on a global scale. From remote device management to industrial DataOps and AI-ready semantic models, Cumulocity provides the mission-critical foundation needed to turn raw telemetry into actionable intelligence; and securely close the loop by executing remote commands, updates, and automated actions right back at the edge.Stay Tuned for More!🙋 Join the ITOT.Academy (new cohort in September) →📘 Pre-order the IT/OT Handbook (+ claim the bonuses!) →Subscribe to our podcast and blog to stay updated on the latest trends in Industrial Data, AI, and IT/OT convergence.🚀 See you in the next episode!Youtube: https://www.youtube.com/@TheITOTInsider Apple Podcasts: Spotify Podcasts: (*) At the IT/OT Insider we do value our independence and transparency. So as we look for ways to pay the bills we were looking for ways to work with sponsors without giving up on those principles. This is where the idea of sponsors comes from. Together with a few selected sponsors we’ll explore some topics that we both find interesting in the same way we write our normal articles. In the coming weeks you’ll find a couple of pieces that have been sponsored. Feel free to contact us if you are interested in a partnership as well. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit itotinsider.substack.com
