In case you didn’t see it yet, we published our latest Internet of Things Application Enablement Platform Middleware Market Research Report recently. You can check the key findings from here, after you have recovered from the inevitable awe of witnessing a total of eight upper-case nouns in a row. I’ve understood that I can finally call myself a proper industry analyst when I pull off a full ten without batting an eyelid. This time round it was within my reach, but that humble “of” in there disqualified me.
Besides displaying a questionably liberal attitude to nouns and their capitalization, another vice that the people of my trade are known for is excessive segmentation of the markets we cover. We analysts have to conceptualize, summarize, and generally package our research and thinking, which on the downside sometimes means that certain solutions, vendors, and even emergent trends may go unnoticed if they don’t fit in neatly to the identified market segments. What makes this segmentation bias problematic is the fact that in real life many innovations are developed as a solution to a specific problem that the involved team has experienced first-hand, rather than as a response to any analyst’s intellectual landscaping exercise.
So there’s a mismatch. Moreover, there are also two factors in play that are exacerbating it. First, the physical-digital convergence represented by the IoT is making the scope of technology “problems” much broader than it used to be. And second, solutions to them are nowadays more often than not created by companies that are relatively young and/or small, instead of corporate-level players with large marketing budgets and dedicated AR functions. What this then means to analysts such as me is that we need to (a) learn to think outside our segment boxes, and (b) do more legwork when mapping out the relevant innovators. Here at ABI Research we’re making a conscious effort to do exactly that.
Yet let’s cut to what I was planning to blog about in the first place, before making a conscious effort to derail myself into the emergent segment of self-promotional rambling. I’d like to highlight three vendors that play a promising role in different parts of the IoT software stack. What they all have in common is that they have a strong focus on solving an application enablement problem that is not being effectively addressed on the actual platform level. For me personally, they're also a segmentation headache, but that is an adversity I must overcome alone.
- EVRYTHNG – digital identity management for physical products: Evrythng is a vendor we’ve been following for a while now, and what originally caught my attention in it was the founding team’s view of a connected product as a touchpoint-style continuum, with multiple stakeholders (e.g. manufacturer, retailer, marketer, end-customer) interacting with it throughout the product lifecycle. Importantly, the connectivity opening up such interactions doesn’t need to be perpetual or even regular, with also the more intermittent kind, via e.g. RFID and NFC, already going a long way. Evrythng’s software engine has been purpose-built to manage each product’s identity as well as the associated metadata and controls.
- PrismTech – data sharing for industrial environments: PrismTech supplies data distribution service (DDS) middleware, positioning it as a layer to address the interoperability issue that holds back many industrial-scale IoT deployments. These deployments tend to involve multiple vendors and different implementations, which is an opportunity for a third party that can standardize the format of the data that the machines within the system are producing. For comparison, if MQTT – which is currently enjoying a decent level of interest – is known as a standard to drive device-to-cloud messaging then DDS could be best described as its equivalent for device-to-device, edge-level communications.
- PubNub – data streaming network for smart devices: Initially, PubNub used to be involved in managing notifications from smartphone apps, but as of late they have pivoted to the newer sort of smart devices, such as connected cars and home-automation equipment. These kinds of devices generate continuous streams of data, and PubNub’s goal is to serve as a sort of CDN that ensures the real-time delivery of such streams into the enterprise’s backend. Having real-time data, in turn, enables more resilient or sophisticated applications; for instance, a taxi service’s app can display a dispatched vehicle’s accurate location, instead of one showing where the car was e.g. 30 or 60 seconds ago.
