Konux\u2019s IoT device in situ where it\u2019s able to monitor the condition of a railway switch (Image credit: Konux)<\/p>\n<\/div>\n

Underpinning its products are robust, track-mounted sensors (painted an eye-catching high-gloss yellow) which contain a series of accelerometers that measure force and the acceleration of force onto the rails. This ground-level data is fed into its AI models which estimate what\u2019s going to happen to the tracked component in the near term. (Konux says its Switch product estimates how the condition of switches will develop over the next 90 days, which allows operators to identify early signs of degradation so they can plan ahead for inspections and prioritize maintenance based on actual network usage.)<\/p>\n

\u201cAs you can imagine, you have a few trains which are extremely high stress, high energy, cases that could cripple a network ultimately,\u201d notes Bonnifield. \u201cBy being able to kind of detect the load factor of these trains and their speed and kind of really understanding what\u2019s actually happening \u2014 the underlying ground truth of what\u2019s happening in the network \u2014 this is a game changer for how to manage and operate them because you\u2019re using real data at that point.<\/p>\n

\u201cSo being able to give the people who are heroically operating these networks more visibility into what\u2019s actually happening and lighting up their understanding of what\u2019s going on, and then to make very, very strong predictions as to how they how they should do things differently, these are both the main drivers of where you find that [50% extra] capacity.\u201d<\/p>\n

As well as relying on track-level data captured by its own hardware, Konux loops in other sources of open and third party data to supplement its view of local rail conditions \u2014 such as temperature at a specific location; and visual data from partner companies that operate cameras mounted on trains (i.e. to do a visual check on an asset which its sensors have detected as potentially degrading).<\/p>\n

The goal is for its platform is to be the intelligent processing center that drives smarter rail running by empowering operators to gain network visibility so they can continually make data-driven decisions.<\/p>\n

\u201cUltimately, we see ourselves as an AI company first,\u201d he tells TechCrunch. \u201cWe built an AI company. We built, essentially, a very, very good analytical software company at solving this problem. And then we built the first of its kind sensing device to be perfectly matched to the needs of an AI company \u2014 but we\u2019re totally agnostic; we will fuse data and integrate data with wherever we can find it. Anything that\u2019s valuable. It just so happens to be the case that this sensing problem is an extremely challenging problem. And so we needed to be the first people to solve it. But if we would have been able to acquire the data easily, and there was somebody else that did it, we would have done it a different way. But, you know, we really want to be the brain, not the hands, not the legs, we want to be the brain of the network.\u201d<\/p>\n

\u201cThe goal, of course, is to take what makes these infrastructure managers, these asset owners, expert at what they do, and really make that a bigger and bigger part of their day,\u201d he adds. \u201cSo rather than say you have to actually survey every single asset in your network, we say we\u2019re going to do that for you automatically. Rather than say, when you see a problem you have to actually physically go out and see what the problem was, we\u2019re going to visualise that for you. And we\u2019re going to tell the story of it. We\u2019re going to alert you when there\u2019s a problem and give you even a recommendation if we can \u2014 to make the brainpower of these people as highly leveraged as possible.\u201d<\/p>\n

Konux was founded all the back in 2014, when its founders had the germ of an idea to apply AI in challenging industrial environments. That plucky startup alighted on the railway as its battleground and has since grown into a well-capitalized scale-up \u2014 with some $130.6 million raised to date (including an $80M Series C in January 2021) \u2014 which has tested and deployed products with operators across some ten markets at this point.<\/p>\n

Years of R&D and testing went into developing Konux\u2019s predictive AI models. This included deploying prototypes and trialing hardware across multiple countries and in different railway operating conditions in order to be able to gather diverse enough data to build a model that\u2019s \u201cgeneralizable across basically any environment\u201d, as Bonnifield puts it.<\/p>\n

\u201cThis is one of the hardest things to do because it\u2019s very hard to know if the [AI] models we\u2019re building are overfitting to a specific environment or some specific set of dynamics. So we really still think of the core IP that we built is really this data that we\u2019ve collected \u2014 and the know-how of how to make sense of the data. And then just the overall pipeline that manages it,\u201d he adds.<\/p>\n

While Europe is where Konux has most widely deployed kit currently it has also installed its connected devices on railways in China, India and Japan.<\/p>\n