Konux gears up to scale its AI + IoT play for optimizing the railways - TechCrunch

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Konux gears up to scale its AI + IoT play for optimizing the railways - TechCrunch

Unless you’ve been on an extended digital detox this year, you can’t have missed how a certain flavor of AI hype has been accelerating down the tracks like a runaway train. But far from the viral buzz swirling around developments in generative AI tools like ChatGPT and DALL-E, Konux, a Munch-based deep tech AI scale-up, has been quietly trucking along applying machine learning to transform transportation on the railways. It’s building out a SaaS business powered by proprietary sensing hardware and AI that drives a predictive maintenance software-as-a-service play which is upgrading railway infrastructure, one switch at a time.
Its mission is to drive digitization and transformative change atop what remains the most sustainable mass transit option humanity has — rail travel — using AI plus IoT (Internet of Things) to add intelligence to fixed rails by capturing real-time data on what’s happening on and to the railway network.
It’s doing this at a time when rising demand for train travel as consumers look for ways to reduce their carbon footprints is fuelling a push by governments and railway operators to digitize networks and transform established ways of working with the help of new technologies. That’s creating opportunities for startups to roll up their sleeves and get their hands dirty, although Konux reckons it was first to the punch. (And no surprise it was founded in Germany where the question of whether trains are running well and on time is a perennial political issue.)
“The core problem is something that actually is a dirty problem,” says Konux CEO Adam Bonnifield, discussing what makes this AI business different from the ones hogging most of the global limelight right now. “It’s not one of these clean, AI model-building totally digital problems. It’s the dirty problem of getting sensors to survive the environment, extracting the data, making sense of it, fitting it within the business problems, with the customer, and then bringing along the organisation on a journey through a bunch of organisational changes.
“These are the problems that make your change impactful and leave a legacy behind, I would say.”
Unpacking Konux’s business a little more, it’s using deep tech methods and stress-tested connected hardware to gain visibility into the loads and forces railway lines are accommodating day in, day out — measuring vibration through the tracks to pick up anomalies that may signify failures incoming — and then presenting its probabilistic analysis of what’s going to happen to the infrastructure over the next few months. Its AI-driven predictions were developed to a 90% accuracy standard, per Bonnifield.
The customers for its technology, railway operators, receive predictive maintenance insights delivered in an accessible software interface that’s designed to take the strain out of running vital infrastructure. No more flying blind with scheduled guesswork; track-mounted sensors and machine learning models aim to empower operators to make smarter calls around maintenance, underpinned by what are now “billions” of train traces recorded over a decade or so of Konux’s team attacking this data problem.
At the passenger end of the line (assuming successful implementation of the tech and use of the tools), this application of AI should manifest as reduced service downtime and fewer delays. So forget sloppy general purpose AI; here’s a data-play on rails which signals how machine learning that’s tightly targeted at a specific problem can be the truly impressive feat of engineering.
In addition to predictive maintenance, Konux’s AI + IoT approach supports rail operators with further business intelligence around network traffic and usage; plus — more recently — support with scheduling. Currently it offers three products; the aforementioned Konux Switch (predictive maintenance); Konux Network (usage monitoring and inspection planning); and Konux Traffic (smarter timetabling).
The idea is to leverage AI and IoT to power data-driven decisions that can drive optimization around other aspects of rail operation, expanding out from Konux’s first focus on tracking infrastructure stress at key points on the network. (Switches being both essential for routing train traffic around a network and vulnerable to failure, given they are mechanism...