Join us as Kayne Grau, CEO of Uptake, discusses how their data analytics company is transforming fleet maintenance through predictive analytics for the trucking industry. By using machine learning models and advanced data science techniques, Uptake is able to predict and prevent truck failures, offering valuable insights and recommendations for maintenance. They analyze data from sensors and telematics devices, reducing downtime and improving efficiency for fleet operators.
Kayne Grau is the Chief Executive Officer and Board Member of Uptake, an intelligence system for industrial assets. With a focus on strategic direction and product enhancement, Grau leads the company in providing AI-driven solutions for asset performance management. With extensive experience in the field and recognition for leadership in industrial IoT, Grau is driving the digital transformation of industries worldwide. Here are a few of the topics we’ll discuss on this episode of Cache Flow:
- Their platform increases driver happiness and retention, as well as technician job satisfaction.
- Uptake’s data science team fine tunes their product to eliminate false flags without missing important failure predictions.
- The company’s focus on transportation is driven by the industry’s lack of production, technicians, drivers, and part availability.
- Uptake collaborates with telematics service providers to complement their hardware and provide actionable data to fleet operators.
- These sensors can detect anomalies and strange behavior, alerting fleet operators to potential maintenance issues.
- The vision behind this technology is to connect every asset in the world, creating a better and more efficient global supply chain.
- They focused on understanding the retail and wholesale prices, as well as the length of time vehicles stayed on dealer’s lots.
- 38:00 – “The data’s like the new oil. You got to be able to, you got to be able to extract it, refine it, and monetize it, right? And that could be for us, or that could be for an enterprise. But the hardest part is a lot of times the very front end of that, how can I get the data out of the source? How can I refine it to understand what is usable, and what is noise? And then ultimately, how do I digest that data to give it to the end user so that they see value that yeah, that it’s difficult to do that.”
- 04:25 – “I’ve had this affinity to probably SaaS, indirectly building SaaS products probably within either marketplaces or building it within consumer products. But I love the SaaS space. I love the ability to be able to shape a product and take it to market and, you know, watch that flywheel catch as they always say.”
- 11:15 – “This idea of once somebody forms like the, the initial first impression is really critical, like that first impression, it’s sort of like an empty ball, you know, it’s a, just a ball of clay that can be molded. And once that first impression is created, it’s really, really hard to undo that. Like there’s kind of like, you know, once you put your, once a customer or a user puts your brand into a box, like it’s really hard to get out of that box. And if the truck driver has like two experiences or even potentially one experience where they get that false flag, they come in, and they’re like, why am I here?”
- 39:31 – “You use one of these like software packages like New Relic and those are like spewing logs as well, like really robust logs. And so just even that, like thinking about how much more data a single software application produces now than it did 15 years ago, just like, you know, kind of like exhaust, I guess like exhaust data just for like existing and running, it’s just like spewing off all this exhaust data that, that is even like mind-blowing a little bit.”
- 27:00- Brian: “A check engine light kicks on. It might be, you know, maybe it’s just like a warning check engine light. Maybe it’s like your engine’s about to blow up, check engine light. But if you can catch those things like three months early when they’re about to go into the shop for regular maintenance, so you can, like, nip it in the bud then as opposed to waiting till you’re on a, you know, 2000 mile haul or something. Like that’s probably the strategy there, right?”.. Kayne: “You hit the nail on the head that that’s exactly right. And it doesn’t have to be a check engine light to come on. The sensor could be firing and showing things that are happening with the truck way ahead of time before that light comes on.”
