The Exchanges

Q Okay, and so what happened when you first sat down with the DLC team to figure out how you were going to put this together and operationalize it for them?

A As a new technology company, one of the things that we wanted to do was help utilities make that transition into more of a cloud-based Computing situation, right? So when you think about large enterprises over the past couple of decades, many of them have moved from more sort of traditional on-prem architectures to cloud-based architectures, even entities that highly value security. For example, the Department of Defense uses cloud-based computing now, and so we were, in hindsight, a little bit naive about the fact that we could do a cloud integration and provide this data to them, and they would Find a way to put that into their EMS and use it in, in their day-to-day grid operations. Um, I remember the meeting that we were in when we proposed that type of an approach and the wind kind of coming out of the sails in the conversation because they recognized that the cybersecurity standards that they have around their control room was really not going to jive well with a cloud-based approach. And so they are required to meet standards known as NERC-SIP, Which provide reliability standards around cybersecurity. And the control room is a highly secure environment that typically does not talk to the internet, does not like to bring in data from the outside world. You know, we had done a lot of our homework. We'd even brought in outside consultants to kind of check the robustness and …

AI assessment note: “I remember the meeting that we were in when we proposed that type of an approach”

Q first, where basically you have done so many deployments and you're so familiar to so many utilities that it becomes just a matter of course for utilities to start working with you. So can you talk a little bit about that transition? When was the first time that someone said, We want to put your system into operation, and we don't need to do a sort of initial pilot phase.

A I believe that was in 2023 when Avangrid in New York State signed a project with us, and the project from the initial get-go included operationalization, very much to the point you're making. That was a pivotal moment for us because it showed us what a buying motion for this kind of technology might look like going forward, where we don't necessarily have to To do a pilot for each individual utility and that there's enough proof points out there that the technology is trusted and we can move straight into operationalizing. Now, I don't want to overstate that. There are still very much utilities that want to prove it out for themselves, but we are starting to see that the validation is taking place within the industry at a larger scale. And one of the things that's nice about how utilities think is while they Do tend to move slowly initially. They're also not in competition with one another, which means that when they do find something that works and is repeatable, they talk to one another and they want to know about those successes. And when they see something working, they'll start to do it too. And that's when you start to really start to see kind of that hockey stick growth of utilities talking to one another and adopting a technology at a much greater scale. And I think we're starting to Uh, enter that type of a situation right now where DLR is no longer this thing that is …

AI assessment note: “I believe that was in 2023 when Avangrid in New York State signed a project”

Q first big test, what he learned, and how LineVision worked its way out of utility pilot hell. Okay, so you're ready to operationalize the technology, um, and you've got a utility who's interested in doing this. What was kind of the business case or the reason that the utility ultimately wanted to move from just using your technology from a visibility perspective into using it to actually make operational decisions?

A Right, so usually there is a pressing business problem that the utility executive cares about, and increasingly the one that we see Most often is around load growth when there's potentially new commercial load growth happening in their service territory. The last thing they want to do is to say, you know, we don't have that capacity. We're essentially turning you away. That's a very bad look for utility. And so they really are looking for what tools they have in their tool belt to bring more capacity to bear and be able to incorporate that load into their operations. So that's really tends to be the kinds of things that they look for when making that decision of we've got these technologies that have been Proven out in a pilot situation, but now that we've done that, we actually know that this could help us with the real problems that we care about. Let's take that next step to operationalize and start incorporating it into the day-to-day operations of the grid.

AI assessment note: “increasingly the one that we see Most often is around load growth”

Q was actually going to become a part of the utility fabric was really challenging. So tell us a little bit about what your experience has been. Have you seen that repeated across utilities? And if so, how do you manage that? And who do you talk to? Like, who's in the room first? Who do you bring in later? How do you, how do you think about managing that challenge?

A One thing that we've recognized is that at the end of the day, utilities are not going to adopt something because a pilot was successful in and of itself, nor are they going to adopt it because the technology is interesting or cool. They are going to adopt it because they would have real challenges that they are trying to solve, and the technology that you're trying to sell to them is able So when we think about how we made the transition from that pilot phase to the operational phase, it really is about understanding what those challenges are and making sure that we've connected the value that the technology can deliver to what those executives care about. And then once you're doing that, then they can look to those innovation teams or those pilot projects that were done to get validation from those technical stakeholders that have set that can essentially give them the green light and say, yep, We know that this works from a technical standpoint. You're essentially checking that box, right? If you care about the value proposition, then you want to know, does the stuff work? And if you get that checkbox from your technical stakeholders that you trust, you can move forward with that business case conversation, and that's when you start getting into, um, that broader conversation.

AI assessment note: “how we made the transition from that pilot phase to the operational phase”

Q so let's talk about how that came about. Who was your first partner who was willing to jump in on this with you? And what did the conversation first look like when you sat down to talk about what it was going to take to move into this mode where now you're not just looking at what's happening on these lines, but you're making control room decisions with that information?

A Yeah, the first company to officially move forward with operationalizing was DLC, Duquesne Light Company in Pennsylvania, and they really were motivated to do this because they understood where the puck was headed in terms of building a grid that had end-to-end visibility, and they recognized the story around resilience, reliability, increased capacity, lowered cost to ratepayers. They were one of the more visionary utilities that understood that Without the use of data and sensors and technology, we're never going to be able to make that transition to a much smarter grid. And so they really took that first step of saying, you know what, we're not just going to use this as kind of a read only nice to have kind of information. We're going to take that next step of integrating it into our operations so we can actually demonstrate that value for real and candidly just be a leader in the space that other utilities can look to to say, look, this is actually being done in the real world. Maybe we can try it too. And so DLC, as one of those early customers, really gets a lot of credit for being able to think in a forward-looking way like that and really make something happen.

AI assessment note: “the first company to officially move forward with operationalizing was DLC, Duquesne Light Company”

Q still have paper maps of their transmission systems. Others have everything fully digitized. So what are some of the biggest differences you see among utilities, and to what extent are you adjusting your product or your business model as you get to each one? Does it tend to be something that you really have to think about and cater to, or has it not been that way for you all?

A The utilities that we work with the most tend to be the larger investor-owned utilities, and they do have a lot of this information that Available. However, even within that subset of the market, there certainly can be a range of how up to date the record keeping might be. And this isn't really to anyone's fault, right? There's over the years, you go through different acquisitions from one utility territory to another, you go through different changes of systems, technology upgrades, what have you. And so you can't necessarily expect that everything is just going to be available at a single click of a button. And so we do try to incorporate that into the expectations that we set both For ourselves and for our utility partners in terms of what the process is going to be. Now, ultimately, everything that we do is much, much simpler than what utilities are accustomed to doing. And so at the end of the day, while it can be a little bit of a pain point to go through kind of documentation around conductor properties, for example, the one thing that we hear from in terms of feedback from our customers over and over again is that it's a lot easier than they were expecting. And there's good reason for that, right? So they're accustomed to doing large capital construction projects that take many, many years and go through all kinds of different approvals. We can install our sensors in li…

AI assessment note: “we do try to incorporate that into the expectations that we set”