Building Right-First-Time Fiber Networks.

Hello, this is James Page here at the FTTH Conference 2026 and I'm with IQGeo's Head of Product Management James Wheatley who has been talking on the workshop day here and just come off the stage from a really interesting session that we're going to get into some details of. But James, it's lovely to see you again. Thanks for having a little bit of time to talk to us. James McLean- The session, plenty of speakers, lots of going on, lots of interactions, plenty of questions. It's a tough first question. Are you able to summarize what we've just been watching? Yeah, sure. So, the workshop we put that together with Cyclone Media, IQGeo and Expo. We were focusing on how the quality of the data in all of the processes that you're supporting is absolutely fundamental and critical. And so you can, through the whole network lifecycle, through your planning and design of the fiber network, through to the construction and finally the operation of that network. James McLean- If the data that is underpinning the operational processes is poor or there's errors in that, then those processes will fail. That's unplanned work. It's fallout. It's cost overruns. So, each of the three different organizations were highlighting how their particular expertise and capabilities can help solve some of those challenges. And the thing that we really focused on was how we do that together. So, we integrated that whole thing together and through IQGeo, if you like, as a hub for both parts of the Cyclomedia Media aspect and the Expo aspect, how that joins together and then delivers value and benefit across the network lifecycle. Yeah. And the technology we're particularly focusing on is visual AI. James McLean- Which is something which is a fantastic technology used in lots of different formats in medicine and in surveillance, security. But in this sense, we're talking about how it's helping with installations and it's helping with network management. How difficult is it to deploy that technology? And maybe equally important, how easy is it for people to accept and do you have any barriers to accept? James McLean- Yeah, that's a great question. So, from a deployment point of view, as you said, it's quite an established technology now. We've been doing this for a good number of years. So, we're building on a lot of knowledge and history there. And the important thing is ability with trained the models. So, you're not starting from scratch. This is all trained already. So, it's very quick to deploy from that point of view. James McLean- One of the key things though, as you say, is acceptance. So, particularly from the engineer in the field, if visual AI is checking their work, James McLean- It's like, it's kind of the big brother over your shoulder. Are you really comfortable with that? And we have a number of approaches that we take to do that. So, we can run existing images through our AI and determine how good or bad the existing images are. We can process things in the back office to start with before exposing it into the field engineers. And then critically, we can show to the field engineers how it helps them do their job. So, that's the key thing is to really engage them in the process, Not make it a barrier for them, but make it something that helps them do their work. If they can see the value of actually doing the job right first time, And not having to get dragged back onto site a second time because they missed some small aspect that they needed to do in the job. That's a real boon for them. They can move on to the next job and obviously get paid. And that's what they're really interested in. Okay. So, some important incentives there all around. Yeah. I suppose the importance of having that real -world intelligence where we need to get to, Maybe you can tell us what needs to happen to make sure that that is actually driving, making decisions, James McLean- and driving some actions rather than just adding more information and giving you a prettier dashboard. James McLean- Yeah, yeah. So, just more data for the sake of more data is not, you know, that's not the end game. The end game is to be able to automate as much of these processes as possible. And clearly with AI, that is within reach to be able to do that. But if we don't have that foundation of the quality of the data there, then those processes are still going to have issues. They're still going to have fallout. James McLean- Worse, you might not actually know because the thing is just, you know, in a closed-loop environment and running. So, being able to make sure we've got this concept of a continuously updated inventory, we're using not only visual AI, but we're using other data sources about the network, how the network is performing. James McLean- And I think, you know, we heard in the workshop, the important thing is that all of that information is connected together with the inventory. So, you really need to understand the context of that data in the context of the network. And that's what network inventory, you know, as IQGeo provides can give you that context and build those operational processes on top of that. Yeah. And as you said, there is sometimes maybe a lack of trust or lack of understanding of that network inventory. James McLean- And yet that is absolutely critical, being able to understand it and being able to have that sort of continuous, accurate network model is absolutely critical for being able to use the AI and getting to the autonomous state we want. Exactly. So, that's the end objective is to support operators getting to that autonomous network view, achieving that level five autonomy and that physical inventory aspect to that. And what we support with all the processes on top of that, as we talked about with planning and design through construction and into operations. And clearly, as the shift to adoption and increased operations of these networks, that's where a lot of the real value will come from. So, we'll really drive some of those processes and some of the automation in the closed loop environment there. Particularly with the workflow that, you know, there will still be field workers doing work. So, we want to enable them to be as efficient and as effective as possible. And all of the other activity that can all be handled in time through, you know, through AI, through autonomous networks. Yes. What I thought was really nice in the flow of the workshop session was you did pull it down to the actual practicalities. And there were some great demonstrations of how this works practically. James McLean- When this is all in the right place, when we are where we want to be, which isn't that far away, what are going to be some of the benefits? What's going to happen in terms of deployment costs? I think critically, the quality of experience for the end user. Yeah, yes. I think that's that last point, the quality of the experience for the end user. I guess we've all probably experienced situations where we said we had to take a day off work to go get a new broadband solution, broadband provider institution. And then for whatever reasons that you don't understand as the consumer, unfortunately, it doesn't happen. As a simple example, that's what we want to eliminate. So we just want to get to the point where as the consumer, you've ordered your service. It's all flowed through all the back office systems. There's no human touch involved in any of that. All fully automated. And the data to drive all of that process is there. It's to the right quality level. So that when the field engineer does come to do the installation, everything is all there. The port that he's going to connect to is free. He understands what the drop is going to be. He knows all the data that's going to be required to do that. And most importantly, once he's finished the work, all of that information that he's captured through his process, He maybe hasn't had to do anything. He's just taken a couple of photos and maybe captured some voice notes. And that's all seamlessly flowed back to the inventory and is there to support the ongoing operational processes Should there be any issues in the network later. So that's just one sort of simple example. You can extrapolate that to lots of other scenarios as well. A very important example. All right, great. Well, thank you for explaining that. There was a lot to pack in this morning. I'm sure if people want to find out more, they can. You have an exhibition stand here at the event and there will be plenty of But James, thank you so much for explaining all of that. Thank you. James McLean- Thanks very much.