Episode 294: How Firestory Helps Agencies Predict, Prepare, and Protect with Olivia Breed

Episode notes

How do we turn overwhelming data into meaningful, life-saving action?

Hello Smart Firefighting Community!

Welcome to another episode of covering real world innovations via interviews with fire service and technology industry experts that empower YOU to develop your very own Smart Firefighting strategy.

Recorded live at the Institution of Fire Engineers (IFE) 2025 Conference alongside the AFAC, WAFA, and Australian Institute for Disaster Resilience Conference in Perth, Australia.

In this episode, Olivia Breed from Kablamo shares how their Firestory platform—built in partnership with the New South Wales Rural Fire Service—is helping emergency agencies move from reaction to readiness. Olivia explains how Fire Story integrates multiple data sources into a single view that helps command centers see what matters most, predict fire spread, and make faster, smarter decisions in critical moments.

She also discusses Kablamo’s approach to risk, data prioritization, and the future of AI partnerships in emergency management. From reducing 000 call center wait times to proactively forecasting resource demand, Olivia shows how technology, collaboration, and curiosity can build safer, more resilient communities.

So take a listen to hear what she has to share.

Head to www.smartfirefighting.com to discover how SFF accelerates innovation for emergency responders, to find out when our next event is, or review our curated resources.

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Chapters

1. 0:00 Intro to the IFE Perth mini-series
2. 0:47 Welcome, Olivia Breed from Kablamo
3. 1:59 What an intelligence platform means for operators
4. 3:49 Data overload and automated fire spread prediction
5. 5:42 What is risk?
6. 7:03 Case study: proactive operations with Fire and Rescue NSW
7. 9:52 What's next: AI and partnerships
8. 11:29 Words to live by: just try things
9. 12:25 Wrap

Questions answered in this episode

What is Firestory and who developed it?

Firestory is an intelligence platform co-built by the tech consultancy Kablamo with the New South Wales Rural Fire Service. It brings together data from incidents, truck locations, fuel, weather, field observations, turnout systems, and computer aided dispatch into one platform to help emergency services make better decisions.

Hear it at 1:12

How does Firestory help prioritize incidents across an entire state?

Olivia Breed explains that the platform automates fire spread predictions for every incident, then looks at what homes, power infrastructure, and critical facilities like hospitals and bridges are at risk in the next 12 hours. By comparing risk across all incidents automatically, it prioritizes which fires need resources most, rather than having someone manually sift through 50 different incidents.

Hear it at 4:18

How did Fire and Rescue New South Wales use Firestory to become more proactive?

Olivia Breed says Fire and Rescue New South Wales used 15 years of historical data and correlated it to weather variables. Now the platform looks at weather forecasts and alerts them days in advance of high demand, so they can bring on extra staff at the triple zero call center and stand up the strategic operations command earlier, before a disaster unfolds.

Hear it at 7:19

What impact does advance warning have on disaster damage?

Olivia Breed says insurance companies have statistics showing that 24 hours notice can reduce damage by 30 percent. That advance time lets people move assets out of the hazard path, move furniture up a floor, or get cars under cover, which has a big impact when you are talking about hundreds of millions or billions of dollars in damage.

Hear it at 9:18

Transcript

Machine transcript of the published audio. Names may be misspelled and some sections are missing.

Ep 294 transcript

How Firestory Helps Agencies Predict, Prepare, and Protect with Olivia Breed

Speakers: Kevin Sofen, Olivia Breed

Source: Whisper medium.en machine transcription of the published Podbean audio (no original transcript found in Drive), lightly cleaned. Speakers were separated by voice clustering and then checked and assigned by hand at every speaker change. Gaps where the model returned no usable text are marked [inaudible m:ss].

[0:00] Kevin Sofen: Welcome to our podcast mini-series, recorded live at the Institution of Fire Engineers 2025 Conference in Perth, Australia, alongside the AFAC, WAFA, and the Australian Institute for Disaster Resilience Conferences. With over 28 conversations with fire chiefs, engineers, researchers and innovators, we explored how the fire and emergency community is adapting into a rapidly changing world. From climate resilience and community-led adaption, to the rise of new technologies like satellites, AI, and simple tools designed for the field, to the importance of mental health, diversity, and global collaboration, these episodes highlight the shared challenges and inspiring solutions shaping the future of safety. Enjoy. Olivia Breed from Kablamo, how are you doing today?

[0:50] Olivia Breed: I'm well, thanks for having me.

[0:51] Kevin Sofen: Of course. We also have a range of Tim Tams, if you're delighted that we can wait until the end. I'm still waiting to have one myself, but I also was debating on bringing some Vegemite as well, but I figured the Tim Tams were a better idea.

[1:02] Olivia Breed: Not a good idea.

[1:03] Kevin Sofen: No, I don't know. Maybe I'm just like a silly American thinking they went together, but obviously that's not the case. So what brings you to the IFE conference and here in Perth?

[1:12] Olivia Breed: So we are here with our platform, Firestory. That is a intelligence platform we co-built with the New South Wales Rural Fire Service. So our company, Kablamo, is a tech consultancy. We're based out of Sydney. We have a team over in Canada as well, and we build bespoke digital solutions for enterprise. So we're working in FinTech media, but we have a big part of our business is dedicated to all hazards and working with the emergency services. So Firestory is the platform that we built to serve that need. And New South Wales Rural Fire Service have been a strong partner of ours for the last three, four years now.

[1:47] Kevin Sofen: I gotta admit, Kablamo is one of the coolest company names I've ever heard.

[1:50] Olivia Breed: It is derived from The Simpsons. I don't know if you're, yeah.

[1:54] Kevin Sofen: Wow. Yeah. I mean, I grew up watching The Simpsons. They're one of my favorite shows. Brilliant. So you mentioned all-hazards intelligence and intelligence platform. And while these sound like great words, I'm curious in sort of what does, what does that actually mean? What does that mean for the day-to-day firefighter, the day-to-day fire service operator in some capacity? Give me more intel on that.

[2:15] Olivia Breed: Yeah. So there's a concept in defense. It's called the DQ pyramid. It's basically the maturation from data through information up through knowledge and wisdom. And basically to get through those levels, you're adding things like context and insights. We've sort of adapted that to the emergency services sector and we move through data, information, knowledge, intelligence, and then action. So data is when you're looking at just the raw, this is the temperature or this is the lat-long of a fire. And then when you're looking at intelligence, it's all the way up to based on this fire spread prediction of where the fire is going to be in the next 12 hours, this is the recommended response and where we should put our resources to have this type of impact on the incident. So data is sort of the simplest form and where we start. And it's by bringing all of those different sensors and data sources together into a platform like Firestory that we can create intelligence and then we use that for decision support. So I'm bringing in things like your incident feed, your truck locations, the fuel data, weather, observations from the field, your turnout system, computer aided dispatch, all of that into one platform so that you can find insights across that data and tell people what they need to know before they go looking for it. So there's too much data now to expect people to sit there in a platform for eight hours a day, just trawling through and figuring out what they need to know. We need to automate those processes, give them the data they need to action before they know they even need it.

[3:49] Kevin Sofen: We are overloaded with data now, and our brains are only so big. And especially when you're talking about CAD data, weather data, I'm wearing a smartwatch right now that's tracking location and heart rate. There's all this data, but it is, our human brains can only handle so much cognitive load. So how does your platform work in terms of knowing which data is important, relaying that at the right place at the right time through digital dashboards or text-based alerts, or how do you decipher what data is-

[4:18] Olivia Breed: Yeah, that's a great question. So I guess a good example of this will be a fire spread prediction. So if you're looking at an entire state, so say you're in a state operations command or control center, you might have 50 fires going on at once. It might be a really bad fire weather day. How do you know where to send your very limited resources across all of those different incidents? So by automating a fire spread prediction for every incident then looking at what is at risk from each fire. So looking at the 12-hour fire spread prediction, looking at what homes, what power infrastructure, what critical infrastructure like bridges, hospitals, any of that might be at risk in that 12-hour timeframe. If you can compare that automatically across all of those incidents at once, you can prioritize them in terms of how much risk they present to those assets that you care about and the community at large. So it means that instead of having someone sift through 50 different incidents and try and manually understand which ones are the most risky and where they should send resources, it's automatically prioritized for them. And they're automatically given alerts. So if you're in Zone A, you will be given alerts that you've got a new incident. So instead of having to go in and check periodically, you might receive an email, you might elect to receive an SMS, or you might just receive an in-app notification in the platform. So all of that is customizable, configurable.

[5:42] Kevin Sofen: Working with both the Fire engineering community and the Fire service community, the term risk comes up a lot. I'm curious in your words, and this may sound like a silly, stupid question, but what is risk in your words?

[5:54] Olivia Breed: I think there's people that are much better at working on this and that they've spent their entire careers understanding risk, but it's not just the Fire perimeter or the Fire spread prediction. It's what assets are within that zone. So if you've got 50 houses within the sort of perimeter of that predicted fire spread, understanding for those assets, how vulnerable are they? So if they're all concrete infrastructure, that's very different compared to a bunch of wooden houses or wooden power poles. So it's that vulnerability plus exposure, the hazard, all of those things add up to inform your risk and then how you need to obviously mitigate it and respond to it.

[6:35] Kevin Sofen: Good answer.

[6:35] Olivia Breed: But again, not my area of expertise.

[6:38] Kevin Sofen: Yeah, risk, like the board game. I mean, Mila, thank you for that context. And I mean, I liked how you were talking to just earlier from data to info, to knowledge, and then really all this work that we're doing and the work that you're doing comes down to of how do we take raw data ones and zeros and translate it into something that allows public safety operators, housing authorities, city officials to make a more informed and better decision than before.

[7:03] Olivia Breed: Exactly.

[7:03] Kevin Sofen: And so from where Firestory is now, you know, you were touching on it earlier, but is there any specific case study, like you mentioned with NSW, about how they're using Firestory to reduce risks, to make better decisions, any specific case study that you're allowed to share?

[7:19] Olivia Breed: Yeah, sure. I mean, New South Wales is definitely one example. I might actually sort of switch gears into our fire and rescue pilot that we did. This was recently under funding from the New South Wales Office of the Chief Scientist and Engineer. We worked closely with Fire and Rescue New South Wales. Their goal was to transition to more proactive operations. So instead of waiting for a disaster to unfold and then reacting to it, they want to get ahead of it and know what's coming and what they might need in order to be able to adequately respond and send resources and prevent as much damage as possible, if possible. So what we did with them was we looked at all of their historical data, all of the things that drove demand to their triple zero call center in history. I think we looked at about 15 years of data, correlated that to weather variables. And now we look automatically at the weather forecast as it's unfolding and look for those patterns in the data and we alert them proactively. So days in advance, obviously, weather forecasts are flawed. So you get more accurate forecasts sort of tighter in within that 24 hour period. But this allows them to bring on extra staff to that triple zero call center. And that's hugely important if they want to keep their response times in tight. So, you know, they don't want a call center where you've got 100 people waiting on triple zero, like people call triple zero when there's an emergency. So if they've got enough people in that call center, that's really important in order to be able to respond to people quickly. And the other thing they found that it helped them to do was stand up that strategic operations command earlier. So that's that sort of central coordination when there's a big disaster unfolding, they stand up the SOC. And because they had that forecasted prediction, they were able to say, well, actually, let's not wait for things to get bad. Let's get everyone in here now, get organized, get ready before it unfolds.

[9:03] Kevin Sofen: One of my favorite quotes is, the best disaster is the one that doesn't happen. So there's obviously some of that community risk reduction side, but we also can know that something may or may not be happening and we can be more prepared for that disaster or that rain event or that potential flooding that is going to happen.

[9:18] Olivia Breed: Yeah. I think insurance companies have probably got some good statistics on this, but I believe where they've got insures with like 24 hours notice, the amount of damage is reduced by 30%. And when you're talking about hundreds of millions or billions of dollars of damage, that's a significant amount of damage avoided just by allowing people to move assets out of the direct path of the hazard or move their furniture up a floor or get their cars under cover. So all of those things help. It might seem small, but on a broad scale, that has a big impact, just that more advanced

[9:52] Kevin Sofen: Yeah. Well said. And then it's August 2025. What are you most excited about in the next one, five years? with what Kablamo is doing with the Firestory product and these other solutions. What are you excited about?

[10:07] Olivia Breed: I mean, I hate to say this because I'm sure everyone says it, but I mean, AI is certainly-

[10:12] Kevin Sofen: What's AI?

[10:14] Olivia Breed: It's definitely a cool part of our roadmap. And it's in response to that data problem, that data volume problem. We can't keep sifting through that much data manually. So AI is going to give us a lot of really unique, robust, creative ways to sift through that data and find what we need to know when we need to know it. And that's a great avenue for us to pursue is the AI aspect. The other one is partnership. So because we're all producing different feeds of data, so there's new satellites going up all the time, there are sensors that can detect fire in the forest, all of those things create more data feeds. It's the partnerships between companies that if we can come to an agency and we've already figured out how to work together, we've already figured out where their platform fits within ours and how the data is integrated and what it means for a workflow for a user, that solves a massive part of the problem for them in terms of like adopting the solution and getting value out of it much quicker. So I think AI, obviously, but partnerships from a more foundational

[11:18] Kevin Sofen: I'm excited to Google Kablamo and see what your logo looks like, and also the inclusion of what AI is going to look like, because if it's, if it's It's Simpson inspired, it's gotta be good.

[11:27] Olivia Breed: Yes, it's Simpson inspired AI.

[11:29] Kevin Sofen: So my final question, and this is sort of a random from left field, is there any sort of quote or words of wisdom that you live by? And it could be something that you apply within your daily life or something that is involved within your work at Kablamo, anything like that?

[11:42] Olivia Breed: I think like one of the things that we're really leaning into at the moment with AI, and it can be overwhelming. There's so much new stuff out there. It's all super complicated or it looks that way from the outset. Just try things. just log in, do a free trial to a new tool, do it once a week if you can, and just play around with it. You might not be able to get everything working, you might not understand the whole thing, but in five minutes, you're going to learn something about that technology, something about that tool, and that's gonna help build your knowledge because this is happening, it's coming, so the more you can be prepared, the more you'll get out of it.

[12:15] Kevin Sofen: I see a potential spoof of the Nike logo of Just Do It. Just try it. What's the worst that can happen?

[12:22] Olivia Breed: I don't know who would sponsor that, but good idea.

[12:23] Kevin Sofen: Yeah, I don't know. Maybe Tim's. I don't know. So, Olivia, it was really nice talking with you. Thank you for what you're doing. And I look forward to staying in touch.

[12:30] Olivia Breed: Thanks so much. Thanks for having me.

[12:31] Kevin Sofen: Take care. And that's a wrap for this episode of the Smart Firefighting Podcast. If you found value in this conversation, hit like, leave a comment, share it to someone, and tell us what you enjoyed most. Take care, and thanks for listening.