With the Ro& platform with scalable AI-native intelligence able to analyse hours of video footage to locate specific visual information at a fraction of the price for consumers and businesses, without taking the jobs of existing security guards, the business of physically securing and monitoring businesses, locations, mine sites and more has taken a quantum leap into the efficiencies only AI can deliver.
So, what sparked the creation of this platform, and why is it so revolutionary – CEO and Founder Roanne Monte explains below!
Australian tech entrepreneur Roanne Monte has launched Armatec Global’s latest Video Intelligence platform – Ro& – that is designed to sift through hundreds of hours of footage to locate specific visual information at a fraction of the price for both consumers and businesses.
The platform was created by Roanne after a terrifying personal experience during Covid lockdowns in 2021 during which she was stalked, intimidated, and continually watched in her home and surrounds for well over a year by a man working as a security guard in the office building across the street.
Roanne recalls being gaslit by her stalker, and even by police, who required an actual assault to take place before they were willing to act, even though she had been lunged at and stood over by the individual.
Says Roanne about her experience, “I felt so powerless, slowly over time I was stopping the things that I loved, such as walking the neighbourhood and reading in the park. This was during lockdowns, so it was the only activity that many of us could do at that time.”
“I was then inspired – as someone that develops software solutions – to create a platform that doesn’t take the jobs of existing security guards, rather it works with them and becomes a tool that can amplify their efficacy in the industry. Ro& in this sense, gives those in security an edge and allows them to work smarter, not harder,” she added.
“Unlike traditional security solutions that retrofit AI onto legacy architectures, Ro&™ was built from the ground up as an AI-native platform. This design ensures sophisticated retrospective video intelligence without requiring expensive compute resources or specialised technical expertise.”
Here is my extensive video interview with Roanne Monte – details of Armatec Global continue below, after which you’ll find an AI-generated summary of our discussion, and an AI-generated transcript, so please watch, and read on!
More details on Armatec Global:
Armatec Global, an Australian deep-tech company, has launched Ro&™, an AI-native video intelligence platform that democratises enterprise-grade security analysis for organizations and individuals worldwide. Built on a foundation of capital-efficient AI innovation, the platform eliminates traditional barriers to advanced security intelligence, offering zero deployment time and scalable SaaS-based access to powerful retrospective video analysis.
“Security technology has historically been costly, complex, and slow to deploy. Ro&™ eliminates these barriers,” said Monte, whose background spans Harvard computer science, Cornell Law, and global product development. “With zero deployment time and a highly scalable AI-native architecture, we enable organizations to access enterprise-grade security capabilities immediately—without costly infrastructure investments. This is security intelligence, redefined for accessibility and capital efficiency.”
Unlike traditional security solutions that retrofit AI onto legacy architectures, Ro&™ was built from the ground up as an AI-native platform. This design ensures sophisticated retrospective video intelligence without requiring expensive compute resources or specialised technical expertise.
“AI adoption is often hindered by high infrastructure costs and scalability challenges,” notes Alan Ambron, technical co-founder. “Our AI-native approach optimizes processing efficiency, meaning Ro&™ delivers enterprise-grade analysis at a fraction of the cost of traditional AI-powered solutions. This capital-efficient model allows us to scale globally without the heavy operational overhead that typically constrains AI security firms.”
The platform’s efficiency extends beyond technology—it supports diverse deployment needs through a flexible SaaS model, enabling:
– Instant access for businesses & individuals via zero-deployment, cloud-based AI intelligence
– Enterprise-grade, real-time capabilities available through Ro&’s authorised partner network
“The evolution from the first 3G safety watch to Ro&™ represents a quantum leap in security technology accessibility,” says Sy Laga’aia. “We’re not just innovating for enterprises—we’re making high-level security intelligence available to everyone, from small businesses to global organizations.”
Monte’s commitment to responsible AI development aligns with her contributions to Australia’s AI governance framework and speaking engagements at security industry forums, including the Protective Security in Government Conference in Canberra.
Developed through intensive Australian R&D, with Sydney as the company’s global headquarters and a strategic presence in the U.S. tech ecosystem, Ro&™ reflects Australia’s growing role in pioneering deep-tech solutions for global markets.
About the Founders
The founding team brings together three distinct pillars of expertise from Australia’s technology ecosystem:
– Roanne Monte, founder and CEO, and former West End star, contributes 20 years of proven product leadership in B2B/B2B2C platforms;
– Alan Ambron brings deep engineering expertise as architect of AICPA’s global platform deployed across 100+ countries and DARPA-backed cybersecurity initiatives;
– Sy Laga’aia, a 30-year security veteran, pioneered the world’s first 3G safety watch and secured partnerships with Samsung.
Here is the AI-generated summary of the video interview above, followed by a full transcript – please read on!
1. AI-driven democratization of security systems through enhanced video analytics
Personal experience as catalyst
Roanne shared how being stalked by a rogue security guard during the pandemic inspired her to create an AI-native video intelligence platform to generate evidence and improve public safety.
Democratization of security technology
The discussion emphasized making advanced security analytics affordable and accessible to homeowners and small businesses without requiring expensive hardware upgrades.
Integration of AI with existing systems
Roanne explained how the platform integrates with legacy camera systems, adding AI capabilities to analyze video data and provide actionable reports following incidents.
Multiple functionalities of the platform
The interview outlined the suite of products within the platform, including incident-specific search features, descriptive analysis of footage, and deepfake detection.
Support for security professionals
There was a focus on how the platform serves as a force multiplier for security guards by enhancing their productivity and assisting in real-time diagnostics for large enterprises.
Development and competitive edge
Roanne discussed her technical background, the cost-effective development of the platform, and how a hybrid AI solution differentiates it from competitors reliant on expensive, external hardware investments.
2. AI-driven Video Surveillance and Security Integration
AI in Video Surveillance
Discussed how AI can enhance video surveillance systems, processing unstructured video data to analyze events such as security breaches, package thefts, and incident verification over various devices like body cams, drones, and enterprise CCTV systems. The conversation also highlighted customized models for specific industries like mining and logistics.
Integration and Agnosticism of Technology
Emphasized that the platform is hardware agnostic, supporting different devices including body cams, drones, and consumer systems like Arlo. The API integrations allow for automation and customization, making it suitable for both large enterprises and individual users.
Human Oversight and Productivity
Pointed out that the system maintains human oversight throughout its process. AI is used not to replace jobs but to improve human productivity by helping monitor, analyze, and contextualize video data, thereby aiding in decision-making and incident response.
Collaboration and Partnerships
Explained the importance of collaborating with both big and small security companies, ensuring a win‐win model that balances technology with the needs of security professionals and policymakers. There was also mention of involvement with policy and cybersecurity strategies.
Future Directions and Policy Influence
The discussion extended to future plans involving policy contributions and evolving the platform to meet regulatory standards. The founders are engaging with governmental entities and contributing to areas like cybersecurity and AI guardrails.
Team Composition and Technical Expertise
Detailed the roles of co-founders and technical leadership, highlighting their expertise in physical security, system architecture, and coding. This collaborative and hands-on approach contributed significantly to the rapid development and deployment of the platform.
Use Case Diversification
Explored the potential applications of the platform beyond security, including being a tool for journalists, homeowners, and other fields where large amounts of video data are generated and require organization and analysis.
User Feedback and Continuous Improvement
Stress was placed on incorporating user feedback into the product’s evolution. The team actively uses insights gained from customers to refine and update the platform continuously, ensuring that the product remains relevant and useful.
AI’s Role in Job Support
Addressed common concerns regarding AI replacing jobs, clarifying that the focus is on augmenting human capabilities rather than displacing workers, using technology to reduce workload and increase efficiency.
3. The impact of AI advancements and the necessity of maintaining authentic human insight and execution in a rapidly evolving technological landscape.
Authentic Human Contribution
The speakers stress the importance of genuine, human-written content over machine-generated text, emphasizing the nuances of language and authenticity.
Quality Writing and Execution
Both speakers underline that effective execution in writing and projects matters more than just having ideas, highlighting strong writing skills as a crucial attribute.
Trust and Verification in AI Outputs
There is caution about blindly accepting AI-generated information, with an emphasis on testing tools and verifying the reliability of the outputs to avoid misinformation.
Future of AI and AGI/ASI
They discuss the uncertain timeline for AGI and ASI developments, mentioning quantum advancements and the potential rapid arrival of sci-fi scenarios.
Adjusting to the AI Economy
The conversation points out that jobs will change with AI integration; success depends on one’s ability to learn and use AI, not simply its replacement of human roles.
Learning from Past Experiences
The speakers share personal history with early computers like the Commodore 64, reflecting on the journey of technological evolution and personal growth in the field.
Balanced Caution and Optimism
While acknowledging potential risks, both speakers advocate for being well-informed to avoid fear and to adapt positively to technological changes.
Personal Values and Execution in Business
Advice from industry experts and personal grounding, including the role of prayer and strong character in navigating both business and personal success, is highlighted.
Conclusion
The interview highlights the development and integration of an AI-native video intelligence platform, emphasizing the democratization of advanced security analytics, support for security professionals, and the importance of human oversight in a rapidly evolving technological landscape.
Here is the AI-Generated Transcript of the full video interview, as embedded above:
Alex Zaharov-Reutt: 00:00:07
Well, hello and thank you for joining me for another episode of TechAdvice.Life TV. I’m joined today by Roanne Monte. She’s the creator of the Ro& Video Intelligence Platform by Armatech Global that monitors hours of security footage, making security smarter, safer, and more affordable, and which was inspired due to Roanne being stalked and intimidated by a rogue security guard during the pandemic. We’ll learn about all that in a moment, but Roanne, welcome to the program.
Roanne: 00:00:37
Thank you for having me, Alex. I’m happy to be here.
Alex: 00:00:41
Very happy for you to take the time. Thank you. Now, let’s start at the beginning. Can you please tell us about this rogue security guard that was harassing you for over a year during the pandemic and how this sparked the idea for a video security platform that worked without taking the jobs of existing security guards.
Roanne: 00:01:00
Yeah. So unfortunately, you know, that occurred for over a year. I right before the borders closed, I was actually working in Chicago and I’m Aussie, actually, but I left 30 years ago. So now I’m revealing my age a bit to work and study overseas. And my relatives and family were like, the government’s going to close the border. You better come back. So I did. And I lived in the North Sydney Lavender Bay area and I could only find an apartment.
Roanne: 00:01:33
The only apartment that would take my dog, who I was waiting for, was at this place across a co-working space in Lavender Bay. And unfortunately, the guard was just stalking me for about over a year and it was very traumatizing. Obviously, I had to deal with it.
And it sparked me. It inspired me to build a platform because I couldn’t get any. evidence against the person to make him accountable for what he was doing. And I figured I cannot be the only person who has experienced the situation in which I need evidence to give to the police. So I, you know, instead of, I wanted to do something about it and turn something very negative into a positive.
Alex: 00:02:25
And this exposes the problem that people face in similar situations where the police won’t act until it’s arguably too late because they have undertaken an assault. And so, you know, what was the evidence that you were able to collect and what inspired you? I mean, you must have had some experience in this area to be able to create such a system.
Roanne: 00:02:48
Well, I mean, I’m a technologist. I build systems. That’s what I’ve been doing for over 20 years. I started out as a software engineer. And ended up in product leadership, technology product leadership, basically turning things into something very useful in the technology space, focus more on software. And so for me, it was, you know, there’s obviously a lot of creativity and engineering involved in it.
Roanne: 00:03:23
And I just wanted to, I actually could not get evidence from the situation. It was very unfortunate because I told the business, hey, this is what this guy is doing. You need to, you know, I need to let you know about it. So fast forward two months after, I just couldn’t get enough evidence. And frankly, I felt quite gaslit, like as if I was some crazy person imagining things. And, you know, my nature is I’m a fairly logical person.
You know, I just try to go about my life. And they really. couldn’t do anything about it. And I just really then took a deep dive into the security industry and wondered, well, how can someone get away with this? How do I fix this? I cannot be the only person who is going through this situation where I cannot get enough evidence. So I started, even though I was stressed out, I guess one way for me to deal with my stress was to just start coding and start building the algorithms. And so hence, here we are today. So thankfully, there is a solution.
Alex: 00:04:37
So did you set up camera systems and you were then monitoring what was happening on all the captured video? I mean, what happened as well to the rogue security guard? Did the police end up arresting him or taking some kind of action that stopped his assaults because you then had this evidence?
Roanne: 00:04:54
So I knew that, But I wanted to obviously put AI into it and build it with AI from the start because you need, in order to process tremendous amounts of data, video data, imagine all of the video data that we come across on a daily basis, right? Even if you were, as a homeowner, you know, you have a home or an apartment, one or two cameras can gather a lot of data. So, I, in terms of the security guard, I mean, I actually had a great case.
So, a friend of mine, Chris, he’s Chris Murphy, I didn’t know how famous he was in Australia, but he’s this famous lawyer, and Brian, who works with him, Brian Wrench. So, they were taking care of the case, and we actually had a, have, had a very, very strong case, and I just decided not to pursue that. And instead, solve the problem, you know,
And so I wanted to focus my time instead of focusing on myself to focus on how do I then help everybody else who is going through or who might be going through what I had just been going through. So he’s out there right now. And part of what inspires me to continue and build and improve the platform and democratize the platform so it’s available to everybody is because that kind of actually in a bizarre way, it inspires me because he can’t be the only criminal out there.
Right. There are other bad actors – not to demonize situations, but there are bad. Bad actors out there. And I just wanted to build something that is useful to people and that could help people. So and to obviously try to create some. Safety is a right. It shouldn’t be just for people with money, right, or who can afford expensive systems. Safety is a fundamental human right, and everybody deserves to feel safe, particularly in their homes or in the surrounds of their homes. But, yes, he’s still out there, unfortunately, but it actually drives me to build better and keep improving on it and making it cost-efficient for people.
Alex: 00:07:31
Yeah. Well, having a pain point is usually the catalyst to come up with something that solves that particular pain point. And, look, it’s not as if security cameras haven’t been around for some decades now. So rather than try to retrofit existing legacy solutions to make them AI-enabled, you know, you created the ROAND AI platform as an AI-native platform. So that, you know, this could then scale. And it would have AI at its core. So tell us a bit about this particular, you know, the platform itself and sort of how it’s grown in the time that you came up with, I guess, the pilot version of this system and where you are today.
Roanne: 00:08:15
So thank you for that. That’s a great question. The platform, we have a few, obviously, more complex versions of it, which is more for government and for corporations. To protect their assets. But the core platform, the standard version of the platform, is available to everybody. So whereas before this technology would only be available to businesses and big corporations, now you can, a homeowner or a small business owner can access it.
So the difference between kind of, you know, AI, as you know, is. A lot. It’s an AI native platform because it has AI capabilities at its core. And it hopes to save time and money, obviously. And for situations, I mean, there are many use cases. So a good technologist, hopefully, as myself, builds things that are useful for many different situations, not just one.
I’ve been building technology products for over 20 years. And probably a main challenge for me in this, obviously, for this particular situation is that one way to think about it is like our indirect competitors have, you have to buy the camera, you have to now pay for that and the monthly thing. And it’s very, very expensive. And the main challenge. How do I make this technology available for everybody in a way that is not so expensive?
So it requires a lot of focus and a lot of dedication, obviously, because it’s not easy to do and we’ve done our best. So we’re very excited about it.
Alex: 00:10:26
And are you using or selling your own camera systems or are people able to reuse the ones that they might already have? And then when you are looking at the dashboard of what the AI has analyzed, is it showing you a series of events that it wants humans to look at because it has determined that these are the ones out of the hours and hours of footage that really need that human interaction.
Roanne: 00:10:54
Yes. So there are two. There are three products inside the platform. So it’s really. a product suite. So similar to what you would see Microsoft 365, you’ve got Word, Excel and Outlook and a few others inside. We have kind of the same setup. There are three products, inside the platform.
There’s one called Ro& Clue. And that’s for when if you don’t if you know exactly what you’re looking for, let’s say the incident you’re interested in is because your car got lost and you’re looking for your car and you tell the system you are looking for a red car or to be more specific, a knife or an object of interest. All you have to do is upload your footage into the system and tell it what you’re looking for. And it will tell you, well, here’s what I found. And here are some video snippets. And then you have the option then to send it into a report. So you could send it to your insurance company or if it’s a corporation.
They usually send it to police. But you have at every point in time, you can review the thing that you’re interested in and run a report. The other one, Rowan, now is if you don’t know what happened. Let’s say you have three hours of video and you want to know. You haven’t even seen the video and you don’t have time and you need to know right now what happened. You upload the whole video and it will just, you know, name the file and it will just tell you what happened.
And then you can run a report. So we try to make it as intuitive and easy to use as possible. Most of the technologies that are built around this is very difficult and is designed for people with a lot of computer experience, a lot of technical experience. But we really focus on empathetic user experience for the user that don’t have. to change their cameras. The whole point is to save people money and get value from the thing, not find, you know, but obviously you need to have a camera that can, has enough definition. So if it’s a very, very old camera, that might be a little difficult. So that’s what it is. Very, very excited.
Alex: 00:13:22
Yeah, so just to be clear, it’s not a whole new security system and new cameras. You actually work with people’s existing solutions, but you’re this new additional layer that you can plug into these existing systems, but supercharge it so that it can give you this intelligent, you know, incident analysis, or it can just describe exactly what’s going on in the same way that you can upload a recording of a conference to chat GPT and get it to give you not only a full transcript, but a summary of all the important topics. And that way you’re actually evaluating, what you add and an improver of people. It was existing systems, not a replacement for it.
Roanne: 00:14:03
That’s correct. So one thing, you know, a lot of technologists that just want to disrupt an industry and this is all I’m focused on. We’re obviously focused. The reality is we have economic realities. We have investors and we obviously have to stay in business and make money. But I like to bring value to people, not to kind of, you know, have them think, oh, now I’ve got to change my whole system and spend more money. Our system is you don’t have to install anything.
You can just just like any software as a service, you just buy a subscription monthly and that’s all it is. They don’t have to change their cameras. They don’t need to. Buy new hardware. Part of what differentiates us from others out there is you don’t have to buy anything new as long as your camera is not. like 10 years old or something, then maybe they have to look at your blog and your advice more, Alex.
I’m sure you have better advice on hardware than me. I’m a software person. So that’s what it is. We really want to just bring value to people instead of adding on to cost. The technology is becoming more commercialized in terms of the capabilities of AI. And we want to bring that value add to people.
Alex: 00:15:33
And I’m guessing that some of these platforms might be trying to do something similar as part of their own offerings. But clearly, your platform is superior. Otherwise, you wouldn’t have a market.
Roanne: 00:15:46
Yes. So, I mean, as a product leader, one of the things you study is your competitive analysis. There’s no point spending all this money, although we got to market for less than a million USD, which is quite an achievement. And we’re available in 20 countries. One of the things we study is competitive analysis and make sure that it’s not just, I didn’t want to build something that would be in a flooded market. What differentiates us is that one, you don’t have to buy the hardware. Two, you don’t have to buy an expensive system that you now have to install. And three, it’s available, those systems, if you wanted a fancy system, it’s usually for people with very, very expensive and fancy homes.
And that’s it. What about the people who are just living their regular lives? And want access to the technology. So that’s why we wanted to democratize it by making it cost efficient and affordable for everybody. So that’s the whole point is to democratize it. and make sure that whether you’re a big corporation or a homeowner or a small business, that it’s affordable according to their business needs.
Alex: 00:17:09
I know I’ve got friends that run businesses and they have Hikvision cameras recording to the cloud and to physical systems, but normally there is no AI type of platform that you can export the video to and upload it. So clearly those people who already have existing systems that want this add-on to be able to sort through all that information are going to be the ones that are your primary customers.
Roanne: 00:17:36
Yes. So for the enterprise version, we do have the live version, which is because we didn’t want to make a technology available to the public that is a form of surveillance, because now we do not want people infringing, on another person’s rights, privacy rights. So the readily available platform is only available as an after-the-fact, like diagnostic post-facto tool.
For large corporations, we have both the after-the-fact as well as real-time. So it really depends on the needs of the entities of the enterprise. But a lot of those enterprises who paid a lot of money for their systems, they end up, okay, so I have a security guard. I have 20 monitors. All that guard has to do is blink, and he could miss something, right?
So our one is a force multiplier, so to speak, that allows – it’s like having instead of one guard, you now have four guards. And it allows – It allows the guard to be more productive. In a similar way to – we have the corporate – Right. So it’s generative AI. They input something and it allows them to be productive. One way to think of this is, well, how about the security industry? How about allowing them to work in this new AI economy?
And potentially it could attract good quality candidates for the security industry, which will then hopefully improve public safety because we have the police, we have the security industry. These are the people keeping the public safe. We want to make sure they are part of the AI economy.
Alex: 00:19:47
And look, whenever I watch a movie and there’s… Somebody trying to break in somewhere and somehow they’ll upload a bit of a recording of some footage. that has been captured, it’s sort of going around in a circle so that they can go by and not be seen. And I’m imagining that your live system might be able to detect, hey, this footage is on repeat. Someone’s trying to fool us. Because normally in the movies you see someone sitting behind, or a few people sitting behind some screens, but there never appears to be any sort of AI that is there saying, hey, check this out, this doesn’t seem right.
So is that something that the live version of the platform is doing or even the version that is looking at it after the fact can recognise and say, hang on, I mean, we’re always looking at this one door, but even though it’s the door and you’re waiting for someone to open it or break in, it can tell that that is the same footage over and over. Is it that sophisticated? Are people using it for that right now?
Roanne: 00:20:52
So that’s a great question because we have a deep, a deep fate of features. So for Rowan Clue, if you upload a video and you’re not sure whether it’s real, we have a deep fake feature which will give you an idea of to what extent might that be a fake. If we look at what’s out there right now, there’s a lot of generative videos, deep fakes that are sometimes not good.
And obviously, we want to make sure that what you’re analyzing, what you’re diagnosing is real. So that was one thing that one of the features that I wanted to make sure that was built in the platform. And obviously, for the more expensive plans, more expensive subscriptions, there are more capabilities, whether it’s changing the surroundings or, you know, it gets it’s pretty fancy for the higher end ones. For more. You know, businesses who might.
But for the fundamental thing for consumers, there is a deep fake feature detection to make sure that the video, what’s the point in analyzing the video if it’s not even real? So that was one of the things I wanted to make sure that was in there.
Alex: 00:22:21
And does the ROAND platform use existing AI engines such as ChatGPT or did you have to create your own from scratch.
Roanne: 00:22:33
So we have a hybrid, so we don’t use ChatGPT. We have the capabilities within our team, mainly in the leadership team to create our own. So we use best in breed AI models, but we also create our own. As has been known, it’s becoming more efficient and cost-effective to train. models. We’ve heard of the stuff that’s been in the news. So we didn’t rush into creating our own models because we want to make sure that they’re compliant and that they are not biased in any way. So we’re very careful about our build. And I’m very proud of my other leaders because we’re all except for one who.
is the physical security domain experts, all of us code. So I don’t code as much these days running the company, but we all code. We have an amazing principal AI engineer and the leadership is very strong. So I think it’s helped a lot in making sure we have that originality in what we’re doing.
Alex: 00:24:00
Are there any existing customer success stories, whether in Australia or globally, that you want to just touch on briefly.
Roanne: 00:24:08
Well, we have only been live. The subscription one, the turnkey software as a service, SAS one, it’s only been live for a month. And we have obviously some enterprise and government use cases that we’re in the pipeline with, but we signed confidentiality, so we can’t discuss them. But, you know, we’re just looking forward to bringing value to them.
There’s various use cases, including logistics and transportation. So think, you know, the various distribution centers. There’s also mining that’s of interest to them because everybody wants to cut costs and pay for it. But also they want to get more value from that relationship that they might have with the security company. So it’s structured so that it empowers the guard in their workflow and it also empowers the security company.
And they’re obviously the most qualified for those specific use cases where there are multiple guards involved. So we’re very excited about the various industries that we’re addressing.
Alex: 00:25:35
I’m sure that for mining, it’s not just security in terms of people trying to break in, but like incident control. I mean, people might try and cover up something that happened. But if the cameras have recorded it and the AI can determine that it happened, then the leadership can be involved. And they can make decisions accordingly. But there must also be the body cams that the police and security guards are wearing these days. So that would all be part of the video that can be uploaded into the platform, right.
Roanne: 00:26:04
So it is agnostic, meaning it applies to, it’s not specific to any hardware. So for the body cams and for drones as well, the drone use case for us is being refined constantly. So, obviously, the low-hanging fruit for ICCC TVs, but body cams, it could be any, you know, we don’t want to lock people in.
Whether you’re a corporation or a small business or a homeowner, we like to, good technology is agnostic so that it applies to many different things. But obviously, nothing’s perfect, so we’re constantly refining it. And at every stage of the process, when, you know, a user is on the platform and they’re doing their analysis or diagnosis of, you know, know what happened and gaining insights the human is in control the whole time.
so it does have human oversight at all times so it’s more about making humans more productive making humans bringing more value to what humans are trying to do so I’m very cognizant and very aware of that in our build and in training the system.
Alex: 00:27:27
I mean with generative AI you can describe something and then it’ll create a document or a video for you or a picture are you able to describe certain events that can happen whether on a mining site or building site or whatever it might be and even even maybe demonstrate to the system what some sort of accident might look like so that the system can be fine-tuned to be looking for those sorts of things or does it somehow already sort of have that capability be able to do that?
it’s built in or it’s pre-programmed I mean presumably, probably there’s some way of customizing it for specific things that the system might not know about yet.
Roanne: 00:28:06
That’s correct. So for those situations, for let’s say a very specific situation for mining and there is a – so for example, we have a customer in the pipeline where the package got lost and it’s thousands of dollars and obviously they have to pay – the insurance has to cover for all of that. They don’t know what happened. It took them days to figure out what happened, where did it go, who stole it, the police needed evidence, and it took them days.
So for that type of use case, upload the video. It’ll find it. But we have both for situations where it’s a corporation. We train the model specific to their situation. So let’s say it’s an area that is a quarantined area. Let’s say it’s a quarantine. Stuff that comes from. In plain terms, stuff that’s come from overseas and, you know, it needs to be made sure that no one’s accessing that area.
There are various ways that we can train a model specific to that situation so that as the time goes by, it gets smarter and smarter and it gets smarter at detecting the very situation that it’s looking for. So whereas some companies might just detect objects, you know, so, okay, you found a lady with a red hat. There’s no context, right?
There’s no context. So the more sophisticated version of our platform brings together the context. So in fancy schmancy terms, it’s contextualization of data. And so we want to train that model to. Make sure that it is looking at the thing. that that entity is looking for, and it gets smarter over time.
Alex: 00:30:07
So, I mean, I’m thinking that really this, at the moment anyway, it’s more aimed towards businesses and government and enterprises and logistics and mining rather than consumers at home. I mean, I’ve got an Arlo system, for example, and it can tell me if it detects a package or if it sees an animal or motion. But it sounds like it’s not really something that I, I as a consumer, would want to get yet because it’s a bit too basic because of the system I have. Can I really do that sort of thing? Or is this something that I could, if I have a Swann system or an Arlo system, can I take advantage of this?
Roanne: 00:30:43
Yes. So with Arlo, do you subscribe monthly? It keeps it for 30 days, right, Alex? That’s correct, yes. Okay. So for your situation, you could just go to the website and choose a plan. So you could take that. The cheapest plan. I think it’s $49.95 USD, something like $78 AUD. That’s the most basic a month. And take your, let’s say you, there’s something you’re very interested in.
People have different things that they’re interested in. Who stole my package? Let’s take something simple. What happened to my package? Amazon said it’s there. Now it’s gone and I just spent $300 on a new gadget or something. You could take your past footage, so download it from your Arlo system, upload it to our system, and just ask it, what happened? Where’s my package? Or, you know, I’m looking for a package. Or just name the file, click submit or analyze, and it will tell you exactly what happened.
Here’s what happened in this video. I mean, there are some people, one of our testers, is a man who couldn’t figure out, you know, he was like, well, actually, you want me to, this was before we went live, you want me to test it? Can I test past videos of my son? You know, I’m trying to look for my son’s birthday party. It could be something like that. You know, it doesn’t have to be security. It could just be like, you have hours and hours of video, you don’t know what happened.
So it’s actually good for journalists as well for media. If you imagine field journalists taking footage, do they have time to make sense of all that? And maybe they just need to organize the file. So you could build an entire library on our platform and organize your files and do it that way. So it’s really for homeowners, for journalists. It applies, the more sophisticated one is obviously for businesses and enterprises and government.
But for someone like you, Alex, yes, absolutely. Absolutely. If you just want to find out what happened, you’re too lazy. You’re not going to sit there and analyze it. Just run it and it’ll tell you which video is the one where they stole your package.
Alex: 00:33:11
And in the future, will you be working with these existing companies so that you can have some sort of API that you can choose to have the footage automatically uploaded, whether it’s an enterprise system, so that the whole thing can be automated? Because at the moment, I would have to download and upload, but I would love to just be able to hit a button and then interrogate the system and say, show me. Because at the moment, I have to look through certain days to try and find something. But if I’m telling the system I want… The Rowan system, I want to see every instance of a package being delivered. It would be nice for that to be automated. If you’re only a month old, obviously, there’s plenty of these opportunities and partnerships to come.
Roanne: 00:33:51
We already have an API.
Alex: 00:33:55
Well, I would imagine, yeah. But it’s you working with those other companies and coming to some sort of… Or letting them, having them allow you to log into the system…
Roanne: 00:34:05
Yes, provided they allow us and that’s what they want to do. Everything is automated. The systems can talk to each other so that, you know, they don’t have to do things manually. We also have timed uploads. So some people want near real time. Maybe they don’t want full surveillance and it’s more about getting a report. Some of them do it for compliance and they can do it in timely uploads.
We do that as well. So for the custom versions, we really customize it for what the client needs. But APIs, yes, big thing for us. We obviously use all different kinds in terms of we use whatever integration tool if the client is using. A middle person or a middle entity for that. or we do direct whichever one is useful for them.
Alex: 00:35:04
And is it too soon to ask if some of the existing big security players are already coming to you saying, hey, we want to offer you directly to our customers because it’s something we’re not experts in and we can just plug you in and go? I mean, if that hasn’t happened, I’m sure it will.
Roanne: 00:35:21
Yes, we’ve had all different kinds of conversations come our way. Obviously, there are ones who just want to buy us. Are you willing to sell your company now? No, we want to build a company and we can innovate faster if we have less hierarchy. But to answer your question more directly, yes, big security companies are obviously very, very interested in what we’re doing. But we want to make sure, that it’s available to the big players. as well as the small players, because I guess one way to think about is I’m a bit of a systems thinker. So security as a system, there’s big security companies, there’s medium and small size security companies, there’s the guards, we want to make sure we’re upskilling them and making sure that we’re not taking their jobs, because that’s not good.
I’m a different type of technologist, maybe I’m a bit of an idealist. And, and then there are stakeholders, there’s the clients, there’s a corporations who always need to get value out of what they’re paying for. So that’s how I’ve kind of built the system so that all the stakeholders and as well as the public is in that system, right? So how do we make sure that everybody’s interests and is balanced and no one is being left out? So my goal is to.
Actually, one of the things that inspired me was seeing an older security officer, and I just found it horrific that the man was working late at night. And so that’s how I built the business model aspect as well. That person can sign up as an affiliate, give his link to people, and he can make passive income every month. So there was a lot of analysis and putting together the business model. We try as much as practicable to make sure it’s win-win.
That’s a good system, to make sure balancing everybody’s interests and making sure nobody’s left behind.
Alex: 00:37:42
And I was just sort of thinking about how I interviewed the founder or the CEO of Swan Technology. They have a doorbell that uses machines. Amazon’s anthropic AI to respond in male or female voices. I think you can clone your own voice. So when someone hits the doorbell, you know, even without you being there, you can have a conversation with that person to tell them to leave the package or go away. Or if they’re, you know, pushing a doorbell at three in the morning, the sound that comes out can be of somebody quite angry to be annoyed. Is that something?
Roanne: 00:38:48
It really depends on our focus right now is to make sure that the problem of raw video data unstructured. Kind of nobody knows what goes on. And a lot of that, most of the time, 80 percent of past video data, nobody knows, nobody cares about until, you know, it’s important for a piece of evidence or something. But for interactivity, obviously, that’s very important for us. One thing I kind of focus on is to make sure that every part of the build that we do and any set of improvements that we do does not violate.
So I have a legal background. I’m not a lawyer, but I do have a legal background. So in all aspects of the product build, I’m always looking at what’s allowed. And what’s not allowed. So and also if somebody is already doing it, I don’t like to I want to make sure I’m not let them focus on that.
They’re already doing that. Well, let them do that. And I would only build. a set of features or a set of improvement if I know it’s going to complement that or it’s going to bring value to that thing. So, I mean, I’m a technologist who doesn’t, you know, I just hope everybody else is that way. Not everybody else is that way, obviously, but and to work with people. There are other tech companies who obviously are very, very interested in helping us succeed and working with us and collaborating with us. And I’m very happy that that’s the case for us.
Alex: 00:40:34
Now, you mentioned one of your co-founders, Sai La’gaia, and you also have Alan Ambron. Can you just briefly tell us about their strengths and, you know, how they’re involved in the business?
Roanne: 00:40:44
So, Sai was actually the one who helped. So, I knew Sai from years ago because he had a startup, a safety watch. So, he had the, he was the founder of the, 3G safety watch.
Alex: 00:41:00
You’re talking about an actual watch itself?
Roanne: 00:41:30
And he said, you know, can you help me out? I can’t scale this thing. Various government agencies want it, but I cannot scale it to the size that I need to. And I was busy, so we couldn’t do the project. Fast forward to the stalking incident, because I knew that that was his expertise. He actually helped me through the stalking situation, to just check out what is going on there. So as I realized that… I needed his domain, physical security domain expertise.
His input to the platform is to make sure we’re not just building, you know, technology for the sakes of building it. We want to make sure that it’s usable and that it’s useful to the people who are going to be using it. So his part, he’s a co-founder. His part in it is as a domain expert to make sure that at every step of the way, we’re doing something that is meaningful and useful.
Alan is a co-founder and he is our chief architect and CSO. He’s very hands on technical, 40 year experience built. I built a number of systems with him, global systems. So he’s a chief architect. For multiple global systems, very talented, multilingual, multi-cloud, everything. can code in his sleep, and now that I have because I have them and I also have my CTO John who’s a former AI professor at the Columbia University School of Engineering a very fancy school they both code and I do too but I leave all the coding to them now after I built the initial part of the platform now I have a lot more responsibilities running the company so very exciting leadership that we have and people always ask me how did you get it to market for less than a million dollars well a lot of it is because we’re not really armchair executives that just strategize I mean we’re heads on coders so all of the algorithms at the start and I still work on algorithms so we’re very technical so I guess that’s a fortunate thing. Saves a lot of money.
Alex: 00:44:00
Now, before I ask you some personal questions, is there anything else that comes to mind that we need to know about Ro and that you’re realizing that we haven’t spoken about and we should know.
Roanne: 00:44:11
Well, I think so to me, thank you for that, Alex. To me, the key thing that I want people to know is it’s a different thing to how AI is thought of. Right. We are entering the AI economy. And as we see in some jurisdictions, there are a lot of mass layoffs, things like that. One thing I want people to know is it’s not here to replace people’s jobs.
It’s here to bring value to an existing problem. It’s here to bring value and solve problems that are a long time coming to be solved. And it’s really here the platform. is here to try and help people. So, I mean, open to, we have feedback forms when people use it. If they think of something, I’m very open.
They can write in and tell me, hey, I used it this way and I want to see this feature. So it’s not that different to singing to an audience, right? Because you’re always looking for feedback from people and how can you make what you’re delivering valuable, to that audience? So we get a lot of feedback and it’s a constant conversation that we have with our users. So that’s probably that it’s not here to take jobs. It’s here to make people more productive and save time and money.
Alex: 00:45:49
I often like to say that your customers are your best R&D division because they have paint points that you haven’t even thought of yet or didn’t realize were so important. So I’m sure… You’ll be getting even more feedback than you can possibly have imagined, and that’s going to help shape the future direction of the business.
So what’s ext for you? Are you working on any other projects in this or other tech spaces, or are you just too busy at the moment with the Ro& platform.
Roanne: 00:46:16
You know, I always say to my team, sleep is a hoax. So, you know, I’m involved in a lot of things right now. I’m involved in, so I submitted, along with John, our CTO, and Alan, our chief architect, to, for instance, the DICER, Department of Industry Science and Resources. The DICER AI guardrails for high-risk settings. I really wanted to bring value and help the policymakers gain some more insights and understanding around AI technologies.
They have some very smart people at DICER working very hard. This is not an email. easy technology for people to understand. So I always try to contribute to policy. So I’ve written, I think I’ve submitted four things so far. In the other ones, it kind of has to do with the Department of Home Affairs cybersecurity efforts, the 2023 to 2030 cybersecurity strategy for the country.
Roanne: 00:47:26
And obviously, those ones I submitted confidentially because we don’t want people to find out what I’m saying, how we can protect the country. So I’m involved a lot in policy in terms of technology. It’s really more algorithms and models and working on just refining and making the platform better each day. So it’s more around thought leadership, I guess.
If people call me that, I get busy. I go on panels and things like that for me right now. There are some other exciting things that I’m working on with my co-founders and tech leadership that will tell you about Alex.
Alex: 00:48:23
It’s all still top secret, and I can fully understand that. I guess at a higher level, how do you see AI unfolding through to 2030?
We’ve seen the ability for AI platforms to actually start explaining the reasons why they’re giving you these answers, which answers the black box problem of non-explainable AI. AI that doesn’t explain itself just sort of gives you the answer. We’re seeing that with DeepSeek. We’re seeing it with Grok 3. Then as an adjunct to that, which AI platforms are you using personally?
Or are you playing with all of them?
Roanne: 00:49:00
I play with all of them, except for the ones I shouldn’t be playing with. So I test, you know, I’m pretty hands-on with looking at what certain ones shouldn’t be doing, what they’re doing. For me, it’s more informative around whether it’s avoiding answering certain things. And there’s something very dangerous about that, right?
Because it can skew the truth or alleged truth, which is oxymoronic of sorts, into something else that shouldn’t be the case. So I do look at everything. I don’t fundamentally, for me, for instance, for writing, I’m not going to, you know, I’m quite a, you know, so I went to a very. Yeah. And they don’t let you graduate unless you’re a really, really good writer. So people think I did computer science there or maybe I just code and that’s all I do. No, they don’t. They don’t let you out of the place until until unless you’re a good writer.
So I don’t I am a little also prideful of my writing. So I don’t use unless it’s kind of like something flip. You know, I don’t want to spend too much time on. It’s just a summary of something. Then I might use chat GPT. But otherwise, obviously, for policy work, that’s I mean, and also I can tell right away there’s when people write, especially the in. Our language, English language, it runs on a specific I am big meter. I can tell what whether a machine did it. And so but for me, I test things. I test a lot of what’s out there.
And it informs me on maybe it’s good to do that, but more so that what not to do. But Grok, for instance, is amazing. It’s really good. There are a lot of great productivity tools out there. Obviously, it helps speed things when you’re doing research or something like that. But in terms of my own work, I’m a little bit, maybe that’s where a little bit of pride comes in, because I find it, you know, sometimes when someone sends me something that they shouldn’t have chat GPT’d, I get a little bit offended. It’s like, OK, you can do better than that. You need a machine to do this for you.
Alex: 00:51:45
I mean, I often recognize when someone has written something on X, which is obviously copied and pasted from, you know, a chat GPT. And I’ll often say thanks and I’ll put their name and then I’ll put the letters GPT behind it. to sort of tell them that I know that they have used that. But in terms of the 2030 thing, I mean, you know, do you think we might have ASI or AGI by then, which will also be a massive game changer.
Roanne: 00:52:14
So nobody knows where the AGI, artificial general intelligence space, is going to go. I think with quantum and the commercialization of quantum and, you know, the entire qubits ecosystem, you know, obviously IBM and the big tech companies are, it’s a race right now for quantum.
With all of these confluence of factors coming together, 2030 could be what would be kind of this unknown thing of the future of quantum. What we see in sci-fi. movies is probably going to be coming sooner than we know. The fact is a lot of folks in the AI space themselves don’t know. This is why we need guardrails. What we do need to be careful of is if those folks who don’t know how it really works, they probably shouldn’t be making people fearful about it because that’s not going to help us.
We want to make sure that we have some great innovators in Australia. And I actually would argue that for the, I mean, if you think about the startup ecosystem here, there’s not a huge private markets here. There’s not a huge, but compared to other countries, such as the US, not to kind of pit them against each other, we’re not going to be able to do that. We’re not going to be able to do that. We’re not going to do that. We’re doing pretty good.
So I think we’re in a good situation where we have policy people who are, focused on it and making sure that they’re doing good for the country and we have innovators as well so it’s a good balancing kind it’s a balancing act but it’s a good kind of situation to be in 2030 I think what people have to remember is that we are already in the AI economy so the best thing the best way to think about it is not that AI and I’m sure we’ve seen this all over LinkedIn where you know the AI is not going to replace someone’s job it’s the person who knows how to use AI that will replace someone’s job who’s not using AI so for 2030 my two cents if people want to know my two cents in terms of jobs and and roles there are going to be it will need an adjustment from a macro country kind of lot broader level, and and, to just be proactive about adjusting with it.
This is why folks like you are helpful because it’s like you’re unpacking what’s going on and help people understand what’s going on. So what I suggest to people is don’t be afraid of it. Get informed. The more informed you are, the more you know about it, the more you can adjust to this new AI economy.
Alex: 00:55:28
Well, the only constant in the universe, they say, is change, or at least that’s one of the two. The other one is death and taxes. And, I mean, humanity has been very good at, for the most part, changing, rolling with the punches. I mean, the Luddites were wrong. I mean, we’ve got more jobs in different areas than ever, and automation has helped farming and so many different things, that you’ve got to look for the positive, and if you dwell on the negative, well, eventually you won’t be here on this planet anymore, and, I mean, life will go on. So just being positive.
Positive is always the key and learning about it and not being afraid of it. Now, my last couple of questions that I always like to ask these one and the second last one is, can you please share a memory of your first personal computer.
Roanne: 00:56:13
I’m going to reveal my age, Alex, but I guess I better fess up to it, right? Right. Please don’t laugh. And I hope actually one of my engineers found some show on the Internet in which the machine I first worked on was speaking to aliens. But, you know, this is just engineering humor. Commodore 64. I was eight years old, coding on basic and low level programming assembly and making rasterized images.
Images on a green and black screen. So, yeah. So that just tells you how old I am about. uh but yes commodore 64 and obviously no one knows it’s a relic for all you young people out there it’s a museum uh but i started coding back then and uh you know i’m i’ve always been a curious uh person and like to uh you know solve things and i like to think i’m creative even though i’m nerdy uh but yes to answer your question, Alex, there it is no point hiding it – Commodore 64, is it is my first machine.
Alex: 00:57:32
Well i mean i must be older because my first computer was in 1979 it was something called the exity sorcerer at the time you could buy the apple one as a kit you could buy the commodore pet which was the computer with the sort of almost triangular monitor that was in the buck rogers and the 25th century show which was the, computer before the vic 20 the commodore vic 20 which was the computer before the commodore 64, So don’t worry about it. I mean, the Commodore 64 was a great place to start.
I do remember all those computer magazines and the cassettes and having to type in things and joysticks and they had the cartridges. And so, yeah, I mean, a friend of mine whose son is, I think he’s now in his late teens or early 20s, they’ve actually found a Commodore 64 from somewhere. They’ve been booting it up and playing with it. And I said to him, well, you should also, you know, try it against the Commodore 64 emulators. I mean, for the young people watching, you can emulate all the old computers on your, you know, newer Windows PCs and Macs. And it’s a great sort of vision into the past to see what those were like.
My second last question is to ask if you could please share some of the best advice you’ve received in life to help you get where you are today.
Roanne: 00:58:49
So that was probably I’ve categorized into more there’s the business side and then there’s the, the, kind of personal character-based side. So on the business side, I take a lot of learnings from a man who wrote a book called Measure What Matters. And it’s really helped me. So his name’s John Doerr. He was one of the first investors of Google.
And he wrote a book, for those of you out there who are interested, it’s called Measure What Matters. And the one line he always says is, execution is everything. So ideas come and go. And a person, a young person wanting to do something great, an idea has to be executed, and it’s the execution that matters. From a kind of personal character perspective, even though I’m into the sciences, I pray a lot.
We do a lot of things in the world. And, you know, at the end of the day, we’re just humans trying to. through this thing called life, and I like to think there’s something more powerful up there that’s looking over me, and so I try not to talk about that too often, but at the most fundamental level, I believe in prayer. I know all of my friends who are scientists don’t believe in that, but for me, it’s just something that grounds me and puts things in perspective in terms of what I’m doing.
Alex: 01:00:28
Whenever I hear about measurement, I think of my father’s uncle who always used to say, measure twice and cut once, and then as for the spiritual side of things, yes, I think that’s something that we’re going to be looking at a lot more in the age of AI and people potentially looking towards AI as a digital sort of god, and if you’ve got the little air pod in your ear, you know, your kids in 10 years, are they going to listen to you, or are they going to listen to you? I don’t know. whispering in their ear to tell them these things. There’s going to be a lot of debate about that and what it means to be human and whether people are going to find that their best friends are machines. I mean, that’s already something that we’ve had people who have sadly ended their lives because they were in a relationship of sorts with an AI chatbot and it was something that was taken away from them. And I don’t remember all the details, but already that’s sort of something that has already affected some people. So, yeah, the next level of existence is we’re living in it,and we don’t even know where really it’s going yet and it’s going to be quite a journey for civilization.
Roanne: 01:01:40
Fantastic existential insights and points, Alex. Wonderful points.
Alex: 01:01:46
So what is your final message for the viewers and readers?
Roanne: 01:01:52
For me, I mean, I’m just another technologist. I’m just hoping to move the needle slightly. My message… It is just more from a broad thing, a broad perspective, which is to just get informed and make sure that the information you’re getting is from a real person. Maybe like Alex, when you’re talking about gadgets, you need a real person telling you what it is.
The more informed we are because we fear what we don’t understand. Always look at the person’s, you know, background. They’ve been doing that thing and they’re good at doing that thing. Be well informed and that way people don’t fear something that they’re not informed about. Do not pass judgment yet. Just learn about it is probably a good productive step.
Alex: 01:02:56
Well, Roanne Monte, I’m sure that you’re going to be doing more than moving the needle, but leaving your own dent in the universe as Steve Jobs was described to have done. I wish you the best of success with the ROAND video intelligence platform and many innovations and improvements to come and I do hope we can speak again in the future. So thank you very much and bye for now. Thanks, bye.
Roanne: 01:03:21
Thank you.
