 Welcome everybody, this is theCUBE, I'm Paul Gillin. Physical security and cyber security have traditionally been sort of isolated worlds that didn't talk to each other, but in the age of the internet of things, we now have unprecedented opportunities to unite these two traditionally separate areas. Armored Things is a startup out of Boston that's doing some very interesting work in using intelligent devices to make decisions and to intuit patterns in crowd behavior, which has applications in cyber security, crowd management, traffic management, a lot of different potential uses of this technology. With me are Julie Johnson, the co-founder and president of Armored Things and Chris Lohr, the Chief Technology Officer. Welcome. Thank you. Why don't you describe it in a nutshell, let's start out what you do, Julie. Great, Armored Things is building software to do next generation incident response. We're using the IoT devices and their data to power decisions across large environments used for safety. So for example, the data that we're collecting can be used to get better situational awareness within seconds and drive incident response in seconds instead of tens of minutes, which is the state of the art today. And so it sounds like a security, the primary target area, or are there others? That's right, we sit at the intersection of physical and cyber security. This information can also be used to drive additional value over time, but right now we're really focused on achieving that mission, using these devices, this technology, to improve both the physical and cyber realms for Internet of Things. Chris, why don't you give us an example of how your technology might be applied? Sure, so very common one is active shooter. People are very concerned about active shooter. And so how can you leverage all the data that you have across different devices, different systems that you have out there in order to understand what happened and get people the right information at the right time? A more commonplace example might be something like a protest formation. So if you look at a university campus where you might have a controversial group meeting on campus and you need to get early warning when there's a protest forming on the other side, our technology will allow you to see that before it's gotten to a critical portion or before it's marching down the street. So why don't you take a deeper dive and talk about how are you federating these devices? How are you using these multiple devices together? Well that's exactly what we are. So we're a data analytics layer across all the silos of data that you already have in your environment. So as you look around, you might have motion sensors in your environment. You might have access control systems in your environment. You have wireless infrastructure in your environment. All of these things are used for specific purposes now but nothing's really trying to correlate and connect the data across all of them. So armored things, builds a layer across all of them, brings that data together to give you better understanding of what's going on in your environment. People and your physical space. Julie, talk about how the company came about. What are the origins? Sure, so I started working with Charles Curran, our CEO about two years ago at Qualcomm. We were really focused on understanding the security portion of the IoT layer and how to manage these things in enterprise. So if you're familiar with IoT in the household, there's been a lot of proliferation around turning your lights on, understanding who's at your front door, but in enterprise it's been much slower to adopt. Fundamentally we believe that part of that was because management took a lot of time. Every time you provisioned a device it took a number of minutes and because there was an intrinsic lack of security on each of the devices. So we went around and started talking to different potential customer groups about what it would look like to bring more IoT into their environments and we really got pulled into universities and large sporting and entertainment venues who we're still working with as our primary customers today because they saw a desperate need for IoT not only to save time on managing these devices and to make sure that they're secure in their environments but also to use them for physical security. So now that we've spent $15 million installing IP video cameras or a few million dollars installing access control systems, how do we actually elevate their use from what they were initially intended for? That spend has a secondary use when it comes to physical security, that ability to quickly get cameras on the scene of an incident, that ability to harness data coming off of motion sensors or environmental sensors. How do we use all of that information to drive an awareness of our environment day to day and then use it in critical emergencies for a better response? I understand you're working with some sports teams right now. Can you describe a scenario in which you might be able to help them manage crowds more effectively? So there was a great example we heard about two weeks ago from a top team who's recently hosted some World Series events. They had a fortunate incident where they were watching, they were hosting a watch party for the World Series in their venue during an away game and they handed about 40,000 paper tickets out. They got a great turnout. 20,000 people came to the venue but in the seventh inning of the game, the other 20,000 people decided that they also wanted to be in the venue in order to celebrate. That was a pretty unanticipated event. Usually in the fifth or sixth inning you start to consolidate your entrances, you start to consolidate your security personnel and send them to other parts of the venue and the net result of that was they ended up closing the doors, not allowing additional entrance in and tweeting that there wouldn't be additional people allowed to enter. There were a lot of security issues with letting 20,000 people in the seventh inning, not of the least as you don't know where they're coming from and you don't really know what their intent is and coming so late to that venue but there's patterns in the data that we could have seen sooner. So hypothetically, understanding that a normal game day has a couple hundred people entering in the fifth, sixth, seventh innings, seeing a significant uptick in that number of people coming into your environment should immediately say, what's unique? You know, what's different about this situation? Now how do I tie in my resources, my security personnel, my responders and just maybe notify people who are in charge of making these types of decisions so that we're not closing the gate and tweeting out to our fans that there's no more entries? And getting back to the technical nuances of this situation, how might your technology detect this crowd assembling before it was even visually apparent? Good question. So there's many, many different things. So part of what we do is rely on diversity of data from different sources. So that might be mobile devices, that might be from wireless, that might be from cameras you have there and doing occupancy counts on those cameras. It might be from other motion sensors you have in your environment. All of this data gets aggregated so that we can come up with a good understanding of population and flow within your environment. So we would have early indications and bring that awareness to people who have to respond, people who might be sitting in a network operation center and looking at other cameras, but not seeing the information. So we can bring the information right there, notify them that there's a problem forming before it's gotten to critical proportions. Fantastic. One more thought on that is there's kind of a unique advantage in data to go beyond what humans can perceive. When we're looking at these knocks, they have thousands of video cameras potentially united in one central screen. It takes not only having the right camera up, but also noticing a degree of difference that might be quite minute to actually see it as an anomaly in real time. So you can imagine a university campus where people are walking through the campus at a certain pace every single day. One day, everyone's walking just 30% faster, not running, just walking. Why? Is there a suspicious package? Is there someone gathered there that is attracting people that they don't necessarily want to be associated with or end up in a vulnerable position? How can we see that in the data faster than someone in the control room might notice it and alert people to respond? And with machine learning, of course now we have the means to do that. Chris, talk about the, it strikes me there must be a lot of complexity involved. You've got a great diversity of devices out there you have to connect to. Every institution would have a different fabric. How are you technically pulling this all together? Well, the nice thing about a lot of these technologies is there is standardization across many of these different types of devices. And there are, you know, there are tiers of players, right? And so we do have to be selective about who we integrate with. We are integrating with the top tier players in all these categories and we'll prioritize other integrations over time based on our customers and our market. So. And Julie, what are your plans for deployment? What's your timeframe? Well, we're looking to roll out our first generation of product in the next nine to 12 months. That really drives home at that situational awareness piece. So before we even get to building through incident response at scale, the ability to give people very specific cues during a critical emergency. How do we start with getting more information to the people who are there? So getting occupancy, flow, the dynamics of movement around a campus or a large venue. How do we start equipping the police personnel and security personnel to make better decisions and drive value from there? I understand there's no shortage of demand for the solution. We do have some top tier universities and pro sporting and entertainment venues who we're working with to build the right solution, not just the solution that we think is needed, but the solution that they're telling us, hey, we would really like to use something like this. I also understand you've pulled together a team, kind of a dream team. Talk about some of the people that you've brought on board for this operation, which few people have even heard of. Yes, so I think the first of those you're seeing here, so Chris joined us as co-founder and CTO and has been really an asset to this team given his background in cybersecurity from Carbon Black and before that. And if you wanna add more to that, please feel free to. We've also brought in, I would call it two pillars of our strategy, one on the physical security side and one on the machine learning data analytics side. And those two women are Elizabeth Carter who came to us from Apple where she led crisis management for the Americas. She previously worked at Chertoff Group where she sat at the intersection of physical and cybersecurity and before that actually worked for the city of New York where she understood weapons of mass destruction, different types of biological and chemical weapons response planning. So she's kind of the pillar of our physical security response, understanding and driving product. The other woman, her name is Claire Bernard and she recently joined us from another Boston startup called Tamer where she was running product and engineering for them. Claire's background is actually in particle physics. She was BU and Johns Hopkins and happened to work with the team that discovered the God particle while she was getting her PhD. So we think she's as smart as you can find and is going to help us think about these data challenges, the analytics piece at a scale that we think has the potential to really improve physical security and cybersecurity. I would be remiss if I didn't mention the rest of our team. Our CEO Charles comes from a background in the venture capital community and is just incredibly knowledgeable about the process of building a company from the ground up and has many skills when it comes to recruiting as well. Really helped drive some of these hires forward and the rest of the team is the next generation of rising stars. People from Oracle, HP Vertica, other carbon black individuals, people who just have experience from across the board that's going to help us build the right solution. And at a time when diversity has been a major issue for tech companies, I understand your team is unusually well represented. I think our executive team is about 60% women which we're very proud of. I think our team in general might actually be about 60% women which we're also very proud of. And I'd like to say that that's organic, that we've worked with some great advisors and potential customers. And I do think that from my perspective, it's been helpful to have younger women coming in who see a path forward for senior women and executive roles in their company. I think that's something that can't be underestimated. Where do you stand in funding right now? We just closed our first institutional capital about a week and a half ago. We're still finishing the close of that round but we have a Boston based partner who's very focused on machine learning and analytics and also has been a well-recognized investor in the cybersecurity realm. So we're very fortunate to have this investor as our partner and excited to keep working with them. Chris, as someone whose background is in cybersecurity, how do you see the security landscape changing now with the IoT coming on and the possibility of really transforming the way organizations look at their physical and cybersecurity operations? Good question. So over time they're converging and they're converging, I think, more rapidly than we expected. So I'm going to step back a little bit and say that there's a lot of parallels. Cybersecurity, I think, is probably about five years ahead of physical security in terms of maturity of technology and approaches to problems. And so what we're seeing right now and we're part of the force behind that is taking the learnings from cybersecurity and applying them to physical security, right? So when we talk about situational awareness, when we talk about the data analytics that supports that, and when we talk about incident response and orchestration automation, all of those are core to taking cybersecurity and applying it to physical security. In terms of convergence, we're seeing many cases, and this is going back a number of years, where people are using cyber events to create physical problems, right? Stuxnet is a classic example, but you can do the same thing by taking over something and instilling panic in a stadium and causing all sorts of grief, cyber driving physical. You can also see cases where people who are running cybersecurity operation centers want access to physical knowledge of their environment in order to do their job better. Whether it is a malicious insider that they suspect, whether it's an infection that occurs on a particular machine, being able to pull up the cameras, know who was there at the time, bringing all that information together is again necessary in order to understand their perception of situational awareness. So to converging towards one, we're going to be building towards that goal from our perspective. Now the flip side of federating IoT devices is that the bad guys can do the same thing. So you potentially have a much broader attack surface. That has to be factoring into your thinking. What is these embedded security in your platform? So we're not going to address fully that right now, so we take advantage of best and brief security principles in our design, both for security and for privacy. But in terms of the dependency we have on a lot of IoT devices and IoT systems, part of what helps us is diversity of data across those and diversity of devices. And so while you might have compromises in specific cases, the fact that you are dealing with so many and so many different categories at the same time allows you to maintain and fulfill your mission and deliver what you're trying to do, regardless of some of those individual compromises. We're also in a unique vantage point where we can actually see the operational integrity of what's going on. So when you look across all those different categories and you look at the data that we're collecting, whether it's malicious or not, we're able to identify a failure and bring that to the attention of the people who are dependent on those systems. So we can be an early warning to cyber events, malicious or not. Julie, entrepreneurs love to dream. I'm sure you are thinking big beyond the immediate cybersecurity applications. Where could armored things eventually go? It's a great question. The dream is that we become not only the dominant solution for physical and cybersecurity for schools and large venues, but we bring our solution into K-12 where some of this is desperately needed. That's kind of the mission orientation of our team. How do we start to drive value in a way that we can get to every school in the country sooner? In the longer term, though, I think there's a lot of opportunities with IoT and we're still kind of at the tip of the iceberg here. We're gonna see all sorts of new devices come online over the next two, five, 10 years. The growth of these devices is incredible. And the question is how do we continue this challenge of solving the data at scale in a way that continues to drive value, not just for some of the first use cases which are often around marketing and understanding an environment in that sense, but also continuing that physical cybersecurity angle? Enormous potential. And I hope you stay based in Boston. We can use more companies like that. Chris Lord and Julie Johnson, thanks very much for joining us today on theCUBE. Thank you. Armored Things, keep your eye on them. You're going to be hearing a lot more about this company in the coming months to come. I'm Paul Gellin, this is theCUBE.