We've got robots running [24/7/365] in 15 states across the US in all four time zones.
Stacy explains how Knightscope is using always-on robots to protect their customers and their businesses
Ben Newton: Welcome to The Masters of Data Podcast, the podcast that brings the human to data. And I'm your host, Ben Newton. One of my favorite parts of hosting this podcast is talking to really cool companies doing cool things with technology. My guest on this episode, Stacy Stephens, executive vice president and chief client officer at Knightscope fits that bill. Stacy and his co-founder created Knightscope with a lofty mission of making the United States of America a safer place. They are working towards this goal with robots, robots that are running autonomously every day, all day, and have demonstrably made their customers safer. So without any further ado, let's dig in.
Ben Newton: Welcome, everybody, to another episode of The Masters of Data Podcast. And I think we've got a very interesting episode for you here today. We get to talk to a lot of very interesting companies, and I think in particular the company and the founder of that company we're going to talk to today is going to be very, very interesting to talk to. So we're talking to Stacy Stephens today, the EVP and chief client officer at Knightscope. Welcome, Stacy.
Stacy Stephens: Good morning, everybody. How are you?
Ben Newton: I am good. I'm excited to talk to you here. We talked a little bit about this when we had our first conversation, but it's really cool. We'll get into more of this. But I mean, basically, you guys build robots. And I saw that robots at ... I've actually realized I've seen them a couple places now. And when I got introduced to you, I was super excited to talk to you about this because what you guys are doing is really neat. So I think this is going to be a fun discussion.
Stacy Stephens: Well, thank you. I'm super excited. I'm always excited to talk about it. But what gets me pumped up is I've got three kids. And my kids get to tell their friends that Daddy works on robots. And it's pretty extraordinary to see their faces go, "Uh, uh," so it's a lot of fun.
Ben Newton: Yeah. Yeah. I expect that you can win easily like bring your daddy to work day.
Stacy Stephens: It does play well into the new robotics programs that are coming up in schools nowadays. I get pinged quite a bit for that. But yeah, it's a great topic to talk about.
Ben Newton: Yeah, no, absolutely. And so I want to get to Knightscope and a little bit more about what you do. But as always, I think it's important to humanize the people that I talk to. And I think particular, you definitely have an interesting background. So maybe talk a little bit about: What was your journey to arrive at a robotics company? What's your background? What's your story?
Stacy Stephens: Well, it couldn't be more convoluted, I don't think, if you had scripted it. But it's very interesting. I was born and raised in Texas, grew up in the Dallas Fort Worth Metroplex, so die hard Cowboys fan and super proud Texan, as most of us are. But my growing up, I originally thought, "I want to be an attorney," and then I went and worked for one, and I ruled that out super fast. Then I had a huge passion for aviation, for airplanes and flying. I was very, very fortunate to be able to learn to fly at the age of 15. And so had a tremendous appreciation for aircraft and the like. So I decided, okay, well, I can go study aerospace engineering in college and go and design aircraft.
Stacy Stephens: And unfortunately in the early '90s, that kind of all blew up because defense budgets were cut, and all of the aerospace engineers who were previously working on these nice governmental projects flooded the civilian marketplace, and nobody could find work. So I was putting myself through college working full-time, and ended up working for one of the world's largest financial companies. And 10 years passed, and I turned around and went, "Okay. Wait a minute. This is not the direction I wanted my life to go." I had a very good friend of mine who was a police officer in the Dallas Fort Worth Metroplex. And we were together one night, and he had asked a group of us, "Hey, any of you guys want to go for a ride along?" And I said, "Okay. What the heck is a ride along?"
Stacy Stephens: He laughed at me and he said, "It's exactly what it sounds like. You come ride along with me." And so I went to ride along with him one night. I figured, hey, if nothing else, I get to hang out with a buddy for eight hours and see what he does. And I absolutely fell in love with it. I had this feeling in me that, that's really something I needed to do. And so I started doing ride alongs with other departments. And after about six departments, I said, "You know what, this looks like something that I need to do as a profession." And I went and sought out the ability to become a police officer. I went through the police academy, got sponsored by an agency. And I graduated valedictorian. I was very, very fortunate, and put a lot of hard work into it, obviously.
Stacy Stephens: But went and became a police officer, and I absolutely loved that. I enjoyed the work. I enjoyed that every day was different. And it was what I could make out of it, so I was as busy as I ever wanted to be. And I latched onto it. And fast forward a few years, I had my first child and started to have to make some adult decisions. And I decided at one point in time that there was a better way to serve the law enforcement and public safety community if I were to start my own company. And the very first company I started, I co-founded a company that was building police cars from the ground up. And it was a fantastic company, built that up over the course of about 11 years, had $1.2 billion in pre orders and sales for that vehicle.
Stacy Stephens: And then in 2012, we lost our funding. And so $600 million flew out the window overnight, and we were looking for something else to do. So what any good entrepreneur does when they get knocked down is they get up, dust themselves off and start over again. And so we did that. And about that time, Sandy Hook happened. And then very shortly thereafter, the Boston bombings took place. And obviously, I'm still very ingrained in the law enforcement culture and community and active groups that are associated with law enforcement. And one of the groups that I belong to was doing a study on active shooters, and specifically on Sandy Hook. And the bullet point that came out of that, that really was the catalyst for what we do today was that if we were able to get officers into Sandy Hook just 60 seconds sooner, we could've saved as many as 12 lives.
Stacy Stephens: Well, as a father of three, former police officer and entrepreneur, that made the hair on the back of my neck stand up. And I really thought, "Okay. This is a problem worth solving." This is something that we need to try to figure out how to do something about. And my business partner, who came out of the automotive sector, he didn't ... I mean, aside from the fact that we'd been working in public safety, he's never done the job, never really understood how police function and so forth. And he just asked me the naive question that I think most people do naturally ask. And that was, "Okay. Well, why don't officers just get in that school faster and blow the guy away, or take care of the situation, do whatever they need to do?" And that's all dramatized by what you see on TV. But unfortunately, that's how you get more people killed.
Stacy Stephens: And so he stepped back and he said, "Okay. I get it. I get it. But what do we do? How do you actually bring these things to a conclusion much faster?" And the only way to accomplish that is through actionable intelligence. And the only way to gain actionable intelligence is through some form of eyes and ears on the scene. And so that's what really started us down this path of robots. We started looking at cameras and artificial intelligence and video analytics. But that's become such a commoditized market that we did not want to get lost in this sea of competition. So Bill, my business partner, he came out of Carnegie-Mellon, the number one university on the planet for robotics. And he called up a few folks there and said, "Hey, we'd like to meet with some of your brightest talent that you have." And approximately eight months later, we had our first robot, so that's kind of how we started Knightscope.
Ben Newton: This is really neat. I had read some of that in an email. Hearing you tell it, I think there's a lot of companies start for a lot of different reasons. But I think that's a really inspiring story. And I think in particular when you look at your guys kind of model your mission to basically make the world a safer place, to make America a safer place, I think that's a ... I mean, it's not something you're going to hear with most startups these days. I think that's really, really neat.
Stacy Stephens: Yeah. We used to joke about, during the time when we started the company, of course everybody was funding the next new social media app. And we thought, "Okay. Yeah. That's all fine and good. But how does that change the world?"
Ben Newton: Right.
Stacy Stephens: You know? And we wanted to figure out a way to really make a material difference and change the world. And I think everybody's sick and tired of turning on the TV and seeing about some kind of bad news, no matter what it is. And this we felt like was a way to make a much more positive and meaningful impact.
Ben Newton: Yeah. And one thing, reading a little bit up on how you guys started, I mean, this was obviously not an easy thing to do. I think I saw some pictures of you had a first robot put together, and it looked like it was really quite the science project for a while. So what were kind of the challenges when you guys started out? It was obviously, I'm sure, very challenging. What were the kind of things you remember being the biggest hurdles to get this going?
Stacy Stephens: Oh, my God. Well, obviously, nobody had ever done this before. $80 billion has been invested into autonomous vehicles, but I can almost assure that nobody has arrived, nobody in our audience today has arrived at their work, or even going out on their leisure, in a fully autonomous vehicle. So it was very arduous and a scary task to kind of go down that path of, okay. How are we going to put something that moves on its own in these very public, complex environments? So we went through a lot of exercise of form factor. What are the machines going to look like? And what's the drive train going to be? How are we going to protect them against damage? There were so many, many different things. And it just got more and more complex because building something in a lab is one thing.
Stacy Stephens: Once you get it out into the real world, it's entirely different. So that's why, I mean, that's probably the thing that kept us up the most was once we put something out there. What's going to happen? And it's funny because in the very early days, the very first robots that we put out, we put out in front of our offices in Mountain View, California. And we literally had volunteers sleeping at the office overnight because we were scared to death of what was going to happen to our robots that we had just left running around outside the office. And so we did that for a considerably long time before people said, "Okay. It looks like they're going to survive. And people in the area are going to respect them."
Stacy Stephens: So then slowly we started to navigate out into the client world and start to kind of release them. But I think those were the scary times really, was just one, figuring out how to ... What's going to be our secret sauce? How are we going to make these work? And two, putting them out into the public domain amongst the completely random.
Ben Newton: Yeah, because you reminded me, I don't even remember the name of the company. But there was some company here. I think they were in Redwood City. And they may have been in San Mateo, California right nearby. But it was they had a little delivery robot. It was always some guy with an iPhone following it to make sure nobody did anything to it. So I can totally visualize that. And one thing too as part of that, I think when I was kind of reading more about what you guys were doing, I think obviously, at least anyone from my generation, or maybe I'm the only one, but when you think security robot, or a robot that's helping in that area, you're immediately thinking RoboCop or something, some sort of something in that ilk. But it sounds like a lot of what the system is doing right is it's helping process a lot of information and having more basically eyes and ears in more places. Is that right?
Stacy Stephens: Absolutely. And you bring up a really good point. People, the whole pop culture feeling about the robots, it kind of brings thoughts up into different people for different reasons. You have the Orwellian folks who are looking at this scared to death that the government's going to take over. And you have the sci-fi fans who look at this and go, "Wow. We got R2D2 and we're going to have friendly service robots." And you've got the people who look at the RoboCop and they think that the robot uprising is coming. And it really, it kind of hits you from all different angles. Right?
Ben Newton: Yeah.
Stacy Stephens: And that was one of the things early on we had to tackle was: How are we going to make these? How are we going to walk that fine line between the pop culture side and the reality side of what they're doing? And really, where we landed on that was the design was going to be incredibly important. So I'll give you a quick for example. If we had put these on a tracked propulsion system, and we had made the body language on the robots very angular, very stealth like, and we'd given in a matte black paint job, and made all of the lights on it red, that has a dramatically different appearance to somebody. And it evokes a different set of psychological feelings in people than a soft, curved, white, very light colored, airy blue light, being. It's incredibly different how that portrays itself in these public environments. And that's how we kind of approached this, was we wanted something that was going to have a commanding presence, but something that was still friendly and approachable, for lack of a better way of putting it.
Ben Newton: No, no. That actually makes a lot of sense. Hearing you describe it, it really does connect in my mind because I think when ... Yeah. I believe I saw the one that you guys were running for a while at Stanford Mall in Palo Alto, California. And then I believe I might've seen one at Samsung. Yeah. I think that was the thing that struck me because I was there with my family, and my kids were fascinated. At first, I was trying to figure out what it was because, again, it doesn't fit that mental image of what the movies at least I watch. But also, yeah, it was a friendly presence. Once I figured out what it was doing, it kind of made a lot of sense. But to your point, it's doesn't fit any of the cultural stereotypes that we're thinking about how you'd be interacting with a robot, for sure. So I think that's really impressive how you guys have done that.
Ben Newton: And one thing that would be really interesting too, I remember reading through a lot of the material that you guys have on your website, you obviously have some really interesting stories, where it's actually already made a difference. Because like you were saying, I think you maybe alluded a little bit more to this. Well, first of all, you're basically the only company out there that's actually running fully autonomous robots 24/7, 365. Right?
Stacy Stephens: To my knowledge, yes. And nobody's challenged us on that yet. We've been to a lot of different events. I just came back from CES out in Las Vegas, which was absolutely surreal. And yeah, I've not come across another company that's running 24/7. That's super humbling for us and very exciting, and also very scary because that to me means we have a tremendous responsibility to other companies that are looking at doing this. So yeah, it's really cool. We've got robots running currently in 15 states across the US in all four time zones. And here we are, humble little company out in Mountain View, California.
Ben Newton: That's really neat because to your point, one thing about being in the Silicon Valley here in California, I see the "self driving cars" all the time. But there's always somebody in the front seat. I can remember it's not that ... I think I was in versions of that in college. They've been working on that for a long time. And it's still in this kind of nascent stage, and you guys have taken and made these practical. Do you have any favorite stories to share? Because I know what I've done in my career, there's always those stories of how customers have used something that kind of stick with you and kind of define how you describe what you do. Are there any ones like that for Knightscope you're able to share?
Stacy Stephens: Oh, yeah. Definitely. There's a few probably that I could share with you. One actually ties right back to what we were just talking about with regards to design and how the robots are viewed in society. When we first deployed one of our robots at a very large hospital network, there was some apprehension in folks and saying, "Oh, what's this new tool? And what are you guys doing with it?" And it's new technology, I get that. There's people who are going to doubt the validity of it and everything. And that's to be expected. But what was not expected was, I guess it was probably three to six months into the deployment, we had sent a service technician out to perform some kind of service on the robot. And we got a phone call from the service tech very shortly after he was dispatched.
Stacy Stephens: And he said, "Hey, I just wanted to let you know what just happened. I was repairing the robot. I'd pulled a couple of panels off and was making some repairs. And I look up and there's four nurses surrounding me." And he said, "Hi. Can I help you?" They said, "What are you doing with our robot?" He said, "I'm fixing it." "You're not taking it anywhere, are you?" They said, "No. We just had some routine maintenance to do it, or service." And they said, "Okay. Well, good because he makes us feel safe." And a couple of things came from that. One was it was very personal to them. Two, it had, they referred to it as a he. And that to me kind of resonated as something very next step-ish, for lack of a better way of putting it because they made it more human, if you will.
Stacy Stephens: And three, they were able to convey that previously, when they go out to their cars in the middle of the night, they were nervous. They were scared because it was an unsafe area. And the crime in their area in that particular location, once we deployed the robot, dropped down dramatically.
Ben Newton: Wow.
Stacy Stephens: And it made them feel safer. And so they wanted to ensure that their safety was continually protected by making sure that robot was going to stay there. And that robot is still there to this day. But I thought that was pretty extraordinary that the people who were there that we were really focused on protecting felt protected, so that was incredible.
Stacy Stephens: Another more recent one, we had an incident that occurred at one of our clients up in the state of Washington in Seattle. And the district attorney's office called me directly, probably six, eight months ago. Said, "Hey. We just wanted to let you know this is one of the most unique cases that we've ever had, where 100% of the evidence was being provided by one of the victims," because in this particular case, they had three felony charges on an individual, two for burglary, he broke into a couple of different buildings, and one, he actually attempted to damage one of our robots by ramming it with his car.
Stacy Stephens: And the "victim" was the robot. And the robot recorded high definition video of the incidents, the license plate of the individual, individual description, description of the vehicle, direction of travel, time of event. And it had everything. And the disposition of the case was just released in December. And all three felony charges were pled guilty to. And that was for us, huge, huge win, and super exciting also because again, this was in an area that was previously not covered by any other type of security because it was a remote location for this particular client. So they were adding in another layer of security to an already robust security program. And it ended up solving three very big crimes for them.
Ben Newton: Wow. Well, how was the robot after? Did it [crosstalk 00:22:26] or anything?
Stacy Stephens: It was fine. Yeah. No. Fortunately, we offer this as a subscription service, so we take care of our robots. And when something goes wrong, we triage it. We put them through emergency care, and then we get them back to work as soon as we possibly can. So yeah, that was very exciting also. And then lastly, when we started this company, we had these grand visions. I talked about earlier that we wanted make a material difference in people's lives. And our vision was that we hope to some day be able to say that we helped make the United States of America the safest country on the planet. And so we had this grand vision that 10 years down the road we would be able to tell anybody, "Hey, anyplace we deploy a robot, we're able to reduce crime by 50%." That would be a tremendous win for us. Well, what I can say is that just in the short time that we've been deployed, we have had already numerous clients saying, "Hey, yeah. We actually have had tremendous successes here. But it's not just 50%, we have 100% reduction in crime."
Ben Newton: Wow.
Stacy Stephens: And that just blows my mind, absolutely blows my mind. So for example, last year, April of last year, XPO Logistics put out a press release. And they said in the first six months of using the robot, they saved $125,000 in six months, a quarter of a million dollars annualized. They reduced crime on their campus by 100%. And they are now looking at expanding to multiple different locations.
Ben Newton: Wow.
Stacy Stephens: In the press release. I mean, I actually was caught off guard because they contacted me and said, "Hey, would you like to give a quote for this press release?" I said, "Sure."
Ben Newton: And that's not usually the way those kind of things happen, to be very clear.
Stacy Stephens: No, no. And then this month, the Huntington Park police department, they were our first actual police agency who was using this. They had a real big problem in one of their city parks. And it was a new area. It's a fabulous little location because they've got basketball courts. They've got all this recreational space and places for people to come. But they were having a really bad problem of crime in the area. And so they just put out the statistics from the previous year for same six month period as 2019. And they said in that year's time, they had a 10% reduction in calls for service. They had a 46% reduction in crime reports, a 27% increase in arrests, and a 68% reduction in citations issued. So I mean, that's phenomenal, phenomenal statistics to be able to say a security robot helped in this way. So those to me are the things that just get me super pumped and keep me excited every day and getting up and going to work and doing so with a giant smile on my face.
Ben Newton: Yeah. I can hear it. That is really exciting. And one thing, just to kind of ... Particularly with being this is a Masters of Data Podcast, one of the things that's really interesting to me there is that, basically, these robots are constantly collecting data. And how does that actually typically work? Are the clients themselves monitoring it? Or do you guys monitor things for them and kind of write it back? Or does the robot do a lot of triaging of the data itself? How does that work?
Stacy Stephens: Yes, yes, and yes. So a few things. One, I think it's incredibly important for everybody to understand. The technology that we use is no different than anything that people encounter today in any situation, whether you're going to the grocery store, to your bank, to the shopping mall. What we do is the same type of work and surveillance that every responsible company does. So we're not collecting your personally identifiable information. I can't go through your phone and your text messages and things like that. But what we can do is we can collect forensic information that can be used either to prevent and deter crime, or the flip side of it is to be able to do investigative forensics, so that's what is very important. Each one of our robots pulls down about 90 terabytes of data per year.
Ben Newton: Wow.
Stacy Stephens: The majority of that is in video. But we're doing a number of different types of analytics that are all being, as you said, triaged by the robot to say, "Okay. Is this an anomaly for this environment at this time of day in this location?" And then once that anomaly is detected, it is then reported back to a security operations center of the client. The client actually owns that responsibility and that information at that point. And they then with the whole idea of having humans in the loop, because you want there to be somebody who's making those critical decisions, they're the ones who are deciding. Okay, is this something that we need to either dispatch a security guard or law enforcement to handle? Or is this more benign and something perhaps we need to keep an eye on? Or is it completely normal? So that's kind of how the process flows.
Ben Newton: Yeah. No, that makes total sense. And I think your first point is really essential. I mean, it's not like this is over and beyond in terms of what you would ... Because every time you walk into a store, or a grocery store, or 7/11, you are on video. But this is something you're making a more effective way of doing that that's not ... It just feels like it's both a more visible and a more effective way of doing a lot of the same things. That's neat.
Stacy Stephens: I get asked all the time. Well, how's this any different than CCTV, or closed circuit television, the little security cameras. And there's a few things. One, in my career in law enforcement, I can honestly tell you that the number of times I got called out to some sort of crime where they had security cameras on location or in place nearby, the amount of times that I was actually able to get something usable, something that had evidentiary foundations for being able to solve a crime, was next to none. You'd go up and you'd say, "Hey, I see you've got security cameras." And they kind of look at you, and you can see they're getting sickly just by you asking that question.
Stacy Stephens: And you say, "Well, can we get the footage from it?" Well, a few things, one, it's either the cameras were old analog cameras and the footage is horrific. Two, the angle that the cameras are at provide almost no evidence. I'm a bald guy, so if I walk into a store and you take a picture of the top of my bald head, how are you going to identify me? It's not going to work. Three, well, the cameras are there just for appearance. We don't actually record anything. We wanted to try to deter people, and that doesn't deter anybody if you're not doing anything.
Stacy Stephens: Four, we don't retain the data, or worse, they're broken and we're not recording the data anymore. And so cameras themselves have become a little bit less than useful than what they used to be. And most importantly, they're not ground level. They're not eye level. So the quality of what you have for identifying a subject who may have just assaulted somebody, or broken into something, or stolen something, that doesn't exist, or it doesn't exist to the degree that is incredibly helpful. That's one thing that we wanted to make sure of, is we have this five and a half foot tall, three foot wide, 400 pound robot that has cameras a full 360 degrees around it that allow for this super high definition, even 4K recording capabilities, and gives you very, very excellent quality of ground level surveillance.
Ben Newton: Yeah. No, that actually makes a ton of sense because that's kind of the thing that is missing in those kind of stationary cameras is being able to react to a situation and get something that's useful and kind of tailored that can actually move around. Yeah, that makes total sense.
Stacy Stephens: And let's face it, people who are doing bad things do not want to get caught.
Ben Newton: Yeah.
Stacy Stephens: They don't want to spend the night in jail. And when they see this large object, I think when we talk about the statistics of how well they've performed, a lot of that comes from the fact that we have this very conspicuous, very obvious machine that's moving around. And if you equate it to something I think everybody can relate to, if you're driving down the road, and you're behaving yourself, not doing anything illegal, you're just driving down the road, and you look to the side of the road, and you see a marked police car. What's the first thing you do?
Ben Newton: Slow down.
Stacy Stephens: You're behaving. You're not doing anything wrong, but you subconsciously know, hey, I need to be on my best behavior. I need to be on [crosstalk 00:31:57].
Ben Newton: Right.
Stacy Stephens: And I think that's what the robots are having a similar effect of doing, is people don't want to get caught. They don't want to spend the night in jail. They see this robot moving around. They raise an eyebrow. I can go down the street where one of these robots is not and do the same thing and not get caught.
Ben Newton: Yeah. That makes a ton of sense. And obviously, I could talk to you about this for a long time because I think this is super, super interesting. I think where you guys are going with this, it's going to be exciting to follow the company. And one thing that you brought up when we were talking before that I thought was really interesting, kind of taking a little bit of a right turn here, is that beyond the way that you guys just build the robots, the way that you have raised the money and the way that you guys actually funded the business is different. I think that's one thing. It hadn't really ... I knew something about that. But when I was looking at your website for the research for the podcast, and basically seeing a button to click and invest. It's again not typically something you see with most startups. So talk to me a little bit about that. I mean, what kind of model are you guys using to fund the company? And how's that different?
Stacy Stephens: A couple of comments. One, it wasn't enough for us that we were dealing in the top three technologies on the planet, artificial intelligence, robotics, and self driving technology. That wasn't good enough for us. We had to go out and do something completely different on the fundraising side. So I will say that all disclaimers and legal things in place, legal counsel's not in the room right now. But I have to tread lightly on what we talk about on the financial side. But the interesting thing on what we do for raising money is that there's conventionally you would think the normal route of going out and raising money is you go find a venture capital fund or some kind of private wealth fund that is going to come and supply you with money to go and build your dream. How that typically plays out is in a venture capital world, they will come in and they provide a tremendous amount of value because they know about, for example, software startups. They know how to do apps. They know about the social media stuff that we talked about before.
Stacy Stephens: But finding a venture capital company who knows how to build large scale hardware outdoors, who is an expert in security matters, and who understands everything about self driving technology all rolled up into one. It doesn't exist. It doesn't exist. So back in 1933, there was a 1933 securities act, which if you can recall back after the great depression, there were a lot of snake oil salesmen going out, and they were conning people, mostly elderly, into giving them their life savings for whatever snake oil is going to cure all of their ails. And so the government stepped in and said, "Nope. No more. In order for you to invest in a privately held company, you have to meet certain criteria that we are going to set. And not only are you going to have to meet criteria, you as a privately held company cannot even tell anybody that you're raising money unless you have a preexisting relationship with it."
Stacy Stephens: So if I just met you, I couldn't tell you, "Hey. Hi, Ben. I'm Stacy. I'm with Knightscope. We're raising money." I have to already have some kind of established relationship with you first. Then later on down the road, I can tell you, "Hey, we're raising money if you're interested and meet the qualifications then you can do so." And those qualifications again set in 1933 were you had to have a million dollar net worth, not including your primary place of residence. Or, these are either/ors, they're not all collective. So you had to have a million dollar net worth or you had to have as an individual a $250,000 a year annual income for the past three years with the expectation of doing the same next year, or combined household income of $300,000 a year, again, for the past couple years with the expectation of doing the same in the following year. Or you had to be an officer of the company. And that law has been in place since 1933. Okay. Can you tell me, have things changed a little bit since 1933?
Ben Newton: A little tiny bit.
Stacy Stephens: A little bit. So thankfully, finally in 2012, the jobs act was introduced and passed. And that changed how investment monies were allowed to be raised. And so we took advantage of that and we did a crowd sourcing for being able to raise money to do what we are doing today. And the reason we elected to go that route was A, the aforementioned problem with the typical route of raising money. But B, as I said before, people are tired of seeing the bad news. And we felt like this was something that the general public would get behind and be passionate about, and they would feel like it was worth investing in.
Stacy Stephens: So anybody can go to our website at knightscope.come, click the little invest tab up at the top of the page, and you can get all the information about what that means. But to date, we were the largest [inaudible 00:37:42] crowd funding raise that we're aware of, $28 million. And we had over $5000 investors that invested in that.
Ben Newton: Wow.
Stacy Stephens: I think that kind of speaks volumes to what I said before. People are tired and they want to do something different. And so now we have a second raise that's on that same platform.
Ben Newton: Wow. That's really neat. I remember when that first came out I thought it was interesting, but you didn't ... At least I didn't see a lot of interesting activity around that. You're right. It totally makes sense with what you guys are doing. It's something that people can understand and that they can connect with and that can very easily ... It's very easy to explain how it could affect their day to day life, and so I think that's really neat.
Ben Newton: Well, this has been an amazing conversation, Stacy. I think what you guys are doing is, it's important, it's interesting. It's both cutting edge and really kind of getting at the core of what people care about is feeling safe. And I think that's super important, super interesting. And maybe just to kind of wrap a bow on it, what's next for you guys? What's on your mind now? Where do things go next?
Stacy Stephens: So as a matter of policy, I typically don't share kind of what's on the horizon. However, I think there's a couple of things that I can say that are quite interesting. One, obviously anybody who's ... We're a commercial style product, so anybody out there in the commercial world who's trying to figure out how they can take their security to the next level, please visit us at Knightscope.com because I can set you up with one of my team to do a full virtual demo and literally get to see a live demonstration before your very eyes. So I can do that too.
Stacy Stephens: We have an already commercialized K1, a K3, and a K5. And there's a lot of numbers that fall after that, and I'll just leave that at that. Three, we have been working very, very hard on the next feature of the robot, which is visible weapons detection. We already have a working alpha prototype that is doing extraordinary work in detecting weapons of multiple different types in invisible situations, so obviously it's not going to find anything that's concealed at this point. But one of the things that we're doing right now with the financing that we're raising at the moment is we're advancing that development as quickly as possible because I think everybody's tired of hearing about shootings of any kind. And if we again provide just a couple of seconds of extra notification of a weapon being brandished, then we're going to be able to help save lives. So I think that gives you a little bit of a flavor of kind of the direction that we're heading and really how we're viewing this technology on a go forward basis.
Ben Newton: Yeah. Wow. That's amazing. Well, rooting for you. I think you're excited to see where you guys go next. So again, Stacy, thank you for coming on the podcast. I think people are going to really enjoy this. And maybe we can bring you back on again when some of those things come out and talk to you about them. I think that's super interesting. Thank you for coming on.
Stacy Stephens: I look forward to it. Thank you so much, Ben. I appreciate it.
Ben Newton: Absolutely. And thanks, everybody, for listening. And as always, look for the next episode in your feed and check us out on iTunes, rate us so that other people can find us and enjoy awesome content like this. And take care, everybody, thanks for listening.
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