>> Hello everyone, I'm John Furrier cohost, founder Silicon Angle media, we are here in our Palo Alto studios for cube conversation with your Juergen  Linder, who's the senior vice president of Oracle SaaS. You're getting great. Great to see you again. Thanks for coming in. Appreciate, uh, the time senior vice president of ERP, SaaS, you handling all the business aspects of the Oracle cloud is correct. And you'll lots happening. What's the big, the big story right now? >> Well, here at OpenWorld, it's, it's a little bit of a kid in a candy to your point, I do think it's fantastic that we can store. I mean, showcase our innovation capacity. What we have really done and you're going to see most of those announcements are around how we pervasively infuse emerging technology into our product lines. So not just a sidecar concept, but productizing out use cases where customers can reap an immediate business benefit as of day one. So allow me maybe to plow through some of those. There is a lot of it, um, what's happening and one of the big ones is certainly around cloud ERP. If it's a huge investment for us, we'd like to think it's the most strategic SaaS investment you will ever do. From that perspective. We're very committed to make sure that the emerging technology is applied for business impact. What I mean with that is take examples such as, um, intelligent payments. So imagine you have a cash surplus all of a sudden, which is a great position to be in, but two, how do you allocate it to strategically cultivate supplier relationships based off in the moment data based on machine learning suggestions. Think about the change that we're seeing out there in terms of business models. I mean product as a service is a completely different model in which our companies need to operate. So this entire motion of shipping transactionally into going into a service provider model is huge for a lot of companies and oftentimes they have multiple business models to cater to. So big announcement, this open world is subscription management, which is a unique offering where we have really plowed together the combined strengths of our customer experience cloud to handle seamlessly the customer facing interactions. So sales, service, marketing type of pieces. But teamed up with our ERP offering to really have all of the billing, the renewal cycles, the um, revenue recognition seamlessly solved in one offering. So big announcement for us. >> So on the subscription management is that for the ERP years at Oracle Cross, all oracle portfolio products are specifically ERP. >> It's both actually, it's, it spans the customer experience piece, but it's also natively embedded into the Oracle ERP cloud to have it a seamless experience because we don't think that you can solve subscription management in isolation. Oftentimes you feel vendors who does it on the customer experience side, but then you'd still need to have the backend features to make sure that you can deliver on the promise that you do understand the customer intimately, that you could do effective up cross sell and handle the renewal cycles. Constantly tap into the customer sentiment to see if they're happy and just see them grow. So we'd like to think it's really a combined effort between what we have as customer experience and the ERP side >> I mean, this brings up a great point because I think you're hitting on the major trend that's happening around Oracle open world, certainly in the industry right now that is integrating a lot of different functions. I mean ERP, they want knows ERP was lifted the days that's really critical software and it powers the business. It's not going anywhere. What people are concerned about, how do I extend the capability of the data that I have? Yes, and cross connected so that it's seamless, so I want to just go a little slow on the subscriber management thing. So what you're saying is you upgraded subscriber management so that the customer can manage their piece of their business without mangling or changing or tweaking any of are taking me through that. I was at. How are they rolled that out? What's the use case of that >> I think this is important to hit on the key point which is data mean. specifically? They give an example. What Oracle always has been synonymous with is owning, managing and securing the world's data. We'd like to live on that heritage for a while because we think it's fundamentally differentiating. If you want to bring those emerging technologies to life for outcomes, um, since we're covering all lines of businesses in the cloud and are ready to go today, it brings us into a very unique position to really stitch together data points very elegantly across a unified data platform, right? Where data travel seamlessly. Because if you think about a subscription business, there's so many aspects that goes into that. Think about conducting, collecting sensory data based on Iot. >> A lot of databases are out there and you have multiple databases you're hitting. >> Oh absolutely. So we want to make sure that obviously any data that we're collecting about the usage of a given product allows us to find tune the business model for subscription. If we have the customer or if the company made a decision to go into a subscription model, it's huge from a revenue recognition perspective, how do you report that out? It has to do with how do you service the customer constantly predict and anticipate the very next move four up and cross selling type of mechanism. So it's a big movement. >> Customer intimacy used to be a cx problem, now it's an integrated data problem and it's interesting because, you know when I broke into the business when I was graduated from college, the word data processing was a department when you guys were in the database business mean data processing now is a core competency that's not limited to one siloed system or one abstract system like an ERP or cx. It's managed to everything. So you have to do data processing because that's the value. So if, if that's the case and more data is coming to the marketplace, you need machine learning, you need to have the tools. So I gotta ask you Oracle Open world, you guys are doing some announcements around Ai. What's the impact to ai particular or using or managing whether it's symbolic systems, which is a little bit different in ai reasoning. Is is a thing processing and reasoning around the data now you need ai for that. So what are you guys announcing around ERP, oracle cloud and ai? >> So it's fundamentally that, to your point, I had the pleasure of implementing ERP system at customer side on the sis side. I had problems or challenges in my business career to bring them to life on the software development side, but fundamentals have stayed the same. You need to have data consistency and as a complete view of the business. Now, to your point, I'd like to think that machine learning and emerging technologies at large provide a new canvas on how you can create and look at every single business process as we know it so you see us talk about it because I'm all about intelligent process automation in the ERP context. What that means is if you take a typical company, about 85 percent is spent on keeping the lights on, closing the books, doing all of the in hyphened, mundane but necessary stuff, and 15 to 20 percent is typically dedicated towards innovation of new business model. Serving customers with new business model or just being the change agent that typically the finance function wants to be. I mean, there's a reason, for example, why Kraft Heinz had a cfo or has still has a CSR, was 29 years old. They're not hired necessarily for the seniority they hired for the change ability. >> The culture change is both business culture and there's also tech culture that culture cloud, native agile data at the center of the value proposition. Now culturals is about expectations I I need it relevant. I mean it's a commitment problem to needed. I need it fast. solve too as well on both business skills gap and also technical. >> I mean to your  point, I mean kid in a candy store is like the the best way I can describe it. I think every single business process and in the nineties we had this big theme of business process reengineering. You know that I'd like it comes back on steroids right now because you can simply look at every single business process once again and see where the human element and the machine or a robotic element can simply provide superior outcomes. Think about use cases of detecting fraudulent spend more easily like machines are simply better at that. We have to admit that if we can liberate the human potential at large and tap into the ingenuity by liberating them from the mundane and shifted you towards value at, that's huge. So our commitment of infusing machine learning and ai constantly in every single business process and learning from your decision like John, if you have the same workflow and you approved it 99 times, the system should start taking a hint. It doesn't mean hard coding and rewiring the work flow. The system automatically should learn from your behavior. So this is what we talk about, intelligent process automation. It also extends into what we call intelligent process performance management where our entERPrise performance management cloud is very sophisticated and analytical capabilities, but now it's taking it to the next level of prediction, learning, anticipating, constantly and suggesting actionable results. So a lot of things and chatbots for expenses is the entire communication with the system. It's just branded in a way where I say, when is the last time you had an intelligent conversation with your ERP system? A lot of people would say never. >> Well, I think people would love to get more value out of the data. And certainly the work that ERP systems have done as foundational mechanisms or plumbing or infrastructure and software is critical. Data's in there, right? So, yes. But the interesting topic that's becoming apparent and Oracle, you've, you guys lived this and you know at, uh, your other career at sap client server had a great growth when heterogeneous network started to appear, correct? So heterogeneous is a word that's not just a customer problem, it's an oracle opportunity as well because you have to be heterogeneous in an mov yourself. >> Absolutely. >> Then that's the data is the bridge of your internal system. So it's not just here's your oracle, between all of that. So now you have heterogenaity around all go buy some European, deploy it in the customer's heterogeneous environment. You gotta have a heterogeneous integration than Oracle into a cloud environment for the customer, makes it more complex, but the data becomes the key asset. >> Data is the key asset. And this is why we took decisive steps about a decade ago to really rewrite from scratch for the cloud. So we're really not trying to get away with hosting or legacy into the cloud because I think it's a fundamentally flawed strategy, right? So we also learned from what I call typical SaaS, one point old patterns where certain vendors tackled one business problem in isolation, but then it's upon the customer once again to stitch it painfully together with all of the risk it has like security risks, um, data silos that you so desperately trying to run away from comeback on steroids in the age of multicloud. Right? So it's oftentimes what we're seeing is that tactical cloud adoption, our customer and prospect conversations give way to more strategic longevity type of SaaSs consideration. And this is where we think we have a great story to tell by having everything in the cloud. Every line of business re architected for the cloud, but then of course the entire stack So of course we want to make sure that everything that comes out of Oracle depth to support it. works best stitched together. But by all means, it's really that we acknowledged that customers have heterogeneous environments that were open to connect, extend any type of starting point a customer might have. >> So one of the things I've been impressed with Oracle and the previous announcements is your affinity towards some of the emerging tech you guys aren't afraid to, to run at a new environment. And Larry Ellis was classical old with Larry. We'll wait until he sees clear And because you got a big business, you've got zillions of customers, visibility that he'll run hard at it and it's been fun to watch. uh, and you're modernizing and real time. But the big change that's on the market is the blockchain. You guys got some announcements happening around here at Oracle Open? Correct. And you made an announcement earlier what new things are coming out with blockchain because blockchain actually is a database model. It's a little bit decentralized, but it has great use cases, low hanging use case, independent of all the hype and uncertainty around cryptocurrency. But certainly blockchain is an enabling. Technology will impact your world. What new things you announcing here? >> For me, that's likely the most fundamentally disruptive technology heading our way. To your point, still a little bit at the infancy compared to other emerging technologies, but the profoundness of change with this new trust fabric is just massive for every single business process as we know it. Um, so when we discussed with customers, it's really that we try to give our customers a headstart for immediate business impact, meaning we're shipping applications, productized use cases. So the announcements this week are really around intelligent track and trace, making sure that any given point in time, you know exactly where in the supply chain you're product is, what are the handover points all documented seamlessly. You see an announcement around what we call the intelligent cold chain, big topic for some pharmaceutical companies, for example, or food and beverage, right? To have refrigerated products where you need to prove that they never surpassed the temperature threshold. For example, in the supply chain document that via supplied via block chain, we have, um, what we call warranty and usage as a use case. Just simplifying the settlements, the claim processes for any type of things here. So we have multiple more that are in the labs right now. Take an hcm use case, for example, where everyone of us had some educational experience, right? And we want to make sure that the hiring process becomes as if, uh, did you go to the school, you said you went, you know, your supply chain, you know, your journey in life as a, as a value chain. I mean the first universities are actually posting the certificates, unblocked chain so that you have this immutable record and the entire vetting of credentials in the hiring process, which is so cost intensive time intensive could be shaved off seeming as >> One of the things I'm personally passionate about and then release our video businesses that one of the big problems that's going to becoming great fast as deep face tampering with video. One of the things that we're thinking about it, how to put our videos on the blockchain to look at whether it's been tampered or not. Absolutely. Because you know, you can take this video. Could you say something that because this big, this legit problem was verified. So again, this is a verification about it and people want to know, did the produce come from that? Certain lawyers production, certainly manufacturing operations is Qa issues. This is real. These are real world examples. This is not like some pie in the sky hyped up. Tulip craze >> Funny you mentioned that we actually have an innovation panel on Tuesday afternoon where we have, for example, one of the largest food manufacturers in the world building on our blockchain cloud services. Those types of use cases and just amazing what we're seeing in terms of the impact emerging technologies can have and quite frankly business impact we're going to see out of that. >> I think I personally think, and I'd love to get your reaction to this because it's something that we talk a lot on the cube allowed in is good feedback on is that you're going to have to explain yourself and have verification because there's a lot of black box processes that have to be an unexposed because people want to know the transparency of how things move through the system. Whether it's, whether it's fruit, whether it's videos, whether it's someone's resume or credentials, reputation. These are new ways that needs to be explained by algorithms. Yes, so now the black box is going to be opened up. This is an opportunity. It's a threat to a lot of people, so you're on. Do you agree with that idea that there'll be soon things will be explained and be able to be inspected eventually. >> Transparency is huge and as to your point, I don't think you can hide a lot of things going forward anymore, so everything becomes more transparent, but with enabling technology such as blockchain for example, they also become immutable into dispute to your ability to to, to, to, to alter the information flow becomes less so. It's both. I'm very enlightening in terms of having transparency, speeding up business processes and to your point also understanding the origin where something originated. We have a lot lineage, for example, as another blockchain applicant. Live lineage, you mean like production lots, production loads, for example in provenance, right? To really understand the genealogy example that understand the genealogy as to where, for example, certain parts of your supply chain really come from. Do they come from countries for example, where you shouldn't be doing business So it's all those types of things where you can always prove like maybe the with? Right. >> Chinese put a chip on a board and puts it in Amazon Apple Data Center. That's a supply chain concern. But I totally wouldn't you love to know where that motherboard is. I mean, this is, these are real world examples. If it went through to press the last couple of weeks, it definitely is. It's a real. Aws and apple have vehemently denied, strenuously objected to the claim. I refuted. I would, I checked it out, I think with the Bloomberg story wrong, but we know that there is hacking going But again, this is an example of, on, no doubt. as things are moving around a lot, whether their workloads are manufacturing, this is a data problem. >> It all comes down to data. I mean data is the ultimate weapon in this age where they were in right now, um, and the company that can help you best to have as much data meaning first party generated data, but then also complement that with, for example, Oracle data cloud, right? Really Privacy compliant. Third Party data points to have this contextual demographic, Geo geolocation type of context to really delight customer experience and compliment your own insight is massive and we'd like to think we have a great story to tell not only being to manage this data but also to Securitas data because data security is massive. I mean I have been a personal victim of the equifax hack, so since then I take it very much seriously. >> I mean not take credit card fraud on that. >> You had been to be honest, I mean like impact was less than I'd expected it, but it's still scary to see as to how fast your privacy can be compromised. Right? So you definitely want to make sure that be hacked and some advice we you want to be hacked. Just tell people you own a lot of big coin. You'll be hacking in a heartbeat. But this is the culture. Let's get back down to this core issue because Larry Ellison said a couple open oracle liberals will go, that security should be always on. Yes. And this is a fundamental concern. So you know, as you guys look at bringing this customer experience together, bringing the unity of the data together. Um, I mean there's a lot of oracle products out there. You got, you got ERP and hcm, you've got cx data, cloud, all these things are out there, right? So bottom line, that's SaaS cloud for Oracle. What is the, what's the mission, and simplify it for us. What if I'm a customer? I got a lot of Oracle, I have some oracle, maybe I want more or less or I don't And what's the value proposition for oracle cloud's SaaS solutions? know. Bottom line. >> In a nutshell, it's about future proofing the business of our customers. I'd like to think that cloud is in hyphened the inevitable destination for us to serve the customers and our prospect base at large to help them just be ahead of the curve in either driving innovation, taking advantage of data points to turn it into a competitive advantage and having this quick ability on a quarterly basis to surface as innovation, but don't leave the customer alone with standalone innovation platforms. Sidecar concepts by making sure we have a holistic architectural approach to surface in the context of the business when you need it and making sure. So for us it's really the fundamental way how we can better serve our customer base and our prospect base and we'd like to think that the decisiveness of the architecture we have chosen about a decade ago brings us a lot of advantages right now where customers are realizing tactical cloud adoption was trust. One, LOB is short lift potentially, so they're looking at holistic cloud suites and we have everything in the cloud plus we have the architectural depth to really surface and actually tackle any business problem right now, not as a promise and a couple of years and then also keeping a roadmap, making some extensibility. >> Alright. Personal question. You're again. What are you personally excited about right now? Obviously you've seen a lot of ways of innovation with sap. Now you're at Oracle, you've seen the client server wave, you're now on the cloud wave. What are you personally excited about this next modern infrastructure and software environment as it starts to evolve, that big wave is coming? What's most exciting for you? >> For me, it's really the possibility to re think about every single business process as we know it. It's so fundamental, those technologies, machine learning, constantly learning from your decision that the experience at large, how you interact with a system. We're so conditioned in consumer life that you ask a question, you get this instant gratification of a response. This is exactly the type of experience we're going to see an entERPrise systems as well. So I do think the demographics, the requirements into an ERP system, an entERPrise system at large have changed and we're excited about the ability to serve that up now on a quarterly basis with speed and also customer responds of course, right? Because SaaS for us as a fantastic opportunity to get instant feedback, we can do ab testing, we can immediately see as the, what's used, what's not used. Right? So for us as a vendor, I think we have to be on our toes because I mean there's no hiding in SaaS, right? I mean either you deliver or your don't. Yeah, it's incident. Um, so there's a lag time of shipping info, innovation, safeguarding our customers, and I think we have a great story to tell for customers who have invested with us already in the past with on premise investments, how we can shepherd them into the cloud era at the most predictable type of timeframe caused everything. You mentioned one word which was key unity, which is one of the announcement I forgot to tell customer experience, unity in the past. I think what we have seen on the customer experience side is oftentimes that vendors have taken an approach where you had sales service, marketing, commerce, oftentimes siloed cx. Unity is really our fundamental commitment to making sure that the data management of every single dynamic touchpoints we have with a customer is constantly live up to. But do your point. I think oracle has a fantastic set of cards to deal with customers to help them in any starting point of their journey right now. Not In the future, no re architecture needed. We can take that right out to them. >> I think Oracle is a great opportunity with the data play. I'll see databases, not a foreign concept, the word database, um, data processing, real time. I mean, I think the integration, you guys have a good opportunity and great to great to see you and thanks for spending a QP, appreciate anything, keep conversations. You're lending there. Who's the senior vice president? Oracle SaaS cloud here in the studio, Palo Alto. A lot going on around Oracle. OpenWorld happening. I'm John Furrier. Thanks for watching.

>> Welcome back everybody. Jeff Frick here with theCUBE. We're in Mountain View, CA at Knightscope, a really interesting company that's making autonomous vehicles. They're not cars, they're robots, and they're for security. And they're deployed and they're in use, I think it's 15 states or 14 states all over the country, just closed a huge round of funding. A lot of great momentum, and we're really excited to be rejoined by Cube alumni Mercedes Soria, she is the VP Software Engineer. Mercedes, great to see you again. >> Thank you for having me. >> Absolutely, well thanks. We had you at the studio last time so thanks for having us over here where all the action's happening. >> Yeah, you're welcome to come anytime. >> So for the people that missed the first interview, just give them a quick overview of what Knightscope's all about. >> We build autonomous security robots. Those are machines, they are running around autonomously, collecting video, collecting signals like thermal signals, the signal from your phone, and collecting a bunch of information that then is transformed into a webpage that a customer can see. So they get alerts to anything that is out of the ordinary. >> So, the application is often in a mall, or in a parking lot or some of these types of places where it's really an ongoing patrol that the robot does. >> Yeah typically what you want a robot to do is the monotonous work. So, at a mall, the security guard walks around all day long, and most of the time nothing happens. So when something happens, only then you want to be notified. Otherwise, it's just a guard that walks around. So that's the job that the autonomous robots do. >> And is there somebody monitoring all of the sensors and stuff all the time, or is it more of an alert system, or is it kind of all over the map? >> It depends on our client. For example, we always monitor all the robots. We get alert systems set up so if anything happens to a robot, we will be notified. But on top of that, some of our customers like to see their video 24 hours a day to see what's going on at their facilities. Some other clients only want the security presence, so they don't look at video. It really just depends on what the client wants. >> What's the big difference by having a Knightscope robot versus just security cameras that are just pointing and on all the time. >> If you have a steady camera, by default it just doesn't move, so you can't cover that much space. You're only going to see that one box that the security camera is covering. With an autonomous machine, you can take it wherever the crime is happening; you see something is wrong, you move the machine over and you take a closer look. So it does a lot more than just this one square that you can look at all the time, you can see everything around the machine, it's 360 degree video that is running 24-7. >> And how does it impact the way that the security people do their job? Let's stick with the mall example. When you've introduced a Knightscope robot, what's the right word, is robot the right word, is it robot? >> It's a robot, yes. >> When you've introduces a Knightscope robot into a mall situation, how does that change the way that people do their jobs? >> The robot will do about 70 or so percent of what a security guard does. But now the guard, instead of having to go and walk around the mall all day long, they get to do a more interesting job So now they're more interested in robots, they know technology, they get to know how to deal with a machine, how to interact with people. Those are things of a higher level. If the machine does all of the monotonous and boring work that the guard does. So at the end of the day, that guard does something that is a lot higher level than what they were doing before. >> Do customers typically have fewer guards, the guards just doing more higher-value, how does it impact their whole security system once they bring in a Knightscope robot? >> It could be one of two things. There are some places that our customers have zero, zero, zero patrolling, so they have nothing. So in that case, if the robot comes in, now you have security that you didn't have before. Some of our other clients, they decide that one of the robots is going to do the job of maybe three people, but those three people now are doing administrator work. So their work is to become of a higher level, so it depends on the client a lot. >> We've got a bunch of the robots behind us here in the shop, I'm sure we'll have them in the intro packet, the different ones. You've got four different ones. First off let's do some of the basics: What are some of the sensors, what are some of the inputs that they are collecting, and why do you have four different ones? >> A lot of why we have four ones is because we wanted to give the customer security regardless of their environment. The first one is the K3, that's an indoor machine; it's a smaller size, it weighs about 340 pounds. >> Small one and you say it weighs 340 pounds? >> Yes, that's the small one. >> No little kids are running up and tipping that one over I don't think. >> No, they're not. People have tried, but not yet. That is for indoors. It has all of the sensors that our other machines have, they all have a thermal detection. They have their regular cameras. They have inertia measuring units. They have lighters, which is what allows you to tell that there is something in your way, that you have to get out of the way. We have ASD, which is Automated Signal Detections. Your phone emits a signal when it's trying to connect to Wifi. We can detect all of those phone signals, and then we can log that into the server. All of the machines have that, it's just how they are using in a different environment. Indoor for the K3, outdoor for the K5, we have the K1, which is a static unit. That's typically going to be put in the door of the places we're going to monitor. And then we have the K7, which is the largest unit that we have so far, and it's going to places that a machine that's smaller cannot typically transverse. >> So that's the one that looks like a little Jeep back here. >> Yeah, in a wind farm, in a solar farm, these machines don't do very well, and that's when these machines go in. >> So definitely for outside >> Outside-- >> On the road, in the dirt >> Large companies-- >> It doesn't have to be in a parking lot, in a paved environment. >> Gravel, any different type of environment. >> What is the experience, why do these things work? Is it just because you have more coverage because you've got a robot that's going places you don't have enough guards? Is it the intimidation that someone is watching me now, you're bringing a camera into the parking lot where maybe it was kind of hidden behind a little wall? Is there a two-way interaction, do people talk to these things and expect them to talk back? Where do you see the most effective, why are these things effective? >> The reason why they're more effective can be summarized in one point: Security guards don't like to do their job. There is a 300% turnover rate in the security industry, people don't normally know that. So you're getting a new team every four months. People don't like their job, it's a job that is very monotonous, very boring. We're putting a robot there to do the same job, so you can free people to do something of a higher level. And that's the main reason why they work. >> I wonder if you can speak a little to where you're using machine learning and some of the deeper technology beyond simply putting a camera on a mobile platform. >> Some of our customers, for example, at night at the malls or corporate campuses, there isn't supposed to be anyone there at night. So one of the big applications that we have is we have an image, and from that image we can train our algorithms to detect people in that image, to detect faces in that image. All of that is done by machine learning. Because we have five years of data of images and people and we train our algorithms to say, this is a pole, or this is a person, this is a tree, this is a person. So we get to detect people in a really high accuracy level, about 80%. We also do the same thing with license plates. We train our algorithms to detect that there's a license plate in an image, you detect that there's a car first, then you detect that there's a license plate, and from there you detect all of the character in that license plate. And all of that uses machine learning, even to differentiate that there is a number one opposed to a letter L. All of that had to be trained as the technologies that we're using. For the future, we're going to use prediction algorithms in the way that, now we have data of what happens around the location where the machine is deployed to. We're going to be able to say, "Okay, this area has a lot of crime that happens "on a daily basis or however often, "you probably should go patrol over in that area." That is what we will do in the future. >> The other interesting thing is you don't sell these, these are not for sale as like, going to buy a car, you actually provide it as a service. So a very different business model, very much in line with what we see more and more, it's a service, people basically rent the robot with the monitoring service? Is that accurate, or are there lots of different flavors that they can buy? >> What we do is called machine as a service. To eliminate our customers having to pay a big amount of money at the beginning, they don't cover that cost, we do. But they pay us a monthly bill. Included in that monthly bill is the machine itself, all the parts, the monitor in there with the one on our end, all of the software upgrades, which we do every two weeks, and all of the hardware upgrades, which we do every six months to every year. All of that is included in that package. How the customers chooses to monitor their machines, that is up to them. We have agreements with two of the largest security guard companies: Securitas and Allied Universal, so they can do the monitoring for the customer if they don't have a security operation center. >> Clearly, you're operating in places where they already have security in place, they have systems, so do you integrate with the existing alert systems and the existing infrastructure they already have in place, do you guys just tie into that? I would imagine there's some industry APIs that you can feed into those systems or is it a completely independent monitoring that they have to do now? >> We did a little bit of the reverse of that, we built our system for it to be integrable. The way we wrote our code, a customer system developer can call our APIs and get the information from the machine that way, so all of that is finished so they can integrate with us opposed to us integrating the other, there's hundreds of systems out there. So if somebody wants to look at data from Knightscope that's already there. >> But you've got the open API into your data feed so they can feed whatever system. >> It of course is secure, you have to have keys and passwords and codes, and all of the information is encrypted So there's measurements that we've taken to make sure that the information is secure at all times. >> So you're a hardware company, you're a software company, you're a services company, you're doing AI. >> Woman: We're doing design too. >> And design, and autonomous vehicles. >> Yes. >> What did I miss? >> Production! We build. >> Production too? >> We build. Yes. >> That's right, I noticed this says on the bottom, reminds me of an Apple product-- >> It is designed and built in California. 85% of what you see in this machine is United States. >> Pretty amazing. So what's next? What's the next big challenge? I know the Seven is not released yet, is it just more form factors, is it different sensors? As you kind look forward from an engineering challenge, what is some of the next big hills that you guys want to take to move this thing along? >> The three next big hills that we have: Number one is getting the K7 out there and patrolling. Number two is concealed weapon detection, that has been requested by a lot of our customers. >> Concealed weapons detection? >> A lot of our customers are requesting that. And third, on the software side of things, the actual prediction of crime that could potentially happen. Those are the next three big goals for Knightscope. >> I would imagine that with the concealed weapons it's just more types of sensors that can see X-rays or whatever to get more visibility. >> Yes. >> The big V. Not necessarily visible light, but visibility from the machine. >> Some of those things have already been requested by our customers, because what we've build is actually a platform. We can add other sensors to the machine depending on the needs of a customer. For example, we have a customer who wanted the machine to be able to identify people, so they wouldn't have to swipe a card. Put the sensor inside, it's accessible, it's already there, you get your sensor and your information. What's the biggest surprise that you hear from customers after they've had one of these deployed for, I don't know what's a reasonable time, six months, so they're kind of used to it in their workflow, how does it really their world, what do they tell you? >> There are two things, number one is how quickly people like the machine, how quickly they go, "Oh, yeah, it's here and it's working." And then also how much crime has actually been eliminated. They thought, "Okay, maybe I have one break-in into "a car every week, well maybe it will just go to less." It goes down to zero. There's people who had lots of crime, and just by the machine being there, they get nothing, they get zero. So that was our surprise for them, and that was a surprise for us as well. That's how the effective the machine actually is. >> It's weird when I just drove up today, there was one right in the middle of the driveway as I was coming in. I was like, "Is it going to move, am I going to move?" It's very, much more intimidating than you might think. It's a presence, for sure. >> Yeah, and we have things like car backup detection, because the machine could be going down the street, and a car could be coming out of there, so we have to detect stuff like that so we don't get run over. All of those little things that we can think of, we have to do that a lot. >> Alright Mercedes, well thanks for inviting us over, it's fun to actually see the machines for real. >> Thank you so much for coming. >> She's Mercedes, I'm Jeff Frick, you're watching theCUBE, we're at Knightscope in Mountain View, California. (upbeat music)