(gentle music) >> Hello everyone. Welcome to this CUBE conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We got a great remote guest coming in. Joseph Nelson, co-founder and CEO of RoboFlow hot startup in AI, computer vision. Really interesting topic in this wave of AI next gen hitting. Joseph, thanks for coming on this CUBE conversation. >> Thanks for having me. >> Yeah, I love the startup tsunami that's happening here in this wave. RoboFlow, you're in the middle of it. Exciting opportunities, you guys are in the cutting edge. I think computer vision's been talked about more as just as much as the large language models and these foundational models are merging. You're in the middle of it. What's it like right now as a startup and growing in this new wave hitting? >> It's kind of funny, it's, you know, I kind of describe it like sometimes you're in a garden of gnomes. It's like we feel like we've got this giant headstart with hundreds of thousands of people building with computer vision, training their own models, but that's a fraction of what it's going to be in six months, 12 months, 24 months. So, as you described it, a wave is a good way to think about it. And the wave is still building before it gets to its full size. So it's a ton of fun. >> Yeah, I think it's one of the most exciting areas in computer science. I wish I was in my twenties again, because I would be all over this. It's the intersection, there's so many disciplines, right? It's not just tech computer science, it's computer science, it's systems, it's software, it's data. There's so much aperture of things going on around your world. So, I mean, you got to be batting all the students away kind of trying to get hired in there, probably. I can only imagine you're hiring regiment. I'll ask that later, but first talk about what the company is that you're doing. How it's positioned, what's the market you're going after, and what's the origination story? How did you guys get here? How did you just say, hey, want to do this? What was the origination story? What do you do and how did you start the company? >> Yeah, yeah. I'll give you the what we do today and then I'll shift into the origin. RoboFlow builds tools for making the world programmable. Like anything that you see should be read write access if you think about it with a programmer's mind or legible. And computer vision is a technology that enables software to be added to these real world objects that we see. And so any sort of interface, any sort of object, any sort of scene, we can interact with it, we can make it more efficient, we can make it more entertaining by adding the ability for the tools that we use and the software that we write to understand those objects. And at RoboFlow, we've empowered a little over a hundred thousand developers, including those in half the Fortune 100 so far in that mission. Whether that's Walmart understanding the retail in their stores, Cardinal Health understanding the ways that they're helping their patients, or even electric vehicle manufacturers ensuring that they're making the right stuff at the right time. As you mentioned, it's early. Like I think maybe computer vision has touched one, maybe 2% of the whole economy and it'll be like everything in a very short period of time. And so we're focused on enabling that transformation. I think it's it, as far as I think about it, I've been fortunate to start companies before, start, sell these sorts of things. This is the last company I ever wanted to start and I think it will be, should we do it right, the world's largest in riding the wave of bringing together the disparate pieces of that technology. >> What was the motivating point of the formation? Was it, you know, you guys were hanging around? Was there some catalyst? What was the moment where it all kind of came together for you? >> You know what's funny is my co-founder, Brad and I, we were making computer vision apps for making board games more fun to play. So in 2017, Apple released AR kit, augmented reality kit for building augmented reality applications. And Brad and I are both sort of like hacker persona types. We feel like we don't really understand the technology until we build something with it and so we decided that we should make an app that if you point your phone at a Sudoku puzzle, it understands the state of the board and then it kind of magically fills in that experience with all the digits in real time, which totally ruins the game of Sudoku to be clear. But it also just creates this like aha moment of like, oh wow, like the ability for our pocket devices to understand and see the world as good or better than we can is possible. And so, you know, we actually did that as I mentioned in 2017, and the app went viral. It was, you know, top of some subreddits, top of Injure, Reddit, the hacker community as well as Product Hunt really liked it. So it actually won Product Hunt AR app of the year, which was the same year that the Tesla model three won the product of the year. So we joked that we share an award with Elon our shared (indistinct) But frankly, so that was 2017. RoboFlow wasn't incorporated as a business until 2019. And so, you know, when we made Magic Sudoku, I was running a different company at the time, Brad was running a different company at the time, and we kind of just put it out there and were excited by how many people liked it. And we assumed that other curious developers would see this inevitable future of, oh wow, you know. This is much more than just a pedestrian point your phone at a board game. This is everything can be seen and understood and rewritten in a different way. Things like, you know, maybe your fridge. Knowing what ingredients you have and suggesting recipes or auto ordering for you, or we were talking about some retail use cases of automated checkout. Like anything can be seen and observed and we presume that that would kick off a Cambrian explosion of applications. It didn't. So you fast forward to 2019, we said, well we might as well be the guys to start to tackle this sort of problem. And because of our success with board games before, we returned to making more board game solving applications. So we made one that solves Boggle, you know, the four by four word game, we made one that solves chess, you point your phone at a chess board and it understands the state of the board and then can make move recommendations. And each additional board game that we added, we realized that the tooling was really immature. The process of collecting images, knowing which images are actually going to be useful for improving model performance, training those models, deploying those models. And if we really wanted to make the world programmable, developers waiting for us to make an app for their thing of interest is a lot less efficient, less impactful than taking our tool chain and releasing that externally. And so, that's what RoboFlow became. RoboFlow became the internal tools that we used to make these game changing applications readily available. And as you know, when you give developers new tools, they create new billion dollar industries, let alone all sorts of fun hobbyist projects along the way. >> I love that story. Curious, inventive, little radical. Let's break the rules, see how we can push the envelope on the board games. That's how companies get started. It's a great story. I got to ask you, okay, what happens next? Now, okay, you realize this new tooling, but this is like how companies get built. Like they solve their own problem that they had 'cause they realized there's one, but then there has to be a market for it. So you actually guys knew that this was coming around the corner. So okay, you got your hacker mentality, you did that thing, you got the award and now you're like, okay, wow. Were you guys conscious of the wave coming? Was it one of those things where you said, look, if we do this, we solve our own problem, this will be big for everybody. Did you have that moment? Was that in 2019 or was that more of like, it kind of was obvious to you guys? >> Absolutely. I mean Brad puts this pretty effectively where he describes how we lived through the initial internet revolution, but we were kind of too young to really recognize and comprehend what was happening at the time. And then mobile happened and we were working on different companies that were not in the mobile space. And computer vision feels like the wave that we've caught. Like, this is a technology and capability that rewrites how we interact with the world, how everyone will interact with the world. And so we feel we've been kind of lucky this time, right place, right time of every enterprise will have the ability to improve their operations with computer vision. And so we've been very cognizant of the fact that computer vision is one of those groundbreaking technologies that every company will have as a part of their products and services and offerings, and we can provide the tooling to accelerate that future. >> Yeah, and the developer angle, by the way, I love that because I think, you know, as we've been saying in theCUBE all the time, developer's the new defacto standard bodies because what they adopt is pure, you know, meritocracy. And they pick the best. If it's sell service and it's good and it's got open source community around it, its all in. And they'll vote. They'll vote with their code and that is clear. Now I got to ask you, as you look at the market, we were just having this conversation on theCUBE in Barcelona at recent Mobile World Congress, now called MWC, around 5G versus wifi. And the debate was specifically computer vision, like facial recognition. We were talking about how the Cleveland Browns were using facial recognition for people coming into the stadium they were using it for ships in international ports. So the question was 5G versus wifi. My question is what infrastructure or what are the areas that need to be in place to make computer vision work? If you have developers building apps, apps got to run on stuff. So how do you sort that out in your mind? What's your reaction to that? >> A lot of the times when we see applications that need to run in real time and on video, they'll actually run at the edge without internet. And so a lot of our users will actually take their models and run it in a fully offline environment. Now to act on that information, you'll often need to have internet signal at some point 'cause you'll need to know how many people were in the stadium or what shipping crates are in my port at this point in time. You'll need to relay that information somewhere else, which will require connectivity. But actually using the model and creating the insights at the edge does not require internet. I mean we have users that deploy models on underwater submarines just as much as in outer space actually. And those are not very friendly environments to internet, let alone 5g. And so what you do is you use an edge device, like an Nvidia Jetson is common, mobile devices are common. Intel has some strong edge devices, the Movidius family of chips for example. And you use that compute that runs completely offline in real time to process those signals. Now again, what you do with those signals may require connectivity and that becomes a question of the problem you're solving of how soon you need to relay that information to another place. >> So, that's an architectural issue on the infrastructure. If you're a tactical edge war fighter for instance, you might want to have highly available and maybe high availability. I mean, these are words that mean something. You got storage, but it's not at the edge in real time. But you can trickle it back and pull it down. That's management. So that's more of a business by business decision or environment, right? >> That's right, that's right. Yeah. So I mean we can talk through some specifics. So for example, the RoboFlow actually powers the broadcaster that does the tennis ball tracking at Wimbledon. That runs completely at the edge in real time in, you know, technically to track the tennis ball and point the camera, you actually don't need internet. Now they do have internet of course to do the broadcasting and relay the signal and feeds and these sorts of things. And so that's a case where you have both edge deployment of running the model and high availability act on that model. We have other instances where customers will run their models on drones and the drone will go and do a flight and it'll say, you know, this many residential homes are in this given area, or this many cargo containers are in this given shipping yard. Or maybe we saw these environmental considerations of soil erosion along this riverbank. The model in that case can run on the drone during flight without internet, but then you only need internet once the drone lands and you're going to act on that information because for example, if you're doing like a study of soil erosion, you don't need to be real time. You just need to be able to process and make use of that information once the drone finishes its flight. >> Well I can imagine a zillion use cases. I heard of a use case interview at a company that does computer vision to help people see if anyone's jumping the fence on their company. Like, they know what a body looks like climbing a fence and they can spot it. Pretty easy use case compared to probably some of the other things, but this is the horizontal use cases, its so many use cases. So how do you guys talk to the marketplace when you say, hey, we have generative AI for commuter vision. You might know language models that's completely different animal because vision's like the world, right? So you got a lot more to do. What's the difference? How do you explain that to customers? What can I build and what's their reaction? >> Because we're such a developer centric company, developers are usually creative and show you the ways that they want to take advantage of new technologies. I mean, we've had people use things for identifying conveyor belt debris, doing gas leak detection, measuring the size of fish, airplane maintenance. We even had someone that like a hobby use case where they did like a specific sushi identifier. I dunno if you know this, but there's a specific type of whitefish that if you grew up in the western hemisphere and you eat it in the eastern hemisphere, you get very sick. And so there was someone that made an app that tells you if you happen to have that fish in the sushi that you're eating. But security camera analysis, transportation flows, plant disease detection, really, you know, smarter cities. We have people that are doing curb management identifying, and a lot of these use cases, the fantastic thing about building tools for developers is they're a creative bunch and they have these ideas that if you and I sat down for 15 minutes and said, let's guess every way computer vision can be used, we would need weeks to list all the example use cases. >> We'd miss everything. >> And we'd miss. And so having the community show us the ways that they're using computer vision is impactful. Now that said, there are of course commercial industries that have discovered the value and been able to be out of the gate. And that's where we have the Fortune 100 customers, like we do. Like the retail customers in the Walmart sector, healthcare providers like Medtronic, or vehicle manufacturers like Rivian who all have very difficult either supply chain, quality assurance, in stock, out of stock, anti-theft protection considerations that require successfully making sense of the real world. >> Let me ask you a question. This is maybe a little bit in the weeds, but it's more developer focused. What are some of the developer profiles that you're seeing right now in terms of low-hanging fruit applications? And can you talk about the academic impact? Because I imagine if I was in school right now, I'd be all over it. Are you seeing Master's thesis' being worked on with some of your stuff? Is the uptake in both areas of younger pre-graduates? And then inside the workforce, What are some of the devs like? Can you share just either what their makeup is, what they work on, give a little insight into the devs you're working with. >> Leading developers that want to be on state-of-the-art technology build with RoboFlow because they know they can use the best in class open source. They know that they can get the most out of their data. They know that they can deploy extremely quickly. That's true among students as you mentioned, just as much as as industries. So we welcome students and I mean, we have research grants that will regularly support for people to publish. I mean we actually have a channel inside our internal slack where every day, more student publications that cite building with RoboFlow pop up. And so, that helps inspire some of the use cases. Now what's interesting is that the use case is relatively, you know, useful or applicable for the business or the student. In other words, if a student does a thesis on how to do, we'll say like shingle damage detection from satellite imagery and they're just doing that as a master's thesis, in fact most insurance businesses would be interested in that sort of application. So, that's kind of how we see uptick and adoption both among researchers who want to be on the cutting edge and publish, both with RoboFlow and making use of open source tools in tandem with the tool that we provide, just as much as industry. And you know, I'm a big believer in the philosophy that kind of like what the hackers are doing nights and weekends, the Fortune 500 are doing in a pretty short order period of time and we're experiencing that transition. Computer vision used to be, you know, kind of like a PhD, multi-year investment endeavor. And now with some of the tooling that we're working on in open source technologies and the compute that's available, these science fiction ideas are possible in an afternoon. And so you have this idea of maybe doing asset management or the aerial observation of your shingles or things like this. You have a few hundred images and you can de-risk whether that's possible for your business today. So there's pretty broad-based adoption among both researchers that want to be on the state of the art, as much as companies that want to reduce the time to value. >> You know, Joseph, you guys and your partner have got a great front row seat, ground floor, presented creation wave here. I'm seeing a pattern emerging from all my conversations on theCUBE with founders that are successful, like yourselves, that there's two kind of real things going on. You got the enterprises grabbing the products and retrofitting into their legacy and rebuilding their business. And then you have startups coming out of the woodwork. Young, seeing greenfield or pick a specific niche or focus and making that the signature lever to move the market. >> That's right. >> So can you share your thoughts on the startup scene, other founders out there and talk about that? And then I have a couple questions for like the enterprises, the old school, the existing legacy. Little slower, but the startups are moving fast. What are some of the things you're seeing as startups are emerging in this field? >> I think you make a great point that independent of RoboFlow, very successful, especially developer focused businesses, kind of have three customer types. You have the startups and maybe like series A, series B startups that you're building a product as fast as you can to keep up with them, and they're really moving just as fast as as you are and pulling the product out at you for things that they need. The second segment that you have might be, call it SMB but not enterprise, who are able to purchase and aren't, you know, as fast of moving, but are stable and getting value and able to get to production. And then the third type is enterprise, and that's where you have typically larger contract value sizes, slower moving in terms of adoption and feedback for your product. And I think what you see is that successful companies balance having those three customer personas because you have the small startups, small fast moving upstarts that are discerning buyers who know the market and elect to build on tooling that is best in class. And so you basically kind of pass the smell test of companies who are quite discerning in their purchases, plus are moving so quick they're pulling their product out of you. Concurrently, you have a product that's enterprise ready to service the scalability, availability, and trust of enterprise buyers. And that's ultimately where a lot of companies will see tremendous commercial success. I mean I remember seeing the Twilio IPO, Uber being like a full 20% of their revenue, right? And so there's this very common pattern where you have the ability to find some of those upstarts that you make bets on, like the next Ubers of the world, the smaller companies that continue to get developed with the product and then the enterprise whom allows you to really fund the commercial success of the business, and validate the size of the opportunity in market that's being creative. >> It's interesting, there's so many things happening there. It's like, in a way it's a new category, but it's not a new category. It becomes a new category because of the capabilities, right? So, it's really interesting, 'cause that's what you're talking about is a category, creating. >> I think developer tools. So people often talk about B to B and B to C businesses. I think developer tools are in some ways a third way. I mean ultimately they're B to B, you're selling to other businesses and that's where your revenue's coming from. However, you look kind of like a B to C company in the ways that you measure product adoption and kind of go to market. In other words, you know, we're often tracking the leading indicators of commercial success in the form of usage, adoption, retention. Really consumer app, traditionally based metrics of how to know you're building the right stuff, and that's what product led growth companies do. And then you ultimately have commercial traction in a B to B way. And I think that that actually kind of looks like a third thing, right? Like you can do these sort of funny zany marketing examples that you might see historically from consumer businesses, but yet you ultimately make your money from the enterprise who has these de-risked high value problems you can solve for them. And I selfishly think that that's the best of both worlds because I don't have to be like Evan Spiegel, guessing the next consumer trend or maybe creating the next consumer trend and catching lightning in a bottle over and over again on the consumer side. But I still get to have fun in our marketing and make sort of fun, like we're launching the world's largest game of rock paper scissors being played with computer vision, right? Like that's sort of like a fun thing you can do, but then you can concurrently have the commercial validation and customers telling you the things that they need to be built for them next to solve commercial pain points for them. So I really do think that you're right by calling this a new category and it really is the best of both worlds. >> It's a great call out, it's a great call out. In fact, I always juggle with the VC. I'm like, it's so easy. Your job is so easy to pick the winners. What are you talking about its so easy? I go, just watch what the developers jump on. And it's not about who started, it could be someone in the dorm room to the boardroom person. You don't know because that B to C, the C, it's B to D you know? You know it's developer 'cause that's a human right? That's a consumer of the tool which influences the business that never was there before. So I think this direct business model evolution, whether it's media going direct or going direct to the developers rather than going to a gatekeeper, this is the reality. >> That's right. >> Well I got to ask you while we got some time left to describe, I want to get into this topic of multi-modality, okay? And can you describe what that means in computer vision? And what's the state of the growth of that portion of this piece? >> Multi modality refers to using multiple traditionally siloed problem types, meaning text, image, video, audio. So you could treat an audio problem as only processing audio signal. That is not multimodal, but you could use the audio signal at the same time as a video feed. Now you're talking about multi modality. In computer vision, multi modality is predominantly happening with images and text. And one of the biggest releases in this space is actually two years old now, was clip, contrastive language image pre-training, which took 400 million image text pairs and basically instead of previously when you do classification, you basically map every single image to a single class, right? Like here's a bunch of images of chairs, here's a bunch of images of dogs. What clip did is used, you can think about it like, the class for an image being the Instagram caption for the image. So it's not one single thing. And by training on understanding the corpora, you basically see which words, which concepts are associated with which pixels. And this opens up the aperture for the types of problems and generalizability of models. So what does this mean? This means that you can get to value more quickly from an existing trained model, or at least validate that what you want to tackle with a computer vision, you can get there more quickly. It also opens up the, I mean. Clip has been the bedrock of some of the generative image techniques that have come to bear, just as much as some of the LLMs. And increasingly we're going to see more and more of multi modality being a theme simply because at its core, you're including more context into what you're trying to understand about the world. I mean, in its most basic sense, you could ask yourself, if I have an image, can I know more about that image with just the pixels? Or if I have the image and the sound of when that image was captured or it had someone describe what they see in that image when the image was captured, which one's going to be able to get you more signal? And so multi modality helps expand the ability for us to understand signal processing. >> Awesome. And can you just real quick, define clip for the folks that don't know what that means? >> Yeah. Clip is a model architecture, it's an acronym for contrastive language image pre-training and like, you know, model architectures that have come before it captures the almost like, models are kind of like brands. So I guess it's a brand of a model where you've done these 400 million image text pairs to match up which visual concepts are associated with which text concepts. And there have been new releases of clip, just at bigger sizes of bigger encoding's, of longer strings of texture, or larger image windows. But it's been a really exciting advancement that OpenAI released in January, 2021. >> All right, well great stuff. We got a couple minutes left. Just I want to get into more of a company-specific question around culture. All startups have, you know, some sort of cultural vibe. You know, Intel has Moore's law doubles every whatever, six months. What's your culture like at RoboFlow? I mean, if you had to describe that culture, obviously love the hacking story, you and your partner with the games going number one on Product Hunt next to Elon and Tesla and then hey, we should start a company two years later. That's kind of like a curious, inventing, building, hard charging, but laid back. That's my take. How would you describe the culture? >> I think that you're right. The culture that we have is one of shipping, making things. So every week each team shares what they did for our customers on a weekly basis. And we have such a strong emphasis on being better week over week that those sorts of things compound. So one big emphasis in our culture is getting things done, shipping, doing things for our customers. The second is we're an incredibly transparent place to work. For example, how we think about giving decisions, where we're progressing against our goals, what problems are biggest and most important for the company is all open information for those that are inside the company to know and progress against. The third thing that I'd use to describe our culture is one that thrives with autonomy. So RoboFlow has a number of individuals who have founded companies before, some of which have sold their businesses for a hundred million plus upon exit. And the way that we've been able to attract talent like that is because the problems that we're tackling are so immense, yet individuals are able to charge at it with the way that they think is best. And this is what pairs well with transparency. If you have a strong sense of what the company's goals are, how we're progressing against it, and you have this ownership mentality of what can I do to change or drive progress against that given outcome, then you create a really healthy pairing of, okay cool, here's where the company's progressing. Here's where things are going really well, here's the places that we most need to improve and work on. And if you're inside that company as someone who has a preponderance to be a self-starter and even a history of building entire functions or companies yourself, then you're going to be a place where you can really thrive. You have the inputs of the things where we need to work on to progress the company's goals. And you have the background of someone that is just necessarily a fast moving and ambitious type of individual. So I think the best way to describe it is a transparent place with autonomy and an emphasis on getting things done. >> Getting shit done as they say. Getting stuff done. Great stuff. Hey, final question. Put a plug out there for the company. What are you going to hire? What's your pipeline look like for people? What jobs are open? I'm sure you got hiring all around. Give a quick plug for the company what you're looking for. >> I appreciate you asking. Basically you're either building the product or helping customers be successful with the product. So in the building product category, we have platform engineering roles, machine learning engineering roles, and we're solving some of the hardest and most impactful problems of bringing such a groundbreaking technology to the masses. And so it's a great place to be where you can kind of be your own user as an engineer. And then if you're enabling people to be successful with the products, I mean you're working in a place where there's already such a strong community around it and you can help shape, foster, cultivate, activate, and drive commercial success in that community. So those are roles that tend themselves to being those that build the product for developer advocacy, those that are account executives that are enabling our customers to realize commercial success, and even hybrid roles like we call it field engineering, where you are a technical resource to drive success within customer accounts. And so all this is listed on roboflow.com/careers. And one thing that I actually kind of want to mention John that's kind of novel about the thing that's working at RoboFlow. So there's been a lot of discussion around remote companies and there's been a lot of discussion around in-person companies and do you need to be in the office? And one thing that we've kind of recognized is you can actually chart a third way. You can create a third way which we call satellite, which basically means people can work from where they most like to work and there's clusters of people, regular onsite's. And at RoboFlow everyone gets, for example, $2,500 a year that they can use to spend on visiting coworkers. And so what's sort of organically happened is team numbers have started to pull together these resources and rent out like, lavish Airbnbs for like a week and then everyone kind of like descends in and works together for a week and makes and creates things. And we call this lighthouses because you know, a lighthouse kind of brings ships into harbor and we have an emphasis on shipping. >> Yeah, quality people that are creative and doers and builders. You give 'em some cash and let the self-governing begin, you know? And like, creativity goes through the roof. It's a great story. I think that sums up the culture right there, Joseph. Thanks for sharing that and thanks for this great conversation. I really appreciate it and it's very inspiring. Thanks for coming on. >> Yeah, thanks for having me, John. >> Joseph Nelson, co-founder and CEO of RoboFlow. Hot company, great culture in the right place in a hot area, computer vision. This is going to explode in value. The edge is exploding. More use cases, more development, and developers are driving the change. Check out RoboFlow. This is theCUBE. I'm John Furrier, your host. Thanks for watching. (gentle music)

>> Narrator: Live from Las Vegas It's theCUBE covering Edge 2016. Brought to you by IBM. Now, here are your hosts Dave Vellante and Stu Miniman. >> Welcome back to Las Vegas, everybody. This is theCUBE the world-wide leader in live tech coverage. Leanne Kemp is here. She's the founder and CEO of Everledger. Leanne, good to see you. >> Hello, hello. What a great place to be. >> Good joke, Las Vegas again. Stu and I spend a lot of time here. Why did you start Everledger? >> Well, you know, some might say it's my mid-life crisis but the reality is I've been in emerging technology for 25 years. In the mid 90s, now I'm giving away my age I was in radio frequency identification so at the chip and inlay level supply chain tracking. A bit boring, really. >> Stu: No, RFID is cool. >> But in the last 10 years I've worked in jewelry and insurance. And that's given me an appreciation of the size of the problems that exist in the market. And couple that with a whole lot of nerd we have the ability to solve the problems that we're solving today. >> And describe that problem. It's a problem of provenance and transparency is that right? >> Provenance, fraud, document tampering. And when you mix all of those together you have a pretty potent formula for black market trade. And sadly, some of that trade is really running into terrorist-funded activities. So, it's a pretty big problem but I think now is a very real issue that's washing the front pages of every paper on a daily event. Diamonds, of course, is one of the vehicles for anti-money laundering. And if we can go and serve to reduce some of those problems then it's worthwhile getting out of bed for. >> Okay, so you're attacking the diamond value chain. Why that? 'Cuz you have a background in jewelry? Okay, how are you solving that problem though? Describe that in a little bit more detail. >> So, attacking's pretty aggressive. I think we're enhancing. So, we're bringing transparency in a once-opaque market. You know, we're enabling, with the use of technology to bring transparency into the market so that we can start to reduce some of the problems around fraud. When you really think about I mean most people look at us as a blockchain company. I liken us to an emerging technology company. We're using the very best of blockchain and smart contracts and machine vision as an enabler to be able to identify fraudulent-related activities and reduce them in marketplaces. And we're just starting with diamonds but it's really anything that is appreciable of value that criminals like to maybe get their grubby mitts on. >> When did you get this idea, like what timeframe? 2010, 2011, 2015? >> To be honest with you I think this has been a cocktail of experience that really has brought it together at the right time. So, you know, as I said my background has been really unfolding like a patchwork quilt. But when you really see the heightened anxiety that's going on in market now particularly around synthetic diamonds that are of gem-quality standards there's no greater time to be able to bring confidence back into the diamond industry and the consumer networks. >> I guess my question is that at what point did you say okay blockchain can be addressed to enhance this problem? Did you look at Bitcoin and say hmm, that's interesting? Not a currency, it's a technology that I can apply to all the problems. >> Yeah, I mean, you know, I'm a technologist so I really am quite bored with Sudoku so I would rather sort of look at what's going on in the tech space. And so when I really saw the emergency of Bitcoin I understood where that application could lie. But because I wasn't from a banking background it was patently obvious to me that I could decouple the currency from the ledger and really use the currency as a vehicle or a tokenization of assets. And the assets is diamonds, a girl's best friend. So why wouldn't you want to protect your assets? (chuckles) >> Fascinating 'cuz I think the first time I heard of, you know, blockchain and Bitcoin it was about being anonymous and therefore there were concerns that some of those unscrupulous people that are trying to benefit off of like diamonds would use, you know, this crypto currency. They don't have to talk to banks. They don't have to talk to governments. So you've almost flipped the usage of the technology to something to help the world a little bit more. >> That's right. I guess when you really think about it, you know the Bitcoin has often been assimilated with the anarchic world. And we're really bringing it to clean and transparency. So, I guess there is a juxtaposition there. But everything's upside down for me. I'm from Australia so it's perfectly normal. >> Go ahead, Stu. >> Yeah, just when you look at Blockchain and kind of the core technology you think we're really in the early days? What kind of usage do you see out beyond the ledgers? Are there other applications be it beyond the diamonds that you guys are looking at? >> Yeah, you know, so it's interesting. In the early 2000s I worked in WAP, you know? And I was so excited. I thought wow, this tech is really going to do something. So, you know, I'm part of Team Asserti in Australia and wrote out an application. And I felt like nearly six months came into the tech. And all of a sudden, I woke up and I went where the bloody hell did WAP go? It just disappeared. There was a very real danger that this technology was likely to face the same ill fate. And we often see in any emerging technology where there are heightened promises. They often end in disappointment. So, actually most of the decisions I've made in a start-up, and we're only 18 months old have really been counterintuitive. You know, when it's the time to put the pedal straight down I've often held back to really wait to see where the maturity of the technology was going to lie. And in any emerging technology and if you're a CEO of a start-up you have to be completely articulate about where the problem is that you're solving. But not only that you need to take the time to really distill the technology to its purest essence and then enable that to be the potent shot that goes out first and foremost. And so this is a nascent technology. And maybe, you know, it has the parentage of a multilingual PhD scientist but the reality is it's only just been born. We're not even nappy feddy. We're not even out of out of our nappies right now. So we need to give it the time to really grow. And we've chosen a niche market. It just so happens that it's a bloody big niche. >> So what took longer to figure out the problem or the solution? >> You know, I think you know, I don't know. That's a really good question, actually. I think the problem for me I understood quite early but I just didn't appreciate the size of the problem globally and the extension of that problem into other areas. And really I think it's taken some time for the technology to be understood. We've taken a view that we'd like to see ourselves as the custodian of the technology. We don't want to go to market too early. We want to be sure that whenever the message is delivered to market that it's something we've already delivered that we have built that the engineering effort has already been afforded. You know, small acorns grow into mighty oaks. And so for us, it's about ensuring that we take the time to really give the right fertilizer to the growth. >> And that's a 50 billion dollar problem you said this morning is that right? Is that there- >> Just in insurance. But we have banks as our clients too so, you know, we're shooting hoops. >> So you're saying it's a multiplier of that 50 billion? >> Leanne: Of course. >> Yeah, big multiplier. >> I mean counterfeit good if you extend it into luxury goods it's 1.7 trillion dollars. >> And you talked about the sort of value chain of rough cut, 15 billion and you maybe triple that when it gets polished almost 50 billion and then another one and a half X at retail. Where are the holes in that value chain, everywhere? I mean are you seeing fraud occur throughout that value chain or- >> Effectively. You know, we don't have you know, visibility of complete provenance through the supply chain. And in fact, it's not just limited to the diamond industry. I mean I guess the diamond industry there's the allure of luxury. You know, there's the backdrop of affluence. And then, of course, there's the atrocity of what goes on in terms of or what used to go on so prolifically in blood diamonds. You know, effectively the industry isn't as burdened with technology as say financial services. It doesn't have the legacy of 50 years of technology that it needs to unwind. So, when you really consider what's going on in the market today to bring emerging technology into this space not limited to blockchain even enabling new technologies like high-definition photographs and machine vision our marketplace has the ability to consume that technology quite rapidly. And when you think about the problems in our market or the restrictions in our market it's really a lightning rod moment for us where we've just been fortunate enough to be able to build out a solid engineering rod to be able to capture that lightning bolt of problem. >> Dave: Mm-hmm. >> We've had a lot of discussions with IBM executives this week and they feel security is one of the things that IBM does really well. Talk a little bit about your relationship with IBM what IBM does well what they're good at partnering with. How is it to work with IBM? >> Dave: What they could do better. >> Yeah. >> Absolutely (chuckles). We, in the very first 12 months of Everledger we managed to onboard, you know, a million diamonds. And most people were applauding the efforts of our engineering team. And we certainly applauded ourselves. But Christmas was a very lonely path for me because I started to become shivered by the thought of what would this mean if I went from a million to 10 million to 15 million and then into rough being able to track 320 million carats of rough diamonds across 80 countries around the world. So, when you're a start-up and you're faced with some of the largest organizations and governments around the world let's face it, the industry's 130 years old. You want to be able to look towards a technology innovator like IBM that has been around and reinvented itself over a trusted 100 years. And that transactional trust is at the very core of this fabric. So, some of the things that you look at in terms of a start-up may be actually too isolated. A lot of technology companies that are in the blockchain space are just looking at the blockchain fabric. But for me, it was patently obvious we needed to stretch further. We needed to realize that we have to deliver this into a cloud solution. We have to deliver this technology in such a form that has to be secured. And the security needs to really be from the ground up at the root source right the way through to the front end. And there's no other partner that's actually doing that. There are other service providers in this space that shall not be mentioned. But they're, of course, taking whatever nascent technology is being built and putting it into the cloud. IBM has really taken the time to sew together the right security fabric. >> And that's about scale for you, right? I mean you wouldn't be able to scale without it. >> I sleep at night knowing that we have IBM. Like as a CEO, I sleep at night. >> My understanding, there's container technology that you're using in here. Most people think of containers as security's one of the holes there so, you know, how do you feel with the security of containers today? And maybe you can share a little bit about you know, what IBM's doing specifically for that. >> Yeah, I mean the container services team that we've been working with and today I had the absolute privilege it was a diary note moment for me to present on stage with Donna. You know, her background in security has afforded us the ability to really deliver this quite quickly. The work that they have been doing is recognized not only and I touched on the surface of the three markets that of real concern or focus for us is fraud and theft and cyber. And when you consider the container services and the security team that's wrapped this around I really think that actually one of the silent winners in this is the reduction in cyber crime. And maybe that hasn't been focused on too largely. And the 50 billion dollars that I was talking about was really around document tampering and, you know, the over-inflation of insurance claims. When you really think about it it's actually cyber crime that I think we could actually truly solve as part of the solution itself. >> So explain again, Leanne, how does it work? So each diamond has a unique identifies it's got a fingerprint on there. How does it get on there? >> So there are existing processes in industry. There are two parts to the market first is rough diamonds and the second is polished diamonds. And as diamonds are crossing borders as a part of international trade they're often inspected by gemologists. Those that, of course, have received licenses in the skill of identifying diamonds. But that's all- >> Dave: But that's a spot inspection, is that right or- >> Correct. >> Dave: Yeah. >> But there's also actual machinery. So there are certain types of science that have been applied and have been applied for a number of years. And one of the challenges that we faced with ourselves is to IoT-enable the diamond pipeline. So, some of these machines have been in existence. They're highly calibrated and they have precision but that data is often blackboxed. It's not, indeed, ledgered or stored for public view or even inter-office view. And so one of the tricks that we've enabled is the ability to take all of those data points 40 meta data points as well as the reputation or the expert opinion and lay that data into the blockchain. So we're layering really a reputation score not only of the person, the machine but also the diamond and the validity of that diamond. And that can only come over time with large aggregated data sets. >> Okay, and that is your providence. You said the world's provenance is locked in paper. So now you're locking it into- >> Leanne: You're listening >> The blockchain. Of course (chuckles). I knew we had to talk to you. We better listen. Okay, so all right. And then can you explain the banking crisis the liquidity crisis in the diamond business? >> Leanne: Yeah, absolutely. >> What's that stem from? I didn't quite understand. >> It's really affecting the middle part of the pipeline. We have very large mining companies and of course quite substantial retailers but it's the middle part of the pipeline that's really being caused in terms of a squeeze. And so they are the diamond cutters and polishers really generational businesses that have perfected the art and the skill of cutting diamonds. It's the middle part of the pipeline that's really being affected at the moment. And as I mentioned there are two brave Western banks that remain supporting industry. The largest, which has been really in industry for quite some time is ABN AMRO. And proudly, they still remain. And Barclay's Bank. But we've seen an announcement more recently with Standard pulling back out of the industry for a lack of transparency and a burden on their balance sheet. This, of course, has come from Basel III and some of the regulations that's been pushed down from them. And if we're able to take certification and extend transparency but also bring certification to the next level to enable a collateral management system to be built so banks can take the security on the underlying asset rather than just take a balance sheet position it will lift the burden on their balance sheet. It will give them security of the diamond. And let's face it, diamonds are worth something. And as I said when you start to understand the true effect of rough to polished to track the diamond through its lifecycle and give security is something that banks are open-minded about. >> Yes, okay. So it's not a chicken and egg problem it's a transparency begets liquidity is that right? That's the premise anyway >> Yeah >> Dave: That you're testing basically making that bet with your company. We don't have much time but I just wanted to ask you about your company. You're an entrepreneur. You started the company, you said 18 months ago. Funding, VC, you know, give us the lowdown. >> Sure, sure, sure. I mean I came into London in October of 2014. And I was desperate to talk to insurers. And so one of the largest insurers in the London market is Aviva. And they had a hackathon at Google so I thought hey, this would be all right. I'm just going to Trojan Horse the event and see if I can have a talk to the CFO and COO. So I went there. They opened up some APIs. And because I, of course, had a technical background I thought those APIs are hopeless there's not much I can do with that. But if you want to solve some of the problems here this is what you can do. You can take diamonds, take certification and put it on the blockchain as a way to reduce fraud. And at that hackathon I was awarded the innovation prize. But the managing director of Barclay's Techstars was one of the judges and came to me and invited me to join them as part of their accelerator in London which began in March 2015. And, of course, I thought this is crazy. Why would I want to do that? Why would I want to be in London with a bank? It doesn't really make too much sense. And let's face it, I mean Australia is a much nicer country to spend your holidays in rather than London. But in any event, I returned and participated as part of the Barclay's accelerator and I've been supported through the process of the acceleration. But Barclay's is both a bank and an insurance company in Africa so the penny dropped and we put our head down. We wore some letters off the keyboard and Everledger was born. And away we go. >> And so Barclay's funded, in part the company or- >> Barclay's and the Techstars accelerator program have a seed funding event which is a part of the acceleration program for start-ups if you're chosen. And we were fortunate enough to be chosen. And since that time we've been we haven't disclosed who one of our backers are. >> Dave: Okay. >> But we will, in time. And so we've been funded by a selected name in industry. And we're actually just about to go into our Series A so we're looking towards that in the next number of months. >> Dave: You're not even in Series A yet? So you've gotten this far without even getting to your Series A? >> Leanne: Yeah. >> 980 thousand? >> Well, we have revenue, so- >> Dave: Yeah. >> This is my last start-up. I had to go through an intervention with my family to enable me to be here. >> Dave: This is my last So this is it. >> Dave: We've heard that before. >> I promise. I know, it's true, it's true. >> Opportunities beyond diamonds or is that getting too ahead of our speech here? >> Diamonds, watches, art, fine wine you know, and I'm completely empowered by how do we bring what the diamond industry did so well in the reduction of blood diamonds and bring ethical trade really to the forefront of the mind of the consumer and also the mind of the financial services market. So, you know, for me it's really around that part of the world. If that nexus point comes together then I'll keep getting out of bed for it. >> Awesome. Great story. Impressive entrepreneur. Thanks for coming on theCUBE. >> Leanne: Yes, thank you. >> London's not so bad (chuckles). Comment? >> London's probably watching. (Dave and Leanne laugh) >> All right, thanks again. Keep it right there, buddy. Stu and I will be back with our next guest. We're live from IBM Edge in Las Vegas. We'll be right back. (low tempo music)