 Hello everyone, welcome to Special Cube Conversations. I'm John Furrier here at the Cube Studios in Palo Alto. I'm joined with Jeff Jonas, who's the co-founder and CEO of Stealth Startup called Sensing. He won't talk about it, I tried to wrestle under the ground to get information launching later in the month. You're in town, thanks for swinging by. Former IBM Fellow, Cube alumni, some great videos. Check out Jeff Jonas, search Jeff Jonas at the Cube on Google and check out the videos. We've had great conversations over the years. The last time we saw you at IBM event, riffing on the context of data, you're written up and recognized by National Geographic as one of the major, the innovator in data space, which is big honor, congratulations. Thanks man, I appreciate it. Couldn't have to have a better person. Lucky, lucky. So what's going on? Tell us about the new startup. You know I had a great run at IBM. They were really good to me when they bought my company. They were good to me for 11 and a half years. I think I was the longest standing founder from an acquired company that IBM ever had. Great run and then they were good to me on an exit. I proposed something last in 2016, in June. I kind of like it was a red pill, blue pill, matrix kind of move. I went, hey, I got some ideas. But it's time to go. I got to get back to my entrepreneurial spirit. Blue pill, red pill. And they were like, you're a, but you're a fellow. You know, go to, go to research and live happily ever after. You've made it. You've made it. You're a fellow. Why won't you do anything else? Why would you be a lowly entrepreneur? And it truly is the, of all the things I've done that I've like, wow, that is crazy to happen in my life. That's actually the single highest. It's over a few other things. It's a big deal. It is a huge deal. So. But you're an entrepreneur. You're scratching an itch. So this is, so what happened to the blue pill, red pill? Yeah, so, so the, one of the options was, hey, I've been working on this thing here at IBM called G2. It was my next generation entity engine. Figures out who's who in your data matches identities. We've been working on it for years. I think nine years and I just said, I'd like to go build a company around that and I'll give you a rev share. You'll make more money than if I stay. They're like, oh, that's a great idea. Let's have a partnership. Let's do that. So August of 2016, I spun out the source code. Who was the main executive that got behind this? Was it? I was Bob Pitchiano. Bob Pitchiano. He's very entrepreneurial friendly. Yeah. And he had to get alignment across a whole bunch of IBM to make this happen. Anyway, I just, I'm really fortunate in the partnership that I have with IBM even to this day is just extraordinary. So did they fund you as well? Fund, no. I funded it myself for the first five or six months. I took two in money from two private investors that I've known a long time. Really smart, strategic money. They're very active in my business. And you know them? Yeah, I've known them for a long time. One of them was a customer of mine. One I sit on the board with. So the inner circle, they're in the boat. You got some good people that you know in the boat. Yeah. You know, some people are like, how do you manage your investors? I'll be like that, we don't even talk that much. We hang out. Yeah, we hang out. They manage me. Like I go to them and they help me. That's the way it should be, right? Different. You don't have VCs on your board? No, but that's the formula. That's what you want. Entrepreneurs these days get so starstruck on having investors, but it's hard work. You want to get people that you trust and you like. Yeah, I learned that in my first company. We had two rounds of venture capital in my first company. I learned a bunch of things, but they were still, they were great investors. It was a great relationship. I learned a lot about VC because I have my own money in four VC funds. I have Angel-funded four or five companies. But with all of that in mind, I have a really clean cap table. But anyway, so we've been off to the races since August of 2015. So that's when you left IBM. So last time we checked, okay. Yeah, and then I went into stealth mode. We've been collecting real customers. We've been iterating on the product. Our calling, if you will. We know when I left IBM, I sat there with this thing called G2 and I'm like, this is the only thing that makes my team and I special is how to figure out in data, especially big data, who is the same as who? Across cultures, across languages and scripts and doing it where you don't need a data scientist, you don't need an expert to tune it. And I did a survey of about 50 companies out there that are out there in the same business selling entity resolution. And almost all of them say call for a quote because it's also hard. And really it's hard to find any software that's world class. It's less than a quarter of a million and you're going to spend a million. And so what we've been doing is working on making it so easy to consume that. She is moving it down from high ticket item, probably bolted on a ton of professional services to much more turnkey, democratized. I mean, is that what I'm getting at? Yeah, totally. You're absolutely right. Like we don't even have professional services. We're like download and try it on a subscription license. You pay monthly, we send them the code so no data flows to us. And when I, this is kind of funny, you know, and it's very private. Oh, I know I'm saying this on your cameras and all, but every team meeting, you know, our mission is smarter entity resolution for everyone everywhere. And then I tell my team, what's going to make our company amazing is no one calls us, everyone loves us. And we've been really working on iterating on that. You know, every time somebody has any reason they have to call, that's not a moment of joy. And you're launching when this month, right? We are launching. Because you're dark. Yeah, yeah, yeah. There's nothing on the web. Sensing.com's on the web, but it's the right this split second, it's a hold off, a holding site. There'll be a better, the real sites coming out very, very soon, like in the order of next week. This is total stealth dark mode. We're in really dark mode. And although we've been collecting again, customers and great logos, IBM's a customer. They license G2 from us. And so they didn't put money in. No, they did not put money in. I'd put my own money in. Well, I guess they bought my company and then I put my money in. So in some sense, you could say if you follow the money. Do they own any? No, they don't own any of the company. But there's a business partnership. Absolutely. And it's an incredible relationship. We have all kinds of interesting things to do with IBM. It's almost as if I'm not left. They just don't give me a paycheck anymore. Which is why they're like, that guy's a fellow, why is he doing that? He's going to go start a company. Why would he do that? Because you're an entrepreneur. That's why. Well, that's awesome. What are you working on at IBM with the G2? And then, and I know you don't want to talk about the product. And I will spec that out. I'm just trying to dig at it. But what I really want to do is because you're going to launch in a couple of weeks anyway. Let's get the aperture of what you're looking at. What market are you looking at? What problems out there? You mentioned entity is one piece. What's the key thing that you're looking at? You know, the key thing is organizations have all of this data in all of these piles and they're having difficulty knowing it's about the same person or the same company. And I'll just give you one of my favorite use cases. It's just G2 has been in production already for many years. Maybe my favorite deployment to date was deployed in 2012, yeah, 2012, five years ago, six for a company called Eric. It's a nonprofit. It's run by states. 22 states put their data in there on voter registration data. And it's used to improve the quality of election roles. And it's got my privacy by design features baked into it. And I'm just so damn proud of this thing. You know, the Democrats like it, the Republicans like it. That's a winner. No calls and everyone loves you. Yeah, no, that's the truth. And you know, this system's got a quarter of a billion records about 100 million people and they have one person in IT that runs the entire IT department, including G2. Like this is unheard of. So then that's been in production for five years. But the range of companies that are having a challenge with who is who in their data is... And give me an example of what that means. I'm trying to grope the who is who like across multiple databases or give me an example. You see in the voter registration system, you have somebody's registered in two different states but it's the same person. You've got to get the data together to realize it. Somebody's registered in two states. And that's because they moved. If you've ever moved between states, you may have forgotten to unregister. Of course I did. But that's illegal. Every person does. That's illegal. I mean, by 1% would actually go through the motions. Tell the state I moved. Right. All these jury knows I'm getting in New Jersey. What's happening? Exactly. So you got these two piles of data but when you combine it, you see that these two be able to be the same and they're registered in both. So now they can go back to somebody and say do you want to be registered in both. But now I'll flip in and give you an example of companies. There's a, one of our customers does supply chain risk. They take vendors from the biggest global brands. And in their vendor lists of all these companies across the world, there's duplicates in there. And then of course these companies use the same manufacturer. So there's duplicates across these lists but this is messy data. Then they scrape the web and look for toxic spills, child labor and other derogatory data about manufacturers in China, the Philippines, India. And this is super messy. Entity extracted data off the web with just the crappiest addresses you've seen. We, they got our code on a Tuesday. They didn't call us until Thursday. And when they called us Thursday, they just said, and what they did is they combined all of this data so they could go back to a global brand and say, hey, this manufacturer is going to cause you risk to your reputation. And you're resolving who is who. You're untangling a lot of messy data and making it insightful. Analyzing it insights and we got a, this is the example they got the software on Tuesday without a call, they called us Thursday and said, we've canceled all of our own internal work to try to match all this. We're just using your stuff. It's done. And the last we just heard from them, they just went, the quality of your matching you're doing without any tuning or training. It's a special kind of real-time machine learning that we invented. No training, no tuning. And it, they just went, it's the results it's getting our human quality. So obviously you want to talk about price points, but I mean, it's affordable sounds like. It's what you're trying to make it. You're, it sounds like you're mission driven on this thing. So it's not like, I mean, I mean, you've already made some good, good dough as an entrepreneur. I thought you're not afraid to make more money, but this is a mission driven opportunity. So many organizations are struggling with this. We are going to make it affordable to the smallest companies. And I, I can't quite tell you the price point, but- We take care of us with theCUBE, right? Think order of magnitude less than any other option. Can you take care of us? Oh, I can hook you up. We had duplicates all over the place. And we'll give it to you where you're going to, isn't her tell set too? That would be great, yeah. Question for you. What's your take on crypto blockchain? Because, you know, you mentioned know your customer is a big part of anti-money laundering, big part of, you mentioned privacy baked into your, by design there. This is now a phenomenon. And so you look at China with WeChat and making real names, be real identity, be part of that system. So more and more of this potential attention, public data is going to be out there. What's your take on know your customer and some of these trends that are involved? Well, you know, on blockchain, what it really is, it's calling. I mean, I see a lot of people using the term blockchain around that just anything. Yeah. Because it's a- Buzzword. Got a lot of buzz. Yeah. But the reality is, it is a tamper resistant ledger. And I've been writing about immutable audit logs and tamper resistant ledgers in my privacy by design work before blockchain came out, which is really distributed form. The value of it to the kinds of work that we do is a tamper resistant log allows you to connect it to software so that when say somebody searches for something, you can record it in a tamper resistant way. And why would you want to do that? Well, if you've created an index in some central data, you want to make sure it's not being abused. You want to make sure the person that's searching and is not searching up their neighbor or their daughter's new boyfriend, that would be an abuse, right? Yeah, yeah. Right, so a tamper resistant auto log would be a great place to put that, that would be a natural thing to do with blockchain. Yeah, awesome. So you get the launch coming. How are you doing? Are you doing any marathons and triathletes? Triathlons, what are you doing? I think since I was last on your show here, I became one of three people to do every Ironman on the world, every Ironman triathlon. There's one person in Canada, there's one person in Mexico when I'm representing America. You're the American representant in all triathlons. You know, if you go to the ironman.com webpage, there's a list of races around the world. And I'm one of three that can just look at every single race and say yes, yes, yes. Your favorite. Austria. Why? It was beautiful, it was a great course. It was well run. I had good time. Beautiful weather. And you're worst. The one you had the bike on the plane and you lost your luggage. Oh, I had a really, really dark time this last year at the race in South Korea. And this is how bad it was. It's the only race that I walked across the finish. And I sat in this bathtub. This is embarrassing, okay? I sat in this bathtub with the shower thing that you have to hand hold over my head. And I was trying to cry because I was so defeated but I was too dehydrated to even cry. The level of failure. It just knocks you down. When you can't even cry. Well, you know, you went from IBM fellow to lowly entrepreneur. How does it feel? I mean, you're back rolling your sleeves up, getting down and dirty, fun. Having a blast? I really love being a benevolent dictator. How many people on the team? We're like about 16 if you count people that are full-time or half-time or better. I have a few people that are half-time or better. But yeah, so about 16. That was some fun. Great, Jeff Jonas. We'll be looking forward to your launch. Sensing.com, S-E-N-Z-I-N-G. Dot com, former IBM are great to see you and we'll keep you in touch. And where are you going to be headquartered out of? What's the location? Venice, beach California where I live. Although my team is scattered all over the country, we also are licensed in Singapore. And we are hoping to launch Sensing Labs or R&D activities out of Singapore. All right, so we'll pop down to LA and check you out when you're up and running. Okay, Jeff Jonas, stopping by theCUBE here on a great Thought Leader Thursday. I'm John Furrier. Every Thursday we do the Thought Leader interviews with friends, colleagues, CUBE alumni, and more. Always looking for great people. Have to be a Thought Leader. Have to have original content and be an innovator. Thanks for watching.