(upbeat violin music) >> Hello and welcome to Special CUBE conversations. I'm John Furrier here at theCUBE Studios in Palo Alto. I'm joined with Jeff Jonas who's the co-founder and CEO of a stealth start-up called Senzing. He won't talk about it. I try to wrestle him to the ground to get information launching later. You're in town. Thanks for swinging by. Former IBM fellow, CUBE alumni. Some great videos. Check out Jeff Jonas, search Jeff Jonas theCUBE on Google and check out the videos. We've got great conversations over the years. Last time we saw you at your IBM event, riffing on, you know, the context of data. You're written and recognized by National Geographic as one of the major, the innovator in data space, which is a big honor, congratulations. >> Thank you. >> I appreciate it. Couldn't happen to 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 it 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've got to get back to my entrepreneurial spirit. Blue pill, red pill and they were like yeah, but you're a fellow. Go to research and live happily ever after. >> You've made it, you're a fellow. Why would you do anything? Why would you be a lowly entrepreneur? >> And it truly is, of all the things I've done, that I'm like wow, that is crazy to happen in my life. That's actually the single highest. It's over a few other things. >> John: It's a big deal. >> It is a huge deal, so. >> But you're an entrepreneur. You're scratching the itch. So what happened with the blue pill, red pill? >> So 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 stayed. They were like, oh that was a great idea. Let's have a partnership, let's do that. So August of 2016, I spun out the source code. >> John: Who was the main executive at that point? Was it -- >> It was Bob Picciano. >> Bob Picciano. >> Yeah. >> He's very entrepreneurial-friendly. >> Yeah and he had to get in alignment across a whole bunch of IBM to make this happen. Anyways, I was really fortunate and the partnership that I had 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, money from two private investors that I've known a long time. Really smart, strategic money. Very active in my business. >> John: And you know them. >> Yeah, I've known them for a long time. One of them was a customer of mine. One I sat on the board with. It was just great. >> So the inner circle, they're in the boat. You've got some good people that you know. >> Yeah. Some people are like how do you manage your investors and I'm like, we don't even talk like that. >> We hang out. >> Yeah, we hang out. They manage me. Like, I go to them and, help me. >> That's how it should be, right? >> It's 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 star-struck 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 capitals in my first company. I learned a bunch of things, but they were great investors. It was a great relationship. I learned about VC because I had my own money in four VC funds. I've been able to fund four, five companies, but with all of that in mind, I have a really clean cap table. But anyway, we went off to the races since, since August of 2015. >> John: So that's when you left IBM, last time we checked. >> Yeah. >> Okay. >> 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. You 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 of selling entity resolution and almost all of them say call for a quote because it's all so hard and really, it's hard to find any software that's world class that'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-- >> You're moving it down from a high ticket item, probably bolted on a ton of professional services to a much more turn key democratized-- >> Yeah, totally. You're absolutely right. Like we don't even have professional services. We're like download it, 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 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, any time somebody has any reason they have to call, that's not a moment of joy. >> You're launching when? This month, right? >> We are launching. >> 'cause there's nothing on the web. >> Yeah, yeah, yeah. Senzing.com is on the web, but at right this split second, it's a holding site. There will be a better, the real site's coming out very, very soon like in the quarter of the next week. >> Total stealth dark mode. >> We're in really dark mode. 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 put my own money in. >> I guess they bumped my company and then I put my money in so in some sense, you can say if you followed the money. >> Do they own any? >> No, they don't own any of the company. >> But there's a business partnership. >> Absolutely. >> Okay, got it. >> And it's an incredible relationship. We have all kinds of interesting things we're doing with IBM. It's almost as if I've 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 it? He's going to go start a company? Why would he do that? 'cause you're an entrepreneur. That's why. Well, that's awesome. What are you working on at IBM with the G2 and I know you don't want to talk about the product and I respect that even though I try to dig at it. But what I really want to do 'cause you're going to launch in a couple 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 that organizations have all of this data in all of these piles and they don't, they're having difficulty knowing about the same person at the same company. And I'll give you one of my favorite use cases that's, you know, G2's 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 non-profit. 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. I share the privacy community. >> No calls and everyone loves you. >> Yeah, no, that's the truth and this system, it's got a quarter of a billion records of 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 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 just everywhere. >> And give me an example of what that means. I'm trying to crop that, who is who like across multiple databases or? >> Yeah, I'll give you an example. 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 that 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. Most people do. >> Every person does. >> That's illegal. >> Like 1% would actually go through the motions. >> Lawbreaker. >> Tell the state I moved. >> Right. >> As far as the jury knows, I'm getting a new jersey. What's happening? >> Exactly, so you've got these two piles of data, but we combine it, you see that these two are the same and they're registered in both. So now they have to go back to somebody and say do you want to be registered to vote? But now I'll flip and give you an example of companies. There's a, one of our customers does supply chain risk. They take a vendor, some of the biggest global brands, and in their vendor list of all these customers across the world, there's duplicates in there, and then of course these companies reach the same manufacturers and 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 and then they extract the data off the web, with just a crappy as you can see. 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 was they combined all the data so they can go back to a global brand and say hey, this manufacturer is going to cause you risk to your reputation. So they're resolving who is who. >> You're untangling a lot of messy data. >> Yeah. >> And making it insightful. >> We get insights and we got a, this is an example. They got this offer on Tuesday without a call. We got a call on Thursday and said we canceled all of our internal work to try to mess with all this. We're just using your stuff, it's done. And the last we 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 they went, the results it's getting are human-quality. >> So how, obviously you don't want to talk about price points, but it's affordable, it sounds like. It sounds like you're mission-driven on this thing so it's not like getting, you've already made some good dough as an entrepreneur. 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 can't quite tell you the price point. >> It's okay, we're at theCUBE. >> Think order of magnitude life in any other option. >> Can you take care of us? >> Oh, I could hook you up. >> We have duplicates all over the place. >> We'll give it to you and you'll get a towel set too. >> That would be great. Question for you. What's your take on crypto block chain because you mentioned, you know, your customer's a great part of anti-money laundering, big part of, you mentioned privacy baked into by design there. This is now a phenomenon. You looked at China with WeChat. They're making real names, real identities be part of that system. So more and more of this potential attention, public data's going to be out there. What's on your take on, you know, your customer and some of these trends that are involved in this? >> You know, on block chain, what it really is, it's calling, I mean I've seen a lot of people use the term block chain around that just ain't it. 'cause it's got a lot of buzz. >> Buzzword. >> But the reality is, it is a tamper-resistance ledger and I've been writing about immutable audit logs and tamper-resistance ledgers in my privacy by design work before block chain came out, which is really distributed form. The value of it to the kinds of work that we do is a tamper-resistance log allows you to connect it to software so that when say, somebody searches for something, you can record it in a tamper-resistance way and why do 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 that the person who's searching is not searching out their neighbor or their daughter's new boyfriend. That would be an abuse, right? >> Yeah, yeah. >> Right. So a tamper-resistance auto log would be a great place to put that. That would be a natural thing to do with block chain. >> Awesome. So you got the launch coming. How are you doing and are you doing any of the marathons and triathlons? What are you doing? What's the latest? >> Since I was last on your show here, I became one of three people to do every Iron Man on the world, every Iron Man triathlon. There's one person in Canada. There's one person in Mexico and I'm representing America. >> You're the American representation. 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's beautiful, it's a great course. It was well-run. I had a good time. >> Beautiful weather and people. >> And your worst? The one where you had your bike on a plane and you lost your luggage? >> Oh, I had no, 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 where I walked across the finish and I sat in the bath tub. This is embarrassing, okay? I sat in this bath tub with the shower thing that you have to hand-hold over my head and I was trying to cry 'cause I was so defeated, but I was too dehydrated to even cry. The level of failure. >> It just knocked you down. >> When you can't even cry. >> Well you know you went from IBM Fellow to lowly entrepreneur, how's 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. >> John: 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 who are half time or better so yeah, about 16. >> Sounds like fun. >> Great fun. >> Great, Jeff Jonas. We'll be looking forward to your launch Senzing.com. S-E-N-Z-I-N-G.com. Former IBMer, 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 Senzing Lab's RND activities out of Singapore. >> Alright, so we'll pop down to LA to 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 look up to great people. Have to be a thought leader, have to have original content and be an innovator. Thanks for watching. (upbeat violin music)