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Eran Shir is the co-founder and CEO of Nexar which makes every car smart and is building the world’s safe driving network. The company has raised $100 million from top tier investors like True Ventures, Slow Ventures, Samsung NEXT, Expansion Venture Capital, Mosaic Ventures, Aleph, Maniv Mobility, Tusk Venture Partners, Ibex Investors, Nationwide Ventures, 40 North Ventures, Micron Ventures, and Corner Ventures to name a few.
In this episode you will learn:
- The future of self-driving cars
- Insights on mapping epidemics as complex networks
- How much data Nexar has
- Nexar versus Google Street view
- Working inside Yahoo!
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Remember to unlock for free the pitch deck template that is being used by founders around the world to raise millions below.
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About Eran Shir:
Eran Shir is the co-founder and CEO of Nexar, an artificial intelligence dashcam application that seeks to rid the world of car crashes. Nexar is a vehicle-to-vehicle network connecting cars nearby; it can warn its users in real-time of dangerous situations happening beyond each individual driver’s line of sight, such as issuing a forward collision warning, effectively giving drivers more time to react.
Prior to founding Nexar at the beginning of 2015, Eran Shir was the entrepreneur in residence at Aleph, a Tel Aviv-based venture capital firm, where Eran Shir focused on
big-data, crypto-currencies and market disruption.
Eran Shir also was the senior director and head of the creative innovation center at Yahoo!, where he was responsible for their creative advertising technologies strategy and portfolio, as well as the development of their next-generation personalized creative advertising platform.
Connect with Eran Shir:
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FULL TRANSCRIPTION OF THE INTERVIEW:
Alejandro: Alrighty. Hello everyone, and welcome to the DealMakers show. Today we have a founder from Startup Nation, and I think that we’re going to be learning a lot about his own journey, building and scaling companies, doing exits, and everything in-between. So without further ado, let me welcome our guest today. Eran Shir, Welcome to the show.
Interviewee: Thank you for having me.
Alejandro: So born and raised in Israel. How was life there growing up in Israel?
Interviewee: Well, I had a pretty geeky life, honestly. I spent most of my days reading and studying physics as a teenager, so not too many fancy stories. I was doing music and doing physics, and that was pretty much my life.
Alejandro: And why physics? What got you into physics?
Interviewee: Actually, it’s an interesting question that maybe someone could even assist me with. Back when I was in 4th grade, I found in the library, this book that was called, I think, [The Alchemies], or something like that. It was basically sort of like a journal of someone in the Manhattan Project, where they developed atom bombs. So it was reading from his point of view describing some of the things that they were doing there, and that opened up this whole world for me and got me excited about physics. I guess since 4th grade, I was focused on wanting to become a physicist. I’ve been searching for that book and couldn’t find it, so if someone knows it and can help me locate it, send me a note.
Alejandro: There you go. After growing up with this geeky mindset as you were mentioning around physics, you studied physics, too, at University, and then after University, you did the mandatory years in the army. And talking about adrenaline-fueled with explosions and missiles, I’m sure that you learned a fair amount about being focused in tough environments.
Eran Shir: Yeah, and also, it was exciting for me because that was actually my first kind of startup experience because I was involved in starting up a new army unit involved with the ballistic missile defense. We were the first army in the world that had a functioning ballistic missile defense system called [The Arrow 4:28]. A small group of soldiers, a few officers, and I were in charge of making it operational, building up the whole what is called SOP, and the whole standards of how to open it. That was pretty fun. Also, yes, getting involved in all kinds of missile testing, which is quite exciting.
Alejandro: I’m sure that when you are dealing there with explosives and things like that, I’m sure that you were able to understand how to be more comfortable with unpleasant moments and with uncertainty, which, at the end of the day, is the life of an entrepreneur. Is there anything that you took away or that shaped your personality or your way, at even in business, that you got from your experience in the army?
Eran Shir: Yeah. You learn how details are supercritical. I remember one example where there was this massive test that people had prepared for like a year or 18 months. All the top brass of the army, the government, etc. are looking at this with anticipation. The missile goes up in the air and starts doing hoops. It’s really not what you want. One day I researched the reason why. It ended up that the reason was that the person that was soldering two wires in some circuit as part of millions of circuits within this massive rocket connected the wrong wires. This little thing blew off like I don’t know how much of an investment. You get an understanding of if you’re trying to do something that is really important or really big, it’s a sequence of very detailed jobs, very detailed activities, functions, and tasks. It’s the small things that you do every day that matter, and not just having the big vision.
Alejandro: Talking about doing something very big, after the army, when you left the army three years after, you did your Master’s in physics, then after this, you go at it as an entrepreneur, and you start building Cogniview Systems. This was your first startup, so tell us about how this came about and how you went about it.
Eran Shir: This was around 2001. I was then fascinated by this emerging field of machine learning. In particular, I was excited about a certain field called Genetic Algorithms. What we managed to demonstrate, a few of my friends and I is that you can automatically create algorithms that are optimized for different people, all different tasks. My vision was I wanted to go and build a search engine, complete with Google, back in the day, with the idea that if one of us should get personalized search results stemming from personalized algorithms. So, each one of us should have a different kind of logic running based on how the search engine knows us. For example, if you and I search Quantum Mechanics, I might get more expert results or papers on the subject, while you might get a Wikipedia page for it. That was our original idea. We ended up not going there because there wasn’t a lot of excitement back in 2001 for consumer search engine technology, so it pivoted to enterprise. It actually went for a few years. I was less excited, at the time, from the enterprise direction. After a few years, I moved back to the academic world and started pursuing a Ph.D. in physics and engineering focused on complex systems, which was what excited me at the time.
Alejandro: So, Cogniview Systems didn’t really have the exit that you had hoped. It was not the outcome that you had anticipated.
Eran Shir: No. It went for like seven years, and it got a few people good salaries for seven years, so that was, from their perspective, a decent outcome. From my perspective, I learned a lot during that time from lots of mistakes that I’ve done, that we’ve done as a company. Hopefully, I managed to use that experience to get better later in my career.
Alejandro: What was that one lesson that you took away with you that you knew, for sure, that if you were to start another business, you would absolutely implement that lesson?
Eran Shir: The one that I think was most important, and the clearest is the size of the founding team. I came out of it with a strong conviction that the optimal size of a founding team is two people, and three people can also be done well. I don’t think that one person is good, except for really special people because you don’t have this sounding board, and people do keep you honest. I think that anything beyond three is extremely challenging. When I was doing Cogniview, I was pretty lax at adding people into the founding team; we were kind of in the ideation phase because I was kind of “Sure. Why not.” It turned out that it created less than productive dynamics. That was one clear lesson. Another lesson is about the dynamics of markets and vision. I like how quickly you’re giving up on your vision, and at the same time, one of the things that people do not appreciate is that the places where the markets are down is actually the best place to start companies in many respects. In 2001, 2002, starting a long-term consumer proposition was actually not a bad idea, just like we saw the same pattern in 2009, 2010, where a lot of the companies that became a juggernaut in that space [0:14:01].
Alejandro: Obviously, here, you got a taste of entrepreneurship, and you got the good lessons, the bad lessons, the good, the bad, and the ugly, everything that goes into it. Why did you go into academia versus launching something else?
Eran Shir: First of all, because I still had that academic bug, and secondly, because I found an idea that blended well my academic aspirations and my startup aspiration. Basically, my academic research was like an academic startup. I raised money from the European Union for a new lab, and I built a crowdsourced project to map the entire internet. Every router and every ISP in the planet, and we’ve done that by building software and asking thousands and thousands of volunteers to install it. It was called DIMES. It allowed us to create the largest dial set of its time in how every router on the internet behaves and looks and where it is and every ISP, and how the internet evolves over time as a network. That was exciting to me because, on the one hand, it allowed me to research this new creation and learn about complex systems and complex networks. At the same time, it was truly an academic startup. I had engineers working in my lab. I actually had to market and distribute our software in the phones of [16:03] and all kinds of places like that. We created all kinds of gamification mechanisms. I don’t know if you remember, like [16:12] at home. That was the era of distributed computing emerging as a thing, and we were pioneers in that, and that was quite exciting.
Alejandro: Yeah, because here, what you were doing essentially was doing work on complex systems, complex networks, and even epidemics on complex networks. What do you mean with epidemics on complex networks? This is technical for me, and I’m sure it is technical for other people listening.
Eran Shir: Yes. One of the interesting questions that we asked ourselves at the time was, how do viruses propagate on complex networks, on real networks? And how can you develop mechanisms to block them? I built some of these models and published 15 years ago in Nature Physics, some work on exactly that, on the dynamics of epidemics on complex networks. What was interesting was that it was very different for what people thought about, at the time, what typical epidemiologists think about [17:38] model and all this kind of stuff. It turns out that’s not how the real dynamics work, and we can see after these days very vividly because when we do this kind of mathematical model – I have a certain population and a certain percentage get infected. We all became a couch of epidemiologists in the last year. So we all know about [18:11] and all these kinds of factors. It turns out that’s not how it works because there is a big variance between different nodes in this network. I might be sitting in my house all day and not meeting anyone physically, and that’s not infecting anyone, versus someone who is selling in a grocery store, and he’s seeing dozens of people every day. So his probability of infecting someone is much, much higher than mine. Because of that, he has a chance to be what’s called a Super Spreader, someone that pushes the disease, the infection, forward. This whole dynamic that is very different from the type of bell curve that we all know and imagine – someone is a bit higher; someone is a bit taller or shorter, but it’s pretty much the same. In the case of networks, it’s really not the same. It’s much more like the distribution of wealth in the world. I don’t have as much money as Bill Gates, not in a long shot. But we have several orders of magnitude difference between us, and the same thing happens with epidemics. Because of that, you have to change the way you deal with them, and you have to focus on this kind of super-spreading dynamics and mechanisms, and 90% of the population have very little [19:59].
Alejandro: Yeah. It seems like you were doing exciting work here on the academia side and the research. So why did you decide to put it on hold and shift gears toward starting a new business with Dapper?
Eran Shir: The main reason is, again, pursuing ideas. I don’t really have a career in the regular notion of planning what I’m going to do five or ten years from now. I’m really pursuing exciting ideas that excite me and in particular, moon shots. I like ideas that look important or ideas that I think I won’t do them, no one else will. With that, my idea was, what will happen if we turn the web into a set of building blocks, Lego blocks? At the time, you could consume the web mainly by going to a browser and typing in some URL, finding it on a search engine, and reading, and experiencing it through your eyes as a human. My question was, what if we turn every website on the web into an ATI and, basically, into a building block, and we let people take all of those building blocks and create new things with them? Basically, that’s what we did at Dapper. We created this machine learning technology that could take any website, understand its structure, and then turn it into an idea. People got excited about it. That process took about three to five minutes, so people would just come and turn their favorite website into these APIs and create Mashups and create applications and Google Gadgets and Facebook apps, and all kinds of cool stuff. We felt like it’s unlocking the real web creativity in a sense.
Alejandro: So, let’s fast-forward because then you come to the U.S. when you were supposed to do your Series B financing round, and then all of a sudden, the market collapsed, and you find yourself reorganizing the company. Tell us what happened there.
Eran Shir: A year and a half into Dapper, we decided that I need to San Francisco to develop the business. I arrived in August 2008 in The Valley and in the middle of working on my B round, meeting investors up and down Sand Hill Road. Then things looked pretty good, and I was promised a term sheet around the middle of September 2008. Then everything collapses, and instead of a term sheet, I get a phone call saying, “We’ve closed for business,” in a sense. We had to do some quick thinking on our feet. Thankfully, we had great investors in Accel Ventures, which is an amazing marque venture fund. They were very supportive through that wrenching experience. I also had to let go of some 25% of my workforce at the time and reorganized the company and just execute and work through it. Slowly, but surely, through 2009, we picked up more and more business and partners. In the beginning of 2010, we already were doing significant business with several partners, among them Yahoo! By mid-2010, they were starting to convince us to join them, and eventually, by the end of the year, they bought us.
Alejandro: So, obviously, a nice outcome – over $50 million of a transaction, but how did this happen? You were eluding that it was a partnership that eventually turned into an acquisition.
Eran Shir: Yes.
Alejandro: Was it all of a sudden, one day they say, “Guys, we want to do an acquisition,” or what was that process like?
Eran Shir: That was interesting. It started with what we, in Israel, call a [25:43], a big mistake on my part. So, we started the commercial partnership with Yahoo! in something like mid-2009. The reason they wanted to partner with us is because we had some unique technology around next-generation advertising, dynamic advertising. Basically, the way we made money at Dapper was turning all this content of our advertisers in the website into dynamic ads. We were one of the first few companies inventing dynamic ads and retargeting and all this kind of stuff. We started commercially working with them. Apparently, they were excited by the results. Fast-forward at the beginning of 2010, some of the investors invited me for a meeting. I thought it was just a commercial meeting, but they were actually trying to present us to some of the top brass at Yahoo!, some C-level execs. There was a mix-up in the times, and I arrived an hour late, and they were super upset like, “That guy is not accustomed to waiting for anyone.” But it couldn’t be a waltz kind of first date, I guess. But we passed beyond that and built relationships, deeper and deeper relationships. They came to the conclusion that we’re best of breed in that field, and it would make sense for them to acquire us. It took us a while to wrap our head around it and the notion of acquisition because we were enjoying life as an independent company, but told them. At the end of 2010, we came to an agreement, and we saw an opportunity to scale the business together with Yahoo! and joined forces.
Alejandro: The at Yahoo!, you spent a couple of years. During that time, you developed their native advertising platform, which ended up being a billion-dollar business. But here, you were really exposed to the politics and the dynamics. I’m sure that perhaps for you, that was not as exciting as building your own startup. So, what were those politics like, and how did you navigate through it?
Eran Shir: I tried to stay away from it to the extent that I could. For a long time in the beginning, and the first couple of years at Yahoo!, I managed to do it because I was head of an innovation unit, about 100 people, minding my own business, etc. Thankfully, also, I reported to this amazing person called Bruno Fernandez-Ruiz, that was my boss and ended up being my partner also at Nexar, and at this point, we were partners for life. I was actually having a lot of fun, and because I’m also an entrepreneur – when you come as an entrepreneur into a large corporate, you can do pretty much what you want and be forgiven, in a sense. Where the politics started to really be problematic was when we started to succeed at scale. So, Bruno and I started this project around native advertising and native content back in 2012. Marissa Mayer, who was the CEO, approved the project for us and let us run with it. But then in the beginning of 2013, she realized that it’s actually going to be a big deal. Initially, it was like, “Okay. There’s a big company. Lots of projects. You do another one; no problem.” At some point, it started going quickly. Then the mistake that she did was she actually announced to the world that inside Yahoo! and that it’s going to be one of her major initiatives for 2013. What happens in a company like Yahoo! when the CEO announces that this is going to be a major project, what immediately happens is that every SVP that is somehow related wants a piece of the action. You want to be relevant, you want to walk on things that matter, so all of a sudden, you get this whole turf war dynamics, and it was quite funny and amusing, in retrospect, to see that human dynamics kind of play. But at that time, it was quite annoying. We kept going, built that business, but by the end of 2015, I said my goodbyes from Yahoo! and left.
Read More: Max Simkoff On Raising $230 Million To Transform Real Estate With Machine Intelligence
Alejandro: Let’s talk about this phase because now, you and Bruno, you’re ready for another moon shot, and now Nexar comes knocking. What happened with Nexar, and how did you come across the idea, and how did you come about bringing it to life?
Eran Shir: I took a year of sabbatical as an entrepreneur in residence in VC called [32:50], a great VC in Israel. That gave me and also Bruno time to research. We came to that research with one important insight, what we thought is important and interested in exploring. That was that deep learning and machine learning that we knew from Data Center and Cloud experience at Yahoo!, we saw deep learning moving to the edge, to edge devices, to smartphones, and IoT devices. That was fundamental for us. It felt like a tectonic shift that will have lots of implications because the minute you can do that, you can do intelligence in real-time. You don’t have to do everything in the Data Center and in the Cloud. If you can do things in the edge, you can provide intelligence to [33:53], real-time use cases. For us, as we looked at the world and asked ourselves, “What is a problem the world is dealing with that we can help the world in a meaningful way?” We kept going back to mobility and driving because other than missiles, driving is the most real-time experience that most of us will experience and that was one important aspect of it. But the other one was that there was this disconnect between what the industry is promising us and what reality shows. If you look at the number of collisions and the number of fatalities on the road, you see a consistent growth from 2010 to this day. Every year, more fatalities, more collisions. At the same time, people are talking about autonomous vehicles and safety and all these kinds of sophisticated technology coming into the vehicle. We looked at it and said, “What gives? What’s going on here? Why is it that, on the one hand, you have multi-billion-dollar companies and tens of billion-dollar companies talking about how collisions are going to go away soon, and at the same time, we see the number of collisions and fatalities going up, the number of congestion events and the amount of congestion going up. There’s some fundamental disconnect.” We thought that we understood that disconnect, and we decided we were going to try and deal with it.
Alejandro: Then, what were the next steps?
Eran Shir: The next steps were to try to come up with a framework that will try to solve the problem. The problem was time. When you are getting into a stressful situation on the road, you have a very limited amount of time to react, both you as well as the car because you’re only reliant on sensors that are in the vehicle, whether it’s your eyes, whether it’s cameras on the vehicle, lighter, it doesn’t matter what, you are confined to what’s in the vehicle. Our idea was, if you build a network of vehicles that communicate all the time, share information in real-time, that will allow us to vastly improve the situation. We raised some money in the beginning of 2015, and we started working on exactly that – building a network. Initially, we were building it in a single city, just in New York City, and just in Tel-Aviv, and starting to build the technology, and AI, and deploying AI at the edge on a smartphone and in a camera – all these kinds of things – a lot of technology that you need to build and start hustling, start distributing these, going up and after the market. Our main go to market strategy was not going to the [37:36]. We were like, “There’s no way to build a network through [37:42] manufacturers because none of them have enough critical mass to create a network to begin with in any area. You have to go over the top; you have to go after the market. So we latched onto this concept of dashcams and cameras in vehicles and started deploying our own cameras and starting working with wholesale of camera manufacturers and partners. We started building the AI technology, the sensor-fusion technology, all of it coming together. And, like I said, we started lighting up cities one by one. So, initially, we were focusing on Uber drivers in New York. Only there, and started building critical mass there. Then we moved to San Francisco and to Chicago and Las Vegas. Then we started going big across the U.S., and now we have users in over 1,000 cities, and we see over half of all roads in the U.S. every week.
Alejandro: In terms of the business model, how do you guys make money with Nexar?
Eran Shir: What we do is, all of these cameras that are on the road in vehicles that are on the road are capturing a lot of data. We’re basically crawling the public space like Google crawls the web. I think other than Tesla, we have the most amount of video and sensor data from the road. We turn all of this data into maps and insights and data services that are quite useful for people. They’re useful for cities to better manage themselves. They’re useful for mapping services companies, for ride-sharing companies, and mobility companies. If you can detect every street sign and street light, and you can detect road constructions, and you can detect parking spots, and all this kind of stuff, and turn that real-time into actionable data, then there are quite a few potential partners and customers that will be interested in that. That’s the bulk of what we do. We work with municipalities, with states; some of our customers are organizations like the city of LA, Las Vegas, Ohio, different states and cities in the U.S., but also private companies that have to map continuously, have to route their vehicles continuously, companies that deal with mobility and are interested in what’s going on, and insurance companies. Insurance companies are a major set of partners and customers because we can turn a collision from a he-said, she-said situation into a total recall kind of experience. Like, we have these tools to really turn that into a two-minute situation.
Alejandro: How much have you raised for the business because it sounds capital-intensive.
Eran Shir: It is quite capital intensive. That’s true. We raised just about 100 million dollars to date over this past five years. We try to be frugal. We try to be as frugal as we can, but there is a lot of work. If you’re trying to do things at this scale, it does require some significant investment both in technology and IT and in operations.
Alejandro: In terms of the employees, how many employees do you guys have to date?
Eran Shir: We have about 100 employees.
Alejandro: Are they distributed amongst the different regions, or are they all in Israel?
Eran Shir: Most of them are in Israel. Still, most of our employees are [42:30], both research and development. But we also have about something like 15 in the U.S., mainly in New York, and a few other markets.
Alejandro: Is there anything else that perhaps you can provide to give the folks that are listening an idea on how big Nexar is today?
Eran Shir: Sure. I can provide some cool stats. We collected video from over a billion miles of road, over 20 million half events, collisions, near-collisions, and pretty much any kind of thing you can imagine we’ve seen. We collect close to 100 million miles a month of a road. We see over half of the whole U.S. every week and 95% to 99% on the highways and the major cities in the U.S. every week. We see the world at least in the countries where we operate pretty frequently. I’d like next time you use Google Street; you don’t check from when those images are; you’ll probably see that it’s between six months and five years. Then go to an Excel Slide Map and see data anywhere between a few seconds ago to an hour or a few hours ago.
Alejandro: It seems that now there’s a lot of consciousness around driving and around safety. Now there are also a lot of self-driving cars that are starting to be seen out there on the road. Where do you think this space, and in this case, your space is heading as a whole?
Eran Shir: I think it’s going to take a while until any of us are going to use self-driving cars in a meaningful way. They’re going to be focused on specific geographic areas, geofence, in a sense for quite a while, still. The main reason for that is those 20 million events that I mentioned before, if you look at them, you’ll see that they are so varied, there is such a long tail of problems that we need to solve on the road. It’s really not driven. That will take us time. But what we can already do, and what we’re trying to play role is how can we move the needle on safety and on coordination today and not wait for autonomous vehicles, but make an impact today. The way we’re doing that is through networking. What we’ve done at Nexal is we created a mapping of every little piece of road, every one-square meter of road, and we gave it an address. Think of it like an [46:10]. When a vehicle comes into a neighborhood, it can subscribe to all of those little pieces of road and see what’s new and what’s going on. All of a sudden, you can see beyond your line of sight. You can see what’s going on five cars ahead or around the corner or things like that. I think that the world is going more and more into that realm of collecting data and disseminating it in real-time. The other thing that I’m quite excited about is this notion of data as the new oil, which became a bit of a recurring theme in the last few years, but it has a lot of merit. What’s going on with the vehicles is that they’re quickly turning from a car with all kinds of chips embedded into a computer with wheels. The ones that pioneered it are Tesla. From an architecture perspective, they were years ahead of the vision, but all the OEMs are going in that direction. The biggest question for them is, how do I actually monetize all of this data? How do I turn it into a business, and how do I do that at scale – because they are only working at scale. That’s where I’m very excited because if you take a [48:00] fleet, like thousands and millions of vehicles deployed, they are custom to thinking about the compute and the connectivity and all these things as a cost center, something that costs them money and that they have to do in order to get telemetry data and in order to manage it. All of the sudden, now you can turn it into a revenue center and into something that actually makes one. Think, for example, on the problem of parking. Wouldn’t it be lovely to know about every available open parking spot on the street of Paris, Milan, or New York? Every vehicle sees those parking spots. There’s just not an orchestrated way of coordinating and collecting all this data and then sending it back to the driver. These things are now popping up, and I think there’s a lot of excitement around it.
Alejandro: Very cool. Very cool. For the folks that are listening, this is a question I typically ask the guests that come on the show, and that is, knowing what you know not, Eran – it’s amazing that you’re now on your third company. Obviously, this one is the most meaningful one to date, and it’s incredible what you guys are up to. If you had that opportunity to go back in time and have a chat with your younger self, with that younger Eran that is about to launch a business, what would be that one piece of business advice that you would give to yourself given what you know now? What would that be?
Eran Shir: I think for me it is, go and study as much as you can, mental models. I think the most important superpower that you can build as a young entrepreneur is to learn your mental models well because they are, for me at least, the most important tool in my tool chest to understanding new situations. By definition, startups are all about new situations. They are all about exploring the unexplored. When you do that, you need some tools that allow you to find patterns, to set new situations in old frameworks. This is one of the things that people don’t study enough in their early days. The reasons, lack of mental model courses in high school, and that’s sad in my view, so I would go and invest the time, go read your [51:11], read about mental models, read about biases. I think all of these tools are very important.
Alejandro: Very profound, Eran. For the people that are listening, what is the best way for them to reach out and say hi?
Eran Shir: I’m quite accessible on Twitter, @eranshir. I’m also available on my email: [email protected] is a good place to go. I have a TikTok account, but I never should say it, unfortunately. It’s just lurking there. I would go with Twitter and email.
Alejandro: You got me all excited, Eran, with those videos of you dancing. I’m guessing we’ll have to wait for those. Eran, thank you so much for being on the DealMakers show today.
Eran Shir: Thank you.
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