Jul 8, 2020 | 6 min read

Conversation with Evangelos Simoudis

Podcast #99: Transportation Transformation


Evangelos Simoudis is a recognized expert on next-generation mobility, artificial intelligence, big data and corporate innovation. He is a Silicon Valley based venture investor, senior advisor to global corporations and governments, entrepreneur, corporate executive, technologist and author. He is Co-Founder and Managing Director of Synapse Partners, a firm that invests in early-stage startups developing enterprise software AI applications,  and  advises global corporations on AI. Evangelos is the author of The Big Data Opportunity in Our Driverless Future and the recently  published Transportation Transformation.


In our conversation, Evangelos walks through his professional journey outlining the common thread of big data and artificial intelligence (AI). He shares the motivation behind the founding of Synapse Partners as well as his unique investment thesis on enterprise AI applications. Evangelos discusses his latest book “Transportation Transformation” and the variety of new challenges that next-generation mobility brings as well as the future of transportation in The Great Reset.


This episode is essential listening for investors, manufacturers or entrepreneurs interested in the future of mobility and AI. Evangelos’ robust knowledge provides for a fascinating conversation of both the past and the future. 



American Nations by Colin Woodward 

Capital by Thomas Piketti

Homo Deus by Yuval Noel Harari 

The Master Algorithm by Pedro Domingos 



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View Transcript

Good day and welcome to episode 99 of our digital leadership podcast, produced for and by industrial practitioners. Today it’s my great pleasure to introduce Evangelos Simoudis.

Evangelos is a recognized expert on next generation mobility, artificial intelligence, big data, and corporate innovation. He has been working in Silicon Valley for 30 years as a venture investor, senior adviser to global corporates and governments, entrepreneur, corporate executive, and technologist. He’s co-founder and managing director of Synapse Partners, a firm that invested in early stage startups developing enterprise software, and AI applications, and he advises global corporations on AI.

Evangelos is the author of ‘The Big Data Opportunity in our Driverless Future’, and the recently published ‘Transportation – Transformation’. Evangelos is a member of the advisory boards for Caltech, Brandeis International School of Business, the US Department of Transportations Connected Cities for Smart Mobility Centre and securing America’s future energy. He earned a PhD in Computer Science from Brandeis University in a BS Bachelor of Science in Electrical Engineering from Caltech.

Evangelos, welcome to our digital leadership podcast series.

Ken, thank you very much for the invitation, it’s great to be here.

And it’s great to have you. As I recall, you and I first met – I want to say it was 2002 in New York City, when you were working for APAX Partners, so it has been long overdue to feature you on our podcast. I have to give a special callout to Ohad Zeira, who mentioned your book in our podcase 97 just two weeks ago, which prompted this interview. So, either way it was good timing to finally have you featured on this.

Thank you again. Thank you.

So, let’s start with your professional journey, tell us a bit about your background and how it has informed your views of what we call digital industry.

I came from Greece over 40 years ago to study here in the United States, and I would say I was lucky enough to start getting involved with artificial intelligence in 1982, and by ’85 we had the previous AI spring, so I was in the midst of it. I came to Silicon Valley in 1990, spent the first 10 years as an entrepreneur and corporate executive, I started two companies which I ended up building and selling. Then for the past 20 years I’ve been a venture investor as you said, initially with APAX Partners, and later with Trident Capital, and more recently with my own firm Synapse Partners.

The common thread on this journey has been the work on data, and what we now call big data, and the use of artificial intelligence and other techniques to exploit that data. So, whether it was as a technologist, as an entrepreneur, as an executive, or as an investor, data and data exploitation, data management, has been guiding me through.

It was interesting, as I was looking at your investment history, as an investor ourselves the first thing we usually do it pull up Pitchbook and look at the history of any individual in the organizations, and you have really a long and impressive track record of investments and exits. I’ve counted a couple here, Composite Software which was acquired by Cisco. I actually got a chance to work with Jim Green for quite a while at Cisco and really came to appreciate – he’s a brilliant individual as well, but Confluence Software acquired by Oracle, Exalate acquired by Nielsen, and the more recently Understand.AI, X15 software and Wagon Analytics. To what do you attribute your ability to consistently back such winners?

You’re very kind first of all in your characterization. So again, all of these companies had some influence were data-related, and my investment style has always been thesis driven, has always been data driven. So, not only do my team and I strive to understand a particular company that may be an investment candidate, but also its competitors and the overall ecosystem which such companies will work in.

We’ve always strived to understand the industry, and particularly with Synapse this has become much more important in our work, both myself and my teams have always worked, we have close relationships with corporations that could be users of the technologies that we were funding. Then because in many of these cases the companies who were investing in early stage; you mentioned Composite, you mentioned Confluent, you mentioned companies like Understand.AI and X15, the teams were particularly important. So, we wanted to see people who had the drive to succeed, who know that they would need to work through thick and thin as they say, and that success is not a straight line.

So, we wanted to make sure that they had that drive, and of course that they could bring together strong teams, but also they would accept our help in building those strong teams. Because as we were seeing even in these days, because of the pandemic and the troubles that many startups are going through, the ones that are able to move forward albeit slower are the ones who have the strong teams. So, that has always been, data, strong teams, understanding of the space very deeply through the use of data, have been the tenants of our investment work.

Yeah, we have very similar thesis orientation and very similar criteria in that regard, and so the deep understanding of the industry, you need that DNA, and you need to see that in the founders. But the difference between certainly a startup that is going to succeed comes down to always the team, and the ability of the team to operate as you say through thick and thin.

Tell me a bit about what inspired you to found Synapse Partners, and maybe go a little deeper in your unique investment thesis, because I find it pretty relevant.

So, after 15 years of working at APAX and Trident, and given what was happening particularly here in Silicon Valley around 2014-2015 timeframe, first of all I started thinking that the world did not need yet another early stage venture investor. So, when my partner Matt and I started thinking about what we wanted to do next, how we wanted to work together, what we felt was that in order to go deep into a topic and take advantage of an opportunity, you need to understand it from various perspectives, and just being a venture investor doesn’t allow you to do that. Venture investors for the most part tend to be a mile wide and an inch deep.

We decided to focus on enterprise AI applications because we felt that AI in its multiple incarnations, and I should say that AI is not only machine learning, even though this time around data driven machine learning plays a much more important role than it did back in the eighties, when we had the previous AI spring. So, we felt that AI would be very transformative, very much along the lines of what the software as a service model has been for enterprise software, so, we thought it would have a long runway.

The second aspect, or the second tenant of our work has been that again every good we see has a strong rolodex, has a strong network of contacts in the industries where they like to invest. We felt that this is not enough in this time, so we set off to start developing what today we’d call corporate partner network, corporations from three industries, automotive and by extension transportation, financial services, and Telco. The companies that have joined or want to join our corporate partner network we commit that we will spend a significant amount of time with them, with senior executives in their corporation. So, by and large on the average we spend one day per month with each of these corporate partners. That as I said for a traditional venture investor that’s unheard of. In fact, when we started to LPs, we found that they were very skeptical about our approach.

So, the commitment that we’re asking our corporate partners to make is that they will give us access to three individuals to begin with, one of three or sometimes two, or a subset of those three. The CEO, the Chief Strategy Officer, and the Chief Digital Officer, because we think that these three individuals in the right companies – and again we have to do a lot of filtering of who we are going to accept as a corporate partner in our network, we feel these individuals both have or should have a particular vision on what are strategic problems that the corporation need to address, as well as what would be the horizon for solving these problems.

What we try to work with them on is to try to see how startups can help in addressing this problem. So, in the course of these interactions what we end up doing a lot of times is educating these executives that we work with, about which problems could be solved by startups, and by extension being good ideas to venture-backed, and which problems will require different solutions, for example developing an internal team, or going to a management consulting organization to help them to solve the problem.

So, there is a lot of work that is going on, and a lot of advisory that is going on, and education that is going on, and we feel in the process there is this constant value exchange between us as Synapse, our start-up portfolio companies, and our corporate partners. So, we have established how this flywheel, or these mega-networks if you will that creates value for each of its members.

Then the third tenant or founding of creating Synapse was that we wanted to do more than ever, data-driven investing. So, when I started doing data-driven early stage investing bank in APAX days, 2000-2001, there wasn’t a lot of data available about start-ups, so now there’s a lot more data available, there are companies that are collecting such data religiously, if you will. So, we started building a database where we track thousands, in this case of early stage software companies that develop AI applications, and we track their personnel, their founding teams, their investors, so there is a lot of data that we make available. And because of that, because of this emphasis, Synapse has three types of people.

On staff we have obviously investment professionals, we have business analysts who are working with our corporate partners, then we have software engineers and data-scientists that are working not only as I’ve said in building, maintaining, and expanding, and analyzing the database, but also a lot of times helping our corporate partners in our startups to take advantage of certain technologies.

So, it’s a much more complex undertaking but so far after about four years doing it, both because of the exits that we have seen to date, but also because of the very positive feedback that we are receiving from both portfolio companies and corporate partners, we think we’re on the right track and building something very differentiated.

Yeah, I’d say your track record speaks for itself in that regard, and the model of data managed, the analytics, the networks themselves, the corporate affiliation, and I’d say very diverse team, makes a lot of sense. We have a similar pattern at Momenta but obviously with a different thesis on it as well, I can tell you, it does work well having all of those pieces together. So, beautifully done.

Let’s talk a bit about your other passions. Sometimes I think this area of the future of mobility feels a little orthogonal, but I think the name of your first book, ‘The Big Data Opportunity in our Driverless Future’, really ties together well what you said a few minutes ago, about automotive industry and certainly Enterprise AI. You published that book in 2017, what were some of the key themes you observed in that book at the time?

So, at that time I wanted to bring forward three points…

First and foremost, that data is going to be very important in next generation mobility. It’s going to be important not only in making vehicles move autonomously, or semi-autonomously, but it’s going to be important for every other aspect of mobility; understanding the environment in the vehicle’s cabin, and understanding the passengers, or behaviour, or how goods are being transported.

The second aspect, I wanted to start teasing apart this notion of driverless mobility. So, driverless mobility particularly back in 2017 everybody was associating it with autonomous vehicles, and autonomous vehicles in fact are very a very important component of that. But driverless mobility is also about mobility services, in other words it’s about all of the modalities that we can use, and the technologies that we can use, so that I as a consumer or as the shipper of goods does not have to physically drive the vehicle.

The final point that the book tried to bring out was that OEMs, automakers, were not particularly ready for tackling the opportunities that data and AI were providing to them in the context of next generation mobility. They were not ready culturally, but more importantly they were not ready from an innovation model perspective, in terms of how they collaborated with start-ups, how they utilize what start-ups had to offer, both in terms of technologies but also in terms of practices.

I remember right after the book came out, we had a number of conversations with some of our OEMs, automaker corporate partners, on how to take advantage of the opportunities and change some of the behaviors, bring the right people on board, create the right organizational structures.

If I were to make a bridge between what I wrote in 2017 and what I’ve just published, with a new book I feel that the set of problems, these three constituencies that I identified, namely, automakers, mobility services companies, and more recently cities, the set of problems becomes even larger. So, the automakers not only have to deal with the data and AI aspect, which was the point of the first book, but they have to deal with a variety of other challenges that new mobility brings forward.

Yeah, you beat me to the punch on that one. I was going to ask what the inspiration for the last book was, what did you see into this.

Perhaps taking a slightly different angle on this as we’re recording this, I know Evangelos, you’re in California, they’re going back into lockdown, I’m in Switzerland and our borders are open, but either way COVID-19 has created a real impact if you will. The World Economic Forum actually uses the term, ‘The Great Reset’, when referring to this impact. What do you see as the impact of this reset, on the future of transportation?

We had already been talking before this became a pandemic, about the future of work, the future of urbanization, these are two mega trends if you will that definitely impact transportation. I think what the pandemic has brought forward is more of that thinking, in other words, I wrote a piece in my blog, I call it, ‘From 30 Miles to 30 Steps’, and it was a play on words because of the fact that since late February we’ve been sequestered here, and we’ve been working from home, and that is causing corporations to think a lot about telecommuting, and how to deal with a work environment we have. We work with corporations in Asia, they’re establishing certain practices. We work with corporations in Europe, they’re looking at it in a slightly different way. So, the future of work, and the future of urbanization are going to play a big role here.

That is going to cause I think cities to rethink how they approach certain parts of their lives. So, if we’re starting to see move away from the center of cities, so the deurbanization movement, then city designs will have to be impacted. Right now, around the world and in particularly here in the US, the public transportation systems are starting to suffer, because people do not want to get into a public transportation modality unless they absolutely have to. That means that the revenues from the other cities derive from public transportation are decreasing significantly, as people do not drive because they work from home, parking fees are down, fees relating to traffic infractions are down, so traffic tickets are down. So, because of that, cities will need to rethink how they allocate the resources, what part of the transportation infrastructure they start to charge for.

Then going further along, we’re starting to see a significant increase in e-commerce, as people buy more over the internet and they have it delivered to their place of choice, whether it’s residence or some other place. I think this practice is starting now to get ingrained into people’s daily existence, daily life, and I think that will have an impact on transportation.

I think finally what COVID has allowed us to do, even if it is in a spotty way, they allowed us to understand the impact that we’re having on the environment, because as traffic reduced around the world we saw how the pollution changed, whether it is environmental pollution, noise pollution and all of that. So, that is causing citizens to rethink about what they expect from the players that are working on transportation, whether it is the automakers that are producing the vehicles, whether it is the cities that provide public transportation, or the mobility services companies that provide services using either their own vehicles, or other people’s vehicles.

I should finally say, obviously we see an increase in privately owned vehicles, we will have to see whether this is temporary. Obviously, people who can afford to either buy a new vehicle, or they already have vehicles, they’re starting to use them more because they’re trying to avoid public transportation. We’ll have to see whether this is going to be short-lived, as I hope it will be frankly, or not, because if it’s not short-lived, again I think that will create very different kinds of strains into our transportation infrastructures, and into the problems that cities have to contend with.

I love the tile, ’30 Miles to 30 Steps’, it does describe well the challenges if you will, or let’s say the focus. Let’s go back to your point between your two books again, both of them talked quite a bit about the auto industry, and OEMs particularly. There’s been a lot of discussion about the Elon effect,  in some sense how radically different and often disruptive approach could impact business, such as electrical, automobiles, transportation, think tunnels, and space flight, do you think this effect continues to be needed to support the future of transportation? Or, have the traditional players, the incumbents, the OEMs, the automobile manufacturers in the space finally caught up now?

In the new book, ‘Transportation Transformation’, I talk a lot about how these three constituencies, OEMs, Automakers, mobility services companies that provide hailing or micro-mobility and those type of services, as well as cities, will need to first transform and then once they transform they need to start collaborating very intensely, and over a long period, if we are to achieve what’s possible with next generation mobility. I wrote a couple of chapters actually on what incumbent automakers will have to do in terms of these transformations, but also how they will be stratified, because I don’t think that everybody will be able to achieve the same position.

If you were to look at what you call the Elon effect, or Tesla effect, I think that there are essentially four big categories in my mind that Tesla has been teaching the industry.

  1. The technology. So, the Tesla vehicles are high-tech vehicles, and the incumbents have been focusing on the over the air updates. So, if you look at where a lot of emphasis has been placed more recently, it’s in more of the incumbent automakers having the ability to update the vehicle software over the air. Or seeing some emphasis on providing certain levels of automated driving, so your listeners may have heard the terms, Level 2, Level 2+, Level 2++, Level 3… these are all levels of driving automation that are below the fully autonomous capability that we were seeing with vehicles such as Wemo or even GMs Cruise and a few others. So, there’s the technology aspect.


  1. The second aspect which I think is very important that Tesla brought forward, was the business model aspect. You’re able to go get a vehicle without having to go through a dealer, and that’s an important step, and I think in the United States and in the European Union, it will be very difficult for me, not impossible, in the foreseeable future to see how that can be replicated.


  1. The next aspect, which is related actually to the business model, is that of personalization. As a Tesla prospective buyer I can go and customize how I want my car to look, to be equipped with, and even when I take possession of that vehicle I can personalize it in different and more intensive ways than I can with any other vehicle that’s coming from incumbent automakers.


  1. Finally, again building one on top of the other, because of what I mentioned before, I think Tesla has been able to successfully break the development cycle. So, today we have essentially three or four different development cycles that are going on in the vehicle, we have the development cycle of the chassis, of the cabin, of the electronics of the vehicle, these are all different development cycles. So far, incumbent OEMs have been following this very regimented cycle that is a major update every 7 years, and a minor update every 3 years. Well, guess what? By the time that you take possession of your vehicle, most of the electronics are already outdated.

In order to be able to keep up with what’s going on in the software space, in the consumer electronic space, you really need to break apart that cycle. I talk about that in the new book, and the fact that you really need to think about maybe if your software cycle becomes very much like we see in consumer software, and enterprise software, maybe becomes a 6-month update, or a 12-month update. Whereas your chassis maybe it’s a 12-year update, it’s very different because little maybe changing the chassis level of the so-called skateboard level now with electric vehicles, compared to what is changing in the electronics. Then in the case of electric vehicles, you have advances in the battery technology, so that again may have a different update cycle.

So, to summarize, Tesla’s innovations as a company who go beyond just technology. Technology enables many of them, but it’s not only the technology in the vehicle, and I think that even if some OEMs, incumbent OEMs are able to come close to providing similar technology capabilities as we see today in Tesla vehicles, I think there are other aspects of Tesla’s innovations that will be both harder to achieve by incumbent automakers, but certainly will take a lot longer.

It sounds like a great book to read, it certainly is going to be on my reading list, ‘Transportation Transformation’, love the title as well.

So, in closing as digital industry investors and knowing that we have very-very similar thesis, we always like to ask your recommendations on interesting start-ups. Whom might you plug as the ones to watch in your area?

Every investor thinks that their children are the best looking, and above average, as the radio program used to say! So in terms of our own portfolio, and again based on everything, on this discussion that we’ve been having today, I like to point on the automotive side, Divergent 3D and Renovo.Auto are two companies that we’ve been investors, we’ve been fortunate enough to be investors from the beginning, and we invested early-on as we were starting Synapse, and great teams, great innovations in the companies, and the market is rewarding them.

A more recent investment, again outside the automotive space, we’ve invested in an Israeli company called Namogoo, that is doing particularly important work, again in the intersection of ecommerce in security.

Datatron, that is dealing with the aspect of how I take the product of a data scientist, that model that he has tested and validated, and push it out to production, and in the process govern its execution. That’s a problem that we’ve been spending so much time as a community on helping the data scientist and providing better tools for the data scientist, that we in Synapse felt that we have ignored what happens once that model is ready, and now needs to be pushed out to production. Because there’s a lot of work that needs to be done there, in order to have the consistency of performance, both performance in terms of computational performance, but also decision-making performance. So, we feel that Datatron is making very important steps in that area.

Great, four great recommendations then. In closing, can you provide any recommendations of books and/or resources that inspire you beyond the two that you wrote!

I tend to read very broadly. Somebody asked me the other day, how do we stay updated on the developments on the new mobility space, and I say my research team and I have been reading through a lot of blogs, a lot of technical papers and industry papers. But again, for me as I try to create these perspectives to help both our start-ups, our corporate partners, and obviously the readers of my books and other writing, I tend to look around more broadly. So, off the top of my mind I have four recommendations.

The first book that comes to mind is a book by Colin Woodward, ‘American Nations’, which I found particularly poignant given what’s happening in this country these days, and for me on this 40-year journey it was particularly a revelatory book.

We talked earlier about the future of work, the future of urbanization, so I thought Thomas Piketty Capital is also a great inspiration, I don’t agree with everything he says, but very much like several years ago, Kissinger’s on China, it gets you to think about new systems and new approaches, which I think we need these days.

In terms of AI, again very much as was happening in the eighties, we see a lot of publicity now in AI, a lot of books out and articles, but I found that Harari’s ‘Homo Deus’ and Domingos’ ‘The Master Algorithm’, I tend to recommend these two books, because I think they’re particularly well-written. And even though they’ve been out now for a few years, they remain very relevant to the opportunities, but also the challenges that we are facing around this technology. And again, it goes back to the point I said about future of work, future of work is not only about whether we will be working from home or not, or telecommuting, but also there is this race about what and how much we automate.

I think there would be some interesting evolutions, interesting developments that we will see over the next few years. The pandemic may provide the fuel, or the spark maybe, but I think that we have some very important issues to think about work, pandemic or no pandemic, and a lot of them are around both how we want to live, but also around automation and the opportunities that AI provides us.

Thank you so much. So, this has been Evangelos Simoudis, Managing Director of Synapse Partners, entrepreneur, investor, author, and digital thought leader. Evangelos, thank you for a fascinating interview.

Thank you very much again for having me.

Absolutely. And to our listening audience thank you, and please join us next week for the long-expected episode 100 of our digital industry leadership podcast series.

Thank you and have a great day.