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The family of Wan Li Zhu emigrated to America seeking new opportunities. Wan Li benefited from high-quality public education at Bronx High School of Science and went on to a perfect grade-point average at MIT. He studied under renowned quant wiz Andrew Lo and was poised for a career on Wall Street but was lured away by the prospect of hands-on responsibility for product features at Microsoft. After a prodigiously successful stint, during which he was involved in building and marketing Dynamics CRM, Microsoft’s fastest-growing product, he went to Harvard Business School. From HBS he was recruited by early-stage VC firm Fairhaven Capital.
The firm, known for its expertise in web security and digital advertising, now sees promise in various applications of artificial intelligence starting with self-driving technology. Wan Li is deeply engaged in bringing on the next generation of winning investments at Fairhaven Capital. Despite a busy professional life, Wan Li Zhu has found time to advise startups and to co-found MIT Angels in Boston. I learned a ton from my conversation with this wise, yet unassuming early-stage VC and angel.
Click here to read full transcript of the episode.
Here is a list of the topics covered:
Studied with MIT Professor Andrew Lo – Used Natural Language Processing to Assess Market Sentiment
Why Wan Li Zhu Went to Microsoft – Three Years at MS – Shipped Three Versions of the Product
Wan Li Zhu Connects with Fairhaven Capital through HBS Resume Book
Fairhaven Capital Is Thesis-driven – Attentive to Market Trends that Could Create Large Opportunities
How the Fairhaven Capital Portfolio Is Doing
What Wan Li Zhu Looks for in a Startup Investment
Experienced Founders Can Actually Time Markets
TVision Came Via MIT Angels – Measuring Engagement of TV Viewers
AirFox – Enabling Wireless Carriers to Offer More Affordable Data Plans
MIT Angels Company PathAI’s Deep Learning System Is Better at Detecting Tumor Cells than Human Pathologists
Latch – Enterprise-grade Keyless Access System for Apartment Buildings
The Investment Wan Li Zhu Regrets Not Making
Wise VC Wan Li Zhu Continues to Be Very Bullish on AI
Transcript of "VC Wisdom"
Guest: Wan Li Zhu, Venture Capitalist and Angel Investor
SAL DAHER: Wan Li Zhu is a thoughtful venture capitalist. He’s also an angel investor. That’s an unusual combination. You see, venture capitalists invest other people’s money; they tend to invest later. Angel investors invest earlier – invest their own money. This gives Wan Li Zhu a perspective on two universes; the universe of angel investing and the universe of venture capital. He is also the lead for MIT Angels; the angel group for MIT-affiliated companies. So he has, really, excellent perspective. You have this brilliant guy; perfect GPA at MIT’s hardest major; unbelievably off the charts. Really accessible, looking hard to understand how to best build companies in this intersection between the angel universe and the venture universe. I treasure this interview with Wan Li and I highly recommend the relaunch that I’m doing today.
SAL DAHER: Welcome to Angel Invest Boston, conversations with Boston’s most interesting angel investors and founders. I am Sal Daher and my goal for this podcast is to learn more about building successful new companies. The best way I can think of doing this is by talking to people who are doing it, people such as venture capitalists and angel investor, Wan Li Zhu. Wan Li, I’m honored you could join us. Welcome.
WAN LI ZHU: Thanks for having me, Sal.
Sal Daher: Tremendous. In preparing for this interview, I looked at Wan Li’s LinkedIn profile and was overwhelmed, really overwhelmed. The combination of academic prowess with real world business smarts just took my breath away. Wan Li is a principal at Fairhaven Capital, the venture firm. He’s a founder of MIT Angels in Boston and is involved in countless other volunteer activities that help build the startup ecosystem. His investing focuses on enterprise software, AI enabled systems, cyber security and consumer platforms including the internet of things and virtual and augmented reality.
Wan Li has worked in Wall Street and in Microsoft. His academic work involved applying AI, artificial intelligence, to understand the connection between the emotional content of articles and the behavior of financial markets. This is work he did with the renowned professor, Andrew Lo, at MIT. Wan Li was also involved in product development at Microsoft taking a key role in making Dynamics CRM the fastest growing product in Microsoft history. He’s a graduate of MIT and Harvard Business School. Now, Wan Li, please tell us your story before MIT and the perfect GPA, et cetera, the grade point average. Where did you grow up? What did your parents do? What’s the story here?
Wan Li Zhu: I grew up in China and grew up there until I was 10 and came to the U.S. with my parents. My dad was an English translator at Polaroid when we were in China and my mother was a high school teacher. She taught physics and she also taught accounting. I grew up in a family that really emphasized education and China was a great place to be trained and disciplined, maybe not so much in creativity.
It was tough for them when we first came. They really had to start over like many other first generation immigrants. We settled in the Bronx and I was very fortunate to be admitted to the Bronx High School of Science. That was a real turning point for me. I hope that this kind of model can be more prevalent in the U.S., this high quality public education that is freely available to everyone. I remember testing just at the lowest possible score needed to get in because I spoke very little English but I scored okay on the math, so I made the bare minimum cut off and entered the Bronx High School of Science.
It was just an incredible environment, incredible school. There are more Nobel Prize winners that are produced by Bronx Science than by any other high school in the world. Bronx Science counts … I think it was eight Nobel Prize winners, I believe, seven in physics, one in chemistry. It was an environment that really encouraged students to excel in math, science. Computer science was also popular at the school and that was the first time I got exposed to computer programming and to after school activities that involved technology. It was because of Bronx Science that then led me to have a chance of getting into a place like MIT.
Sal Daher: Doing extremely well at MIT. Very, very impressive. Amazing. Please tell us about the work you did with Andrew Lo. You could have been a quant on Wall Street. Why did you not choose that path?
Studied with MIT Professor Andrew Lo – Used Natural Language Processing to Assess Market Sentiment
Wan Li Zhu: I still think about that actually. One of my biggest regrets is not pursuing additional graduate studies with Andrew. He and I still speak regularly. He’s a good mentor to me. He actually wrote my business school application recommendation. I think that’s one of the main reasons why I got into HBS. I worked with Andrew for about a year. I did a master’s degree thesis with him and studied how financial news was related to market movements and with this all by using natural language processing to extract sentiment data on news that are applicable to the broader market.
We looked at Wall Street journal and we had a couple of interesting findings. One finding was that news that’s negative tend to affect markets more than news that are positive. I guess it makes sense. We also found that news tend to be better correlated with market volatility than it is with market direction. The third finding, which perhaps is also not surprising, was oftentimes, we found that the news predicted market less well than market predicted the news. It’s some proof that information’s sometimes already baked into the market in advance of it being released in mainstream news.
Sal Daher: How did you end up at product management at Microsoft? You were very much software guy, quant, so how did you move over to the more human side of that activity?
Why Wan Li Zhu Went to Microsoft – Three Years at MS – Shipped Three Versions of the Product
Wan Li Zhu: It was interesting coming out of MIT that there were a couple of employers back then, this was 2004, that recruited very heavily. They were on campus all the time. I think it also influenced the way the students viewed their career options. I remember the biggest employer at the time was Goldman Sachs and then followed by, I think it was either IBM or Microsoft. The options that were present to the students were coming out of specialty engineer programs like computer science was either to go to Wall Street or go to a large technology company.
I asked myself, what do I feel passionate about, what are some of the things that I wanted to do and learn and coming out of school to be my first job, I want a lot of responsibilities. Microsoft, there was a unique opportunity there at the time for me to join a V1 business that was very new. It was the Dynamics CRM business. It was created by executives to go after Salesforce and Oracle Siebel to compete directly with them in the CRM space. That was post Microsoft acquisition of Navision and Axapta which are ERP software divisions that was doing very well at the time but they wanted to create CRM from the ground up. It’s a unique opportunity for me, coming out of college, to own a large feature area in a product, run a team and learn how to run a business actually. That was what drew me to that path.
Sal Daher: Excellent. You spent seven years at Microsoft and then you went to business school?
Wan Li Zhu: I spent three years there and within the three years, we shipped three versions of the product.
Sal Daher: Wow.
Wan Li Zhu: It’s a pretty accelerated experience. I actually spent two of the three years in product development and then, another year in product marketing all within the same business. As the technology became mature and the product became mature, there was more need on the business side to build a sales channel and to create competitive positioning against other more established CRM players and of course, to also create market presence and to deal with analysts and PR. It was a great opportunity for me as an engineer to learn the business side. I jumped on that and moved to the business side for the last year of my three-year stint.
Sal Daher: You were at Harvard Business School before or after Microsoft?
Wan Li Zhu: It was after. I left Microsoft and I was based in Seattle and moved back to Boston for Harvard Business School.
Sal Daher: Interesting. You went in as an engineer and then you came out as a business product manager because of the natural progression of the product that you were in charge of because it grew so much and you had to take on additional responsibilities. Just a wonderful way to do it.
Wan Li Zhu: That’s right. It was a unique timing and the evolution of that business as well for me to be able to do all these different things.
Sal Daher: Right brain meets the right market at the right time. Good things ensue.
Wan Li Zhu: It was fantastic training.
Sal Daher: How did you connect with Fairhaven Capital? Were you purposely thinking of becoming a venture capitalist?
Wan Li Zhu Connects with Fairhaven Capital through HBS Resume Book
Wan Li Zhu: I was not. I graduated HBS in 2009. It was an interesting time to graduate because the markets were not doing well. I was fortunate to land an offer from Google where I had spent some time between first and second year in business school, so I was contemplating going there. They had given me an offer out of their Asia presence, so I would be moving to China actually to work for Google China. I also had an offer from Amazon as well, so I was considering going to work for a tech company. Over the summer, I got a phone call from one of the partners at Fairhaven who actually saw my resume from HBS resume book. I decided to speak with them and we really hit it off. The partners at Fairhaven gave me a chance and were willing to accept me even though I have no investment background. They’re willing to train me and now, it’s been over seven years and a great ride.
Sal Daher: Really amazing story. I think if I were looking at your resume, I’d see someone who’s done the fintech stuff and then you progressed from engineering to product development, that, to me, tells me that you have extremely versatile mind and you're capable to adjust. That’s really interesting to see. Tell me a bit about Fairhaven’s approach to investing and how it sets itself apart from other early stage VC firms.
Fairhaven Capital Is Thesis-driven – Attentive to Market Trends that Could Create Large Opportunities
Wan Li Zhu: Sure. Fairhaven is a thesis-driven firm. We look at markets, market timing, market dynamics and understand areas where big companies can be built because of some fundamental shift in market trends. Because of that thesis focus, we’ve picked out a couple markets where we’ve concentrated our bets. One was being in Fund One, in the mobile space and we looked at desktop, computer businesses that have achieved significant traction and success and we ask ourselves what kind of businesses can be replicated in the age of mobile. Based on that, we made bets in security, in digital advertising.
In digital advertising, for example, we bet on a very early stage company called Third Screen Media which was one of the first rich media mobile advertising companies. The thesis there was that the advertising model that worked on desktop will be replicated on mobile but in a different form factor because the screens are smaller. As the devices became capable of showing rich media ads, there should be a advertising platform created to take advantage of that opportunity. Third Screen Media was the first company of that kind to come to market and created market leadership position and market presence and it was a successful exit in a short amount of time because it was the right market timing.
Similarly, we bet heavily in the security space over the last 10 years of the firm and we’ve invested across different parts of the security value chain from detection to prevention to incident responses, so forth, and we understood that, first of all, security is a evergreen market in some ways because the attackers are always one step ahead and so there’s always a need to invent new levels of protection and solutions.
The second is to realize that the attackers are always going to get in somehow. Even if they’re in and breached the perimeter of the organization or be able to get to the data, how do you invest and create solutions that will address and mitigate some of the attack and the damage that will be done. By protecting data itself, for example, or by creating solutions that allow you to respond to an attack after it has happened so you can alert the right set of customers and follow state regulatory mandates are all kind of areas where we made the successful bets in.
Sal Daher: Excellent. Would you be able to tell us a little bit about your VC portfolio to the extent that you can, the things that are succeeding, the things that need work?
How the Fairhaven Capital Portfolio Is Doing
Wan Li Zhu: Our security portfolio is doing very well and I think that that’s partly because we’ve studied the market for a long time and continued to make bets in an industry that where the need has increased and demand from customers for solutions has not gone down, so we feel really good about the security portfolio. We’ve also done quite well in digital marketing. After we bet on mobile, we turned focus to social media. Social media became a platform where a lot of consumer interest and traffic and engagement moved to. We bet on marketing solutions that recreated existing successful marketing models in the social media world.
Now that we’re entering a new wave, as artificial intelligence has proved to be more accurate and useful and we’ve shifted the focus to bet on more AI-enabled systems. Many investors realized this opportunity, so we’re not alone in seeing this. It’s based on that, we’ve made investments in everything from robotics, consumer robotics like Jibo, for example, to AI-enabled medical diagnostic systems like PathAI which actually came through MIT Alumni Angels.
Sal Daher: Excellent. Coming up next, I will ask Wan Li Zhu what he, as one of Boston’s most sagacious early stage investors, looks for in a startup. First, I wish to thank listener LRamateur for this review. “I listened to Michael Marks’ and Ralph Wagner’s interviews and found them fascinating. I learned more in one hour about the colleagues with whom I've been working and co-investing than I have in eight years I've known them.” Thanks, LRamateur.
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So Wan Li, with your angel hat on, what do you look for in a startup?
What Wan Li Zhu Looks for in a Startup Investment
Wan Li Zhu: Well, my angel hat is quite similar to my venture hat. What I look for in a startup are predominantly three things. One is, is it the right market and is it the right time in the market cycle to be starting a company in that space? The second is the quality of the team and their previous experience, hopefully in that domain that they’re looking to do something in. The third is whether the product or the solution is differentiated from existing competitors.
The reason why I put market first is that in a good market, it actually gives you some room to make mistakes. In a bad market condition, you have to execute perfectly in order to achieve a success. If you think about the factors that are within your control, the market is really predominant factor that’s not in your control and so if you pick the right market in the right time, it just makes things easier.
Experienced Founders Can Actually Time Markets
If you look at founders that have had repeat success … In fact there was a study done by HBS professor, Josh Lerner, who studied founder performance persistence and looked at repeat founders. He found that repeat founders tend to have a very consistent skill in being able to time the market. The way he did it is he looked at the relative success rates of the entire cohorts of companies that started at a certain period of time within certain markets and then looked at how these successful founders picked these markets. They tend to pick a market time where more companies are successful in that particular domain than in other periods of time. It’s really interesting to me that market timing is actually a skill. It’s actually a skill of successful founders.
Sal Daher: This is interesting because this runs quite contrary to evidence in public markets whereas you're well aware, market timing really doesn’t pay. Eugene Fama got his Nobel Prize on the basis of the work that she’s done proving that in public markets, market timing, the active[ly managed] mutual funds that he studied over 35 years and so forth, only three exceeded the cost of running the fund. You could not identify those three [percent] upfront. However, in the private markets, the highly illiquid markets, market timing by the founders in these highly inefficient markets does work which is quite revelatory.
Wan Li Zhu: It is fascinating. Private market is inefficient but also venture investing and angel investing and specifically, technology based investing. You're trying to invest in a technology trend so there is sometimes a risk of being too early too …
Sal Daher: Yes, definitely. Yep. I see that.
Wan Li Zhu: … which can be disastrous sometimes. Companies can’t run on a capital being too early. I think in a private market, there’s still a lot of opportunity to, as you said, to time the market and also to catch technology trends at a time where these trends change markets and open up new markets. Oftentimes, you see companies being successful capturing a relatively small market but that is growing very quickly. If they can be a dominant player in a small market that is enabled by a new technology trend, they can become a dominant player in a bigger market that is being grown by that technology.
Sal Daher: I guess in effect, the repeat founders are almost like insiders in a sense that they can read the market better. They’re not insiders in the ugly legal sense but they’re insiders in a sense that these are nascent markets, they’ve seen the model before and they can tell what point of the market they want to enter. They’re scanning the horizon of opportunities and they say, “This looks like something like my last startup. It was about this stage. This is something I can succeed at.” Perhaps, that’s the mechanism that’s allowing them to be so successful so that you can actually pick winners.
Wan Li Zhu: Yeah. Early pattern recognition is part of it and repeat founders that have been successful also have this aura around them. They have relationships too with existing investors and …
Sal Daher: … which makes it easier to raise money.
Wan Li Zhu: … which makes it easier for them to raise money and if they can continue to raise money, they can always have another shot at trying to find success of pivot their company.
TVision Came Via MIT Angels – Measuring Engagement of TV Viewers
Sal Daher: Wan Li, I understand you became involved with TVision through MIT Angels. Could you please tell the story about the company and your involvement?
Wan Li Zhu: Sure. TVision is a very exciting company. In fact, they were recently featured in the New York Times on the front page. The thesis for TVision is quite simple which is that these days, we talk a lot about digital advertising and digital marketing dollars which we just touched on here as well but it turns out, TV advertising is still a pretty big market. It’s about a little over $70 billion a year in the U.S. Digital’s actually about the same now, so digital has been catching up and growing very quickly but TV advertising actually continues to grow, so it’s not declining.
TVision’s thesis is that a lot of TV advertising dollars are wasted because it’s very difficult for an advertiser or a TV network to tell whether the TV audience is engaged, how many people in the room, are they actually watching the programming and if they are watching the programming, are they paying attention and not getting distracted? It’s very difficult. Right now, the state of the art is Nielsen and Nielsen’s measurement technology is not very accurate. TVision’s technology actually uses a new method. They use an Xbox Kinect camera attached to a computer and they’re able to, in real time, look at how many people in the room, what the demographics are, whether they’re put through eye tracking and sentiment analysis, whether they’re actually watching the program and paying attention to it and how they’re reacting.
Based on that, they’re able to show that certain TV shows that are rated very highly actually get less engagement than other shows that are rated less highly by Nielsen. Then, in other cases, they’re able to show that content, for example, from The Weather Channel actually gets a lot more engagement than people think. They call it kind of the lean forward engagement. TVision’s now in over 2,000 households. They actually pay the households for having the device in their home and the devices do not capture any actual images. They actually turn the data into vectors and into a mathematical representation which then gets sent up to a TVision cloud for analysis, so there’s no issue of capturing someone’s face or their actual picture.
What’s really fascinating to me and what’ll be a great opportunity here as well is that TVision’s technology applies to streaming content as well as live content because they take an audio fingerprint of the show that’s being played in a living room so it doesn’t matter if it’s playing live on the cable channel network or a TV network or it’s being streamed from a Netflix, Hulu or Amazon. TVision can still detect that, figure out what show it is and then monitor the user engagement to the show.
Sal Daher: It recognizes it from the soundtrack?
Wan Li Zhu: From the sound. Correct.
Sal Daher: Yeah, okay. You’re involved with them as VC or as an angel, just as an angel?
Wan Li Zhu: I’m involved with them from the Fairhaven perspective. Of course, the deal came through MIT Angels. That’s when we first saw them and the MIT Alumni Angel network has been really a great deal sourcing channel for me as a venture investor, to be able to meet this company and to really help them and make an impression and show that I can add value and then later on, make an investment from a firm perspective. I’m very fortunate to be involved with TVision in their latest round which is a series A round and there are great things ahead for the company.
AirFox – Enabling Wireless Carriers to Offer More Affordable Data Plans
Sal Daher: Tremendous. I see that you're an adviser to AirFox. Can you please tell us a bit about them? They’re on my regret list. When you connected me with them, I was regrettably just too busy to give them the attention they deserved. What did I miss?
Wan Li Zhu: Well, they’re going to raise more money so you didn't miss it.
Sal Daher: Okay. I’ll keep my checkbook open. Okay.
Wan Li Zhu: I've known Sara Choi who’s a co-founder of AirFox for a long time. I actually met her when I was still at Harvard Business School and she was finishing up a Harvard undergrad. Sometimes, venture investing and angel investing is really about relationships that you've had with founding teams for a long time. After Harvard undergrad, Sara went onto join Google and she had a very successful career there as a media lead for YouTube. It was there that she met her co-founder to start AirFox. They were based on the West Coast, in fact, and they were about to raise money on the West Coast and I had introduced them at the time to Semyon who-
Sal Daher: Semyon Dukach, yeah.
Wan Li Zhu: Yeah. Semyon Dukach running Techstars Boston and told Sara to consider …
Sal Daher: One moment. I just want to … Semyon, I’m coming after you. I want you to get on the podcast.
Wan Li Zhu: Let me know how I can help with that.
Sal Daher: Yeah. It’s okay.
Wan Li Zhu: Please go ahead.
Sal Daher: This is tremendous. I want to have him on but please continue with the-
Wan Li Zhu: He is awesome. After introducing Sara and Victor to Semyon and they had a chat with him and got into the program, they decided to move from the Bay Area here to be in Boston for the Techstars Boston program, had an amazing time, met so many people that could be helpful to them and decided to stay here. Now, they’re building a company here in Boston. To quickly recap on what they do, the idea here for AirFox is that the telcos have made a significant investment, a fixed investment in their infrastructure and now, they’re selling data plans kind of the same way they’ve sold voice in the past. That doesn’t work very well.
There’s a lot of fixed infrastructure that is being wasted because they can’t sufficiently monetize their data capacity. Because over a hundred million subscribers in the U.S. are on prepaid subscription plans, they’re very sensitive to the cost of data. They want to use more data, of course. Everyone wants to use more data but they can’t necessarily afford that. The question is how do you increase the yield and the utilization for the telcos but by still offering the consumers a cost effective data plan? That’s really what AirFox is setting out to solve, is that problem, that gap, which is a huge inefficiency in the market currently.
The way AirFox does that is by giving carriers the ability to create flexible data plans that are sponsored either by advertisers or sponsored by the developers of the apps themselves. For example, they will let telcos create programs like give the user the ability to use WhatsApp for a lower cost of data than what the telcos currently charge and get subsidized by WhatsApp to do so or to have advertising show up on their screen and for the users to earn certain credits that would then go towards their data plan. And the users can opt in to some of these opportunities and to also download certain apps and so forth in order to reduce their data plan usage cost. It gives the carriers an unprecedented level of flexibility in designing the right plan for the right user types based on their preferences and usage models. Of course, long term, AirFox is able to see so much data from each click, each engagement that the user have on mobile that it can then, in the future, tailor the right kind of offering. It is really unlocking the huge data as a value that the telecom providers have but have, to date, unable to fully monetize.
Sal Daher: I wish I’d known this. When I first looked at it, I was trying to get someone that I know who’s knowledgeable on mobile to pay attention and it just didn't happen. I will take another swing at that ball when it comes around. What stage are they in now? I mean they did a seed round.
Wan Li Zhu: They received seed funding and so the next step for them is to go for their series A.
Sal Daher: Series A.
Wan Li Zhu: They’ve signed a couple of wireless carriers already called MVNOs [mobile virtual network operator, cell phone carriers that do not own their networks] and have demonstrated some great proof points in increasing utilization for the infrastructure and reducing the cost of data for consumers.
Sal Daher: Awesome. Please talk about PathAI, a company that I found really impressive when they pitched at MIT Angels. I know you're involved. You invested via your venture as well as personally?
MIT Angels Company PathAI’s Deep Learning System Is Better at Detecting Tumor Cells than Human Pathologists
Wan Li Zhu: Correct. PathAI, I’m very excited about them. That’s a new investment for us. What PathAI does is they apply deep learning and image analysis to pathology images which are very high resolution. AI has now progressed from kind of rules based systems to deep learning. PathAI is able to do early detection of tumor cells in high resolution pathology images which is very, very exciting. In recent competition studies, they’ve shown that their AI algorithm, fully automated AI algorithm is actually performing at a higher accuracy rate than even human pathologists, which to me is again, very exciting. You can see the trend of AI development in recent years has really accelerated.
It kind of makes sense, right? Technology progresses inherently non-linear because each new generation of technology builds on the last generation. AI, as a sector, has been enabled by not just newer algorithms, of course, but also by the prevalence of data, getting access to high quality training data. In PathAI’s case, it’s a supervised learning approach, so their algorithm gets better each time it gets verified by a human pathologist and of course, verification by humans is the first way it’ll go to market. They’re applying their technology to both research and clinical domains. I’m very excited about them.
Sal Daher: Yeah. If I remember correctly, there was sort of like the accuracy rating of human pathologists, something like 80% and this AI approach is something in the high 90s.
Wan Li Zhu: Correct.
Latch – Enterprise-grade Keyless Access System for Apartment Buildings
Sal Daher: As someone who owns apartment buildings, I’m intrigued by Latch, one of the companies in which you've taken a stake. Would you like to talk about them a bit?
Wan Li Zhu: Sure. I’m a personal investor in Latch. They’re based in New York. What Latch is looking to do is to turn every door into a smart door by changing the access system. It does so by replacing the locks in those doors with a smart lock. It’s different from existing smart lock companies like August, for example, which focuses on consumer homes and mostly suburban homes with a device that sits on top of an existing lock. Latch has created an enterprise grade solution that’s going after office buildings, condo buildings with a management dashboard and a software management system that goes along with it. There’s a hardware component and then, there’s a recurring, actually a software component that is all enterprise grade and certified at the highest levels.
With Latch, what you can do with the system installed is you can enter a door by punching in a code. You can use your smartphone to gain access. You can also grant temporary access codes to guests and to delivery services and of course, with the management system for the building management can now have an access to an audit trail of all the guests and the residents. It can also assign and revoke codes for guests, for example. There is a fairly complete solution that Latch is offering and they’ve done some very successful large scale pilots in New York.
Now, with a product like that, of course, when it comes to physical security, there can’t be any bugs. The amount of effort and the investment that goes into the company to make it ready for launch is significant, more significant than most other software companies but Latch has now reached that stage. They are ready for primetime and I’m very excited about that.
Sal Daher: Yeah. As an owner, manager of multifamily properties, tenants coming in, tenants coming out, the ability to change the “key” on a door with a little bit of software, and to manage that is huge. It really is dramatic because key management is one of the hassles of apartment owning. That sounds really interesting. When a startup gets venture capital funding, one of the requirements is usually that the lead VC get a board seat and have a really important role in the way the company is operating. Please talk about the importance of having a functioning board even before a startup gets VC funding.
Wan Li Zhu: I think having a board actually serves … One of the primary reason is also to serve as oversight for the CEO. That should happen regardless of whether there’s kind of outside investment. Now, of course, a preferred board seat, so to speak, the preferred representation comes with an outside investment oftentimes by a lead VC would then take on a preferred board seat but even before that, you can have common directors that represent the common shareholders on the company which still is the case. After the preferred comes in, you'll typically have common representative and preferred representative.
The third board member type would be an independent who would offer an outside opinion and unbiased opinion in a company and serves as a voice that is not tied to stock ownership in the company. By having a board before taking on an institutional investment shows the institutional investor that you're mature in the way of managing the company and it’s helpful to have that kind of governance in place as well to have oversight over the CEO of the company.
The Investment Wan Li Zhu Regrets Not Making
Sal Daher: My long-time business partner, Bob Smith, used to have a habit of coming. “Sal, do you remember that deal? Oh, I wish we’d gone for it. We’d passed up and it was such a huge profitable deal.” This is an emerging market, distressed debt. He was always regretting deals we hadn’t done. What startups did you pass on that you went on to regret?
Wan Li Zhu: I do recall seeing a startup a few years ago and now, they’re huge. It’s called SoFi. It’s spelled S-O-F-I. It’s a problem I actually understood before. For various reasons at the time, I passed and of course, now, I regret but what SoFi does is it recognizes a simple market dislocation which is that because the student loan market has been pretty much consolidated and taken over by the government, the rates that would be an issue to students were uniform and relatively high under loans. SoFi recognized that default rates for students from top schools are much lower than default rates on average of student loans. They wanted to create a new type of student loan product for students of top schools and offer them a lower rate. Of course, they’ve proven that that’s a significant business.
Sal Daher: Is there a peer-to-peer component to that?
Wan Li Zhu: I believe there is but at the scale they’re operating now, it’s an institutional …
Sal Daher: It’s institutional.
Wan Li Zhu: Institutional product. They were right about it and they had done research with data that backed up their thesis which is that they found something like there hasn’t been a default of a student loan by an MIT graduate for like more than two decades or something like that when they first started.
Sal Daher: Yeah. In real estate, the best predictor of the likelihood of a loan being paid is the loan-to-value ratio of the property, so if people are under water in the property, the default rates are very high. If they have a lot of equity in the property, default rates are very low. I suspect that’s the same thing. If you have a lot of equity in your degree, default rates are low. If your equity’s low, the default rates are high. High value degrees, loans tend to get paid for. Interesting. Do you see trends in the space in which you're investing that you care to highlight?
Wise VC Wan Li Zhu Continues to Be Very Bullish on AI
Wan Li Zhu: I continue to be very bullish on AI. I think now that we’re seeing a lot of action too there in autonomous driving, which is a fascinating field. Back to the market timing comment earlier, there is a lot of interest in acquiring for the existing auto companies to acquire new autonomous driving startups. The reason is the talent pool that exists in these startups which is a combination of machine learning, robotics, hardware, software talent, that configuration of talent does not exist in the larger auto companies. It’s difficult for these companies to acquire and build those teams internally but they’re starting to.
Now, in order for these auto companies to catch up to the new wave autonomous driving, they have been buying very early stage autonomous driving startups. That’s creating a favorable market dynamic for investing in these companies in the early wave of the market. Most of these players have been creating solutions that are at the system and full stack level. As the industry matures, you're going to see more companies specialized in specific problems and creating component solutions that can then integrate into other full stack solutions, for example, that larger auto companies have been acquiring and also developing internally.
I do see these robotics trend in self-driving as a proof point that robots are getting safer to use in physical environments. Because of the increase in the number of sensors that they have, it is now safer for robots to be interacting with humans in physical environments whether it’s in manufacturing environments, in this case, in transportation and also increasingly in the home. I am quite bullish in AI both in digital form and in the physical robotics form for the next 10 to 20 years. I think Boston is also uniquely positioned with the right kind of talent pool and the right kind of technology experience, both larger companies and startups as well as research institutions like MIT and other schools here to produce market leading companies in AI and robotics in the coming decade.
Sal Daher: Awesome. Wan Li Zhu, I’m massively grateful to you for participating and helping make this a really stratospherically great podcast. Thanks.
Wan Li Zhu: Thank you.
Sal Daher: I’d like to invite our listeners who enjoyed this podcast to review it on iTunes. If you have any comments or suggestions, please send them to sal@angelinvestboston.com. I’m Sal Daher. This is Angel Invest Boston, conversations with Boston’s most interesting angels and founders. I’m glad you were able to join us. Our engineer is Raul Rosa. Our theme was composed by John McCusick. Our graphic design is by Katherine Woodman-Maynard. Our host is coached by Grace Daher.