Where Institutional Investors Are Putting Money in AI, Robotics & Vertical Software | Kevin Jiang

Kevin Jiang (00:00)
Volatility is an interesting word because I would say it’s dynamic, but I wouldn’t say that necessarily it’s been particularly volatile. I feel like when I think of volatile, I think of like a lot of ups and downs. There’s been probably far more ups than downs, I would say in the last few years, which, you know, does

bring to mind, I mean, one of the things that I think we care a lot about as a risk and we always try to assess is valuations and the fact that valuations are quite, I would say, rich in today’s world where, a lot of early stage startups, even when they’re just getting off the ground, they can raise billions of dollars at like a, billion-plus valuation.

Scott Bursey (02:14)
Welcome back to the Real Estate Pros Podcast, powered by Investor Fuel. I’m your host, Scott Bursey. And today we’re delighted to be joined by Kevin Jiang. As the co-founder and managing partner of Mangusta Capital, Kevin is a heavy hitter in the institutional venture capital and private equity space. He’s shifting our focus from residential retail to the high-stakes world of vertical AI, enterprise automation,

and complex supply chains. Listeners, get ready to learn how institutional capital is reshaping the way industry gets done. Kevin, welcome to the show.

Kevin Jiang (02:51)
Thank you so much, Scott. I really appreciate you having me here.

Scott Bursey (02:53)
It’s awesome having you here, Kevin. And to help our listeners get up to speed, please give us the ninety-second highlight reel of how your career ignited and where you’re pouring your fuel now.

Kevin Jiang (03:05)
Yeah, absolutely. So I’m originally from Silicon Valley. Grew up here as children of two immigrants. And growing up in Silicon Valley, you get excited about technology and startups from a very early age. And so I got to see a lot of the big tech companies that we know very much about: Apple, Google, et cetera.

kind of developed really in my backyard as I was growing up. And for me, I wanted to be a part of that world. I studied at Harvard and spent my first few years of my career on Wall Street. I worked at Goldman Sachs in their investment banking division. I worked at a private equity firm called Apollo, and then I jumped deeper into technology investing over the last 10 years. I’ve been at SoftBank

Vision Fund, which is at the time the largest venture capital technology investing fund that was ever raised. And when I joined in 2016, I helped to build out the investment portfolio and the team that was responsible for a lot of the larger growth and pre-IPO investments that we made into great technology businesses. And so I was there for about a decade

before deciding I had the founder’s itch that I wanted to scratch and I decided to start Mangusta about two years ago. And we’ve been off to the races building, investing and finding great ways to support AI startups that we invest in. So very excited to be here and and talk a little bit more about what we do.

Scott Bursey (04:41)
Absolutely. It’s great having you here. And that’s a powerful foundation to start from, Kevin. Thanks for sharing that with our listeners. What really caught my attention about you was the way you’ve been able to bridge the gap between high-level institutional funding and the complex, gritty details of physical supply chains. It’s not something you see every day. Building on that,

what is the biggest strength you leverage when identifying high-potential vertical AI platforms?

Kevin Jiang (05:58)
Yeah, I mean look, we’re we are looking for great founders at the end of the day. Investing in venture capital is ultimately a founder and management team bet. And so we meet a lot of really interesting people, but we’re looking for extremely hungry, intelligent, hardworking individuals who we believe could build the next, Uber, Airbnb, name your

successful, big startup nowadays. And it takes a lot of effort to be able to connect with those people, find them, assess that, and then ultimately also win an allocation to invest in their rounds because there’s a lot of capital flowing around Silicon Valley nowadays. And believe it or not, it’s oftentimes the founders have a lot more

leverage than the investors in deciding who’s allowed to invest in their companies and support them on their journey. So we also have to win the privilege to be able to partner with these exceptional entrepreneurs.

Scott Bursey (06:58)
Wondering if you could tell us, what’s a common weakness you see in startups trying to automate complex logistics?

Kevin Jiang (07:05)
Yeah, it’s a good question. I think there’s one of the one of the really difficult things we see across many different industries is just the pace of innovation and change within the technology stack and the different technology tools that are being used. It’s it’s very difficult, I would say, to figure out one week this is the tool to be able to use to, build

the right backend system and software that you’re using for your business. And then the next week it’s a completely different tool that, you know, has become much more leading edge, faster, more, more impressive and powerful. And so when we think about vertical solutions, vertical AI software solutions or applications, we see a lot of

change just disrupting each of these ecosystems and the infrastructure stack of like what tools everyone’s using. And that I often see as probably one of the biggest challenges is updating your technology stack for the latest tools and not getting not not having something that’s become obsolete in a matter of months because things are just moving so quickly in the AI world.

Scott Bursey (08:15)
What advice do you give them to tighten that up in the rapidly moving world?

Kevin Jiang (08:20)
I honestly think it’s it’s just a function of being able to adapt quickly. Having the right mindset personally and having the right team that’s willing to adjust to the environment and the tools that are out there is probably the best way to really be able to adapt and and work quickly to integrate like the fastest, best tools that you have. And ultimately, my belief is that’s

that’s what everyone needs in in whatever industry they’re in. Like the world is changing so quickly nowadays, more so than probably in the past. And being able to adapt to what’s going on out there in the world and what tools are available to you is just an essential skill set.

Scott Bursey (09:00)
We’d love to hear your thoughts on where do you see the greatest opportunity in physical supply chains for AI integration currently?

Kevin Jiang (09:09)
Good question. I actually think there is a lot of opportunity in robotics. You know, it’s one area that unfortunately we just haven’t seen I would say as much progress as as a lot of people would have thought over the last say five to ten years. But I do think we are reaching a bit of a tipping point as we have the hardware that now is kind of up to par.

And also now we have other compute resources, sensor data, sensor hardware that is going to allow these robotics to probably do a lot more than they could in the past. So I do think that we’re on the cusp of potentially a very important robotics evolution. And we’ve invested in companies including Physical Intelligence, which is building

a foundational model for robotics, a generalist model for that, to be able to do any task using any hardware. And I think that the opportunity here is is outstanding because it could be like the OpenAI of kind of robotics models. And so for me that’s one area I think a lot of folks

are focused on and I think a lot of large corporations and companies have invested time and effort and capital into. But it’s always felt like it’s been five years down the road or whatever it is, a couple years down the line. And I do think we are really rapidly getting to a point where that could be a reality within the next couple of years is large-scale robotics deployments that can actually drive significant return,

return on investment, return on time, not to mention probably safety as well, where humans don’t have to be working in very dangerous environments and be at risk of potential injuries and accidents.

Scott Bursey (11:00)
Thinking about the landscape, what is the biggest regulatory threat to AI platforms in the legal sector today?

Kevin Jiang (11:07)
Yeah, it’s a good good question. In the legal sector, I would say, there’s very large companies that have built pretty good brand and pretty good reputation. I think one of the one that would come to mind is a company called Harvey that a lot of venture and tech investors probably know well. I think they’ve done a fantastic job of

building a brand, marketing, and also going to market with some of the largest legal firms in the world. And so, for them, I think, and for any legal tech startup out there, I think the risk is really: do some of the large large language models like OpenAI and Anthropic, do they decide that this is actually a vertical they’re really interested in and that they want to really compete,

head to head and really invest the time and effort to take on the Harveys of the world? So far, I don’t think we’ve seen as much of a push from them, but I think that’s probably the biggest threat and risk, in my opinion, on the legal side, is that obviously these two giants have a lot of resources at their disposal and a lot of capital as well available,

and they also have a great brand name and distribution channels. And so in some ways, I think it becomes a bit of a battle on go-to-market, scaling, acquiring customers and how efficient you can be with that versus the product itself. I think all three of them can build an amazing product that probably does what lawyers and other legal professionals and legal-adjacent professionals are looking for.

But I think from a scaling perspective, the question is which one would be able to execute well and with a lot more capital and resources.

Scott Bursey (12:49)
It’s fascinating to look at. What strategy are you using to navigate the current volatility in growth stage investing?

Kevin Jiang (12:57)
Yeah,

I mean, vol—yeah, I would say volatility is an interesting word because I would say it’s dynamic, but I wouldn’t say that necessarily it’s been particularly volatile. I feel like when I think of volatile, I think of like a lot of ups and downs. There’s been probably far more ups than downs, I would say in the last few years, which does

bring to mind, I mean, one of the things that I think we care a lot about as a risk and we always try to assess is valuations and the fact that valuations are quite, I would say, rich in today’s world where, a lot of early stage startups, even when they’re just getting off the ground, they can raise billions of dollars at like a, billion-plus valuation.

We’ve seen a lot of these

opportunities and situations where it’s literally a team, an outstanding team and outstanding founders, obviously, but they’re able to raise an enormous amount of capital with nothing to really show and and no, pre-revenue, pre-product. And I think that’s something that gives us a little bit of pause and caution because

we want to make sure that we’re investing responsibly. And sometimes maybe the valuation is justified because it is truly an exceptional team that’s been able to show a track record of building amazing businesses before this, and so that’s enough to underwrite an investment into at this valuation for this team. But a lot of times I think the valuation question is one that we take very seriously and we feel

represents a certain amount of risk that we don’t think is necessarily priced into the opportunity. So we have to be a bit careful about that as we navigate, I would say a very hot environment, and, put I guess you can call it maybe volatile in that sense.

Scott Bursey (14:49)
Well, given that we’re riding more of an upward wave, has your approach to capital allocation changed over the last twelve months?

Kevin Jiang (14:58)
It it’s a good question. As a fund manager, and we raise a fund every two—one to two years, right? And our goal is to deploy that, I would say, evenly on a year-after-year basis. So, not different from how, a lot of personal finance advisors probably say that you should dollar-cost average

and invest, over a long period of time, get, deploy capital consistently. We also exercise that belief in in how we invest, right? So we’re looking to deploy about a quarter, 25% to 30% of each of our funds every single year. And so that way we avoid having vintage risk, which is, say, one year, returns are exceptional and the market’s

up and to the right, and then one year it’s down, it’s a it’s a tough year. By deploying consistently a certain amount every single year, you average out the vintage of: this year is a bad year, this year’s a good year, this year’s a bad year, etc. And so for us, I guess maybe to answer your question more directly, we don’t really change the way that we deploy, even regardless of if it’s a hot market or a cold market,

because that’s ultimately, in my opinion, not our job as a private venture capital investor. I think you can make the argument in more liquid asset classes like hedge funds or mutual funds that are actively managed, where you have the ability to have frequent liquidity on a daily basis, that you should reposition your portfolio during times where the market is hot or times the market is not.

But for us as venture capital investors, we are in investing in very illiquid assets where we don’t have the capability to, sell a bunch of our portfolio in one year and buy, we could invest a lot more in certain years. But the funny thing is we are an industry that typically invests more when the market is hot, as we saw in 2021 during COVID.

A lot of large venture capital funds invested more of their capital and raised more capital quickly in those years where the market was particularly rich and and frothy with with opportunity. And so, a long-winded way of saying that I think for us, we want to maintain consistent deployment and discipline because that eliminates hopefully a bit of the vintage risk that we see

from a lot of the larger funds that sometimes accelerate during those hot years. But otherwise, we are keeping an eye on where valuations are, where the market is. And we do want to be cautious of and cognizant of where we are in the cycle. But I don’t think it’s our responsibility necessarily to, we can’t really sell or buy that quickly given the asset class that we play in.

Scott Bursey (17:49)
Love that disciplined approach to navigating the market. And let’s shift gears here a little bit, Kevin. When it comes to relationships and networking, what has made the biggest difference for you?

Kevin Jiang (18:00)
Yeah, it’s a good question. I think for me it’s always about building genuine relationships with people that you believe in, you want to build a friendship with, you trust high-integrity folks. And you know, for me it’s it’s really, you can meet people like that anywhere. And so I go to a lot of events, dinners, conferences where I’m exposed to new people

that I haven’t met. And I do think a lot of times it’s better to meet folks that are a friend of a friend. So it’s like one, it could be a referral, it could be a person that’s hosting a dinner and every one of them, everyone brings like one person that they know, because I do think that those warm introductions are typically higher quality introductions than just, meeting someone completely random.

But at the same time, you can meet a lot of really, really interesting people at high-quality conferences or events that are being hosted by a great organization. And so I think for me, I I’ve made a lot of really good friends from that and just from like friends-of-friends introductions and referrals there.

Scott Bursey (19:10)
Thanks for being open about who you’re surrounding yourself with. Kevin, if you could expand on, what is the most critical piece of advice you’d give to someone looking to scale their venture operations in today’s environment?

Kevin Jiang (19:23)
Yeah, I think, one piece of it is there’s a lot of AI tools out there that you can utilize to make your your business more efficient, right? Whether it’s like a good CRM system—we use Affinity, which is probably the most common CRM tool that most venture capital investors are using—and they’ve just rolled out a really great AI like agent chatbot that can do a lot for you,

automates a lot for you. We use a lot of marketing and branding tools as well. For example, Mailchimp is what we use for our newsletter. It helps simplify a lot of the communications we have with our investors as well. And I think, at the right time, it’s it’s about finding people and hiring people that are also able to adopt a lot of these tools very quickly, right? So

you know, we have a team of a few folks that are also using many of these different tools to automate their day-to-day workflows as well. And they want to scale their impact with, the business as well. So I think it’s finding the right tools that work to help you scale your business and hopefully automate more of things that take time, historically have taken time, and then also finding people and hiring people who are also interested in doing that.

Scott Bursey (20:37)
Thank you for that excellent breakdown, Kevin. And you have given us some really good breakdowns today. But are there any other words of wisdom, any other advice you’d like to leave regarding Mangusta Capital?

Kevin Jiang (20:52)
Yeah, it’s a good question. Yeah, I mean, I think for us, we’re really focused on finding great founders that we want to invest in and support. So with our anchor investor being the EssilorLuxottica family office, which owns Ray-Ban, Oakley, and is the largest eyewear business in the world, you know, we’re always looking for fantastic founders that we can strategically support, providing them with opportunities to

penetrate Europe and help them with go-to-market, and also just learning best practices from our ecosystem of operators across like logistics, marketing, all the key things that a startup founder has a lot of questions on. And then for for our investors, we’re always interested in meeting great family offices and other high-net-worth individuals

who are curious about investing in AI and investing in startups. Our fund is a great way to get involved. We have—most of our fund actually is comprised of high-net-worth individuals and smaller family offices that have made their wealth and and made their fortunes in things from consumer products to real estate.

And we’re always looking for great family office or individual high-net-worth investors that want to get involved. So if there’s folks from your audience that are interested in partnering with us, you know, I’d love to chat and learn more about ways that we could also add value to their their portfolio and and their life.

Scott Bursey (22:20)
Really appreciate that deeper look. And on that note, for those of our listeners that would like to keep this conversation moving, stay in your lane, or collaborate with you on perhaps future deals, what’s the best way for them to plug into your pipeline and reach you directly?

Kevin Jiang (23:15)
Absolutely. So you can reach out to us on our website. We’ve got an email address there, or you can just reach out to me directly. My email, I’m sure Scott can include it as well in the notes of the episode, but it’s [email protected]. We’re happy to find ways to work together with great folks.

Scott Bursey (23:37)
Kevin, thank you so much for joining us today on the Real Estate Pros Podcast.

Kevin Jiang (23:41)
Awesome. Thank you so much for having me, Scott.

Scott Bursey (23:43)
And to our listeners, we appreciate you. If you receive value from today’s episode, please subscribe. We’ll be filling your tanks with a lineup of elite guests just like Kevin Jiang, who are accelerating and setting the pace for the rest of the industry. Until next time, keep your standards high and your vision clear. We’ll see you in the next episode, everyone.