This Week in Startups - The AI arms race escalates: Google’s $300M bet, Neeva’s paid search engine + So Syncd CEO | E1673

Episode Date: February 6, 2023

Molly breaks down Google’s $300M investment in Anthropic and how this deal compares to Microsoft’s investment in OpenAI. (2:00) Then, she dives deep into a former Google executive’s paid search engine and ShiftMed raising $200M to solve the nursing shortage. She wraps the show with an interview featuring the CEO of dating app So Syncd, Jessica Alderson. (13:44) (0:00) Molly kicks off the show (2:00) Google invests $300M in Anthropic (12:15) LinkedIn Marketing - Get a $100 LinkedIn ad credit at https://linkedin.com/thisweekinstartups (13:44) Neeva’s new approach to search (21:33) Acquire.com - Sign up for FREE at https://try.acquire.com/twist (22:58) AI’s data problem (28:27) ShiftMed raises $200M (33:18) LMNT - Get a free sample pack with any purchase at https://drinklmnt.com/twist (34:45) Seed/Series A Interview: Jessica Alderson, CEO of So Syncd FOLLOW Jessica: https://twitter.com/jesssalderson FOLLOW Jason: https://linktr.ee/calacanis FOLLOW Molly: https://twitter.com/mollywood

Hey, everybody. I am back after my long weekend. Thanks to you all for letting me go to Tahoe. Had a great time. And now I'm here doing some solo news. Jason is speaking at Stanford today, like the badass that he is. But we have a great show and a bunch of interesting news. First, I break down the news that Google has invested $300 million in Anthropic, the AI startup that we talked about that's trying to be safer and more responsible than Open AI. We also have a former Google executive building an AI search bot to compete with Google and Bing. That's called Neva. And I want you to tell me if you are ready to pay for private ad-free search because I am. Then we briefly talk about ShiftMed, startup of the day, a massive $200 million

raise to combat the nursing shortage in the United States. Not using AI to my knowledge, by the way. So good for them. Then we wrap up the show with a great series A interview with Jessica Alderson of So Sinked, which is a dating app that matches. people based on their personality type. It's actually, I, you know, listen, I know it's better when we're both here, but still going to be a great show. Stick with me. This Week in Startups is brought to you by LinkedIn Marketing.

To redeem a free $100 LinkedIn ad credit and launch your first campaign, go to LinkedIn.com slash this week in startups. Acquire.com, whether you want to sell a solo project or a booming startup with hundreds of employees, Acquire.com has the tools. experience, and most importantly, engage buyers to help you achieve your acquisition goals. Sign up for free at try.acquire.com slash twist. And Element is a tasty electrolyte drink mix with everything you need and nothing you don't. That means lots of salt with no sugar.

Get a free sample pack with any purchase at drinklmn.com slash twist. All right. Let's dive into our solo dolo news with a little generative AI update for you because it is in fact a day of the week in 2023. So you know we're going to be talking about generative AI again. Friday, the latest news is that on Friday, the Financial Times reported that Google is investing $300 million in Anthropic at a $3 billion valuation giving Google a 10% stake in the company.

Now you remember, hopefully, Last week, we talked about Anthropic, which is a newly launched very, very similar to open AI product that is full of messaging about building safer, more reliable AI systems. We had covered these reports that Anthropic was raising $300 million from an undisclosed investor. And so now there's this news that, in fact, the investor is Google, which isn't too shocking, considering that, you know, there aren't, I guess, that many. with that kind of money to make that investment, but also that Google and Microsoft are now locked in a possibly existential race to get to and deploy generative AI soonest.

There are, though, a couple of interesting things about this deal. Okay, so if we look back at Anthropic itself, remember that it was founded by Dario Amodi and a few other researchers that left OpenAI. And according to the Financial Times, they left because, quote, they were concerned that Microsoft's first investment in OpenAI would set it on a more commercial path and detract from its original focus on the safety of advanced AI. So that gets kind of interesting because you wonder why then they would turn around and raise $300 million from Google, which is obviously a commercial enterprise. According to other reports, Anthropic is planning to develop an

intelligent chatbot called Claude, which will rival OpenAI's chat GPT. And I would would argue it's always a good idea to give your chatbot a cute name so claude cute good one it has not yet been released publicly but here it's worth noting that google is also reportedly working on its own chatbot called apprentice bard so if google is planning to use its own ai chatbot it's unclear why they would invest in anthropic in the first place and this is where it gets even more interesting because the financial times notes that this investment is coming from google's cloud division not its venture arm, GV. And the question becomes, if you are,

if you're a corporate venture capital arm, a lot of times you're investing strategically so that you can incorporate this technology into your parent company. In the case of Google, GV is actually not a very normal venture arm in that sense. They don't do investments in the same way. It's more, they call it balance sheet capital only.

So they're investing, they're hoping to get a return, it is not necessarily about helping out the parent company. So let's give a little background on this. Here's a 42 second clip of Jason talking to Sarah Cannon back in 2020. She's currently an investor at KOTU who previously worked at Google's gross stage venture arm. And she's talking about this kind of distinction. Now, capital G is the corporate investing arm that did, I believe, Uber. So Alphabet makes this very confusing. And then they have Google Ventures, which then became GV, which operates outside of Google

with Google's money, but has independence. And Google, theoretically, Google's employees, business units don't know or get the information that's firewalled with the GV investments. So you know more about this probably than most people at Alphabet. So that's right. We were balanced sheet capital. And so we were independent. So we were not investing for strategic reasons.

It was for a financial return, just like a Warburg-Pinkus or a KKR or a TPG would do. Okay. So that's what would have happened had this investment come from GV, the venture capital arm that spun out of alphabet. But like we said, it seems like it came out of the cloud division, which makes it seem like it's more of a strategic investment of the kind that could eventually absorb anthropic in some way. But it gets kind of even weirder. It sounds like, according to the Financial Times, Google's relationship with Anthropic is limited to acting as the company's tech supplier, which again, is totally different from the way that Microsoft and OpenAI's relationship works,

because Microsoft has been very upfront about how they intend to incorporate OpenAI features into its Azure cloud services, about how they intend to eventually incorporate some chat GPT capabilities into Bing. But in this case, it sounds like Google is making. making this $300 million investment will provide cloud computing and hosting for Anthropics. So help it deal with costs related to compute. But that's it. Then continue to launch its own chatbot called Apprentice Bard and maybe in some way incubate

this safer, right? This again, we go back to this in theory safer and more reliable and trustworthy AI systems. So it's a little unclear what Google hopes to. get out of this. I have a hard time believing it's purely altruistic, but maybe they do have an interest for some reason in figuring out a safer backstop in case it's AI goes off the rails. Maybe they're just like incubating Mothra in case they turn into Godzilla, unclear. But a reminder, though, that Jason and Rachel covered Google's Q4 earnings on Friday and the cloud division was a major bright spot. Revenue up 32% year over year. The segment cut its operating losses by

46% year over year and of course has been locked in sort of that three-way race with Microsoft Azure and AWS. All of this, though, as we talk a little bit about this investment, and we're just going to kind of keep putting a pin in this because it's sort of one of those conversations that keeps bubbling up. And I have learned in my somewhat brief time here at this weekend startups that when Jason keeps bringing up a topic, that probably means that there's a in and it probably means it's a back channel from the poker table. And so this question of round-tripping, the way that these investments are being made by these big corporate partners keeps coming up.

So in this growing AI arms race between Microsoft and Google, you've got this situation where these companies are making these big investments in these AI companies, right? And they're saying, you can use our compute, which you will pay us for. And so they are getting revenue from their investment. And if you are watching this on YouTube right now, you see me making a circle because this is a practice called roundtripping. According to Accounting Tools.com, round tripping occurs when one company sells assets to another party in order to generate sales,

and then later buys back the assets. We know that in the case of Microsoft, they're going to reap a portion of OpenAI's profits when and if it becomes profitable until they get to the $10 billion that they initially invested. So an example from AccountingTools.com is that, let's say, a real estate company sells several condominiums to a related party for $4 million. And then they get to recognize this $4 million sale. And a year later, they buy those condos back for the same price.

In these arrangements, doing so generates sales not only for the original seller, but also for the related party when it sells the condominiums back. In these arrangements, there is minimal net long-term change in a firm's profits. In this scenario, the round-tripping would involve Microsoft getting that large percentage that I mentioned of OpenAI's profits, while also being its largest customer. I'm pausing so you can digest that for a second. Friend of the pod, Bill Gurley tweeted the following about this. Serious question for accounting Twitter.

Now that there are two of these, when a company uses, its balance sheet in a transaction that requires boomerang use of same dollars for their services, are they able to recognize said revenue? Couldn't you juice your own numbers writ large? As usual, the simple question with the most convoluted potential answer, Matt Garrett responded and said, this is round-tripping. I ran Salesforce Ventures for years. This was a big issue. We could not, at Salesforce Ventures, use venture dollars as quid pro quo, or even have the perception of this. If so, we could not recognize revenue

up to the amount of the investment. We had safeguards to prevent this. Otherwise, he went on to tweet. As you point out, otherwise you are using cash on the balance artificially to generate revenue. Even if there was the perception of round-tripping, he went on,

and it was just coincidental, the accounting team would not recognize the revenue. So the real question here is like a nerdy accounting question, but those are the questions on which everything always hinges. If Microsoft does not recognize this open AI relationship as revenue, then it's probably not round-tripping, we think. We might need an accountant on here,

but what we do know is that this is like, again, a major back-channel topic of conversation, especially as these big corporate investments keep happening into these AI products that rely on massive cloud compute services. So once you have Google and Microsoft doing this, you do have to ask the question, like, do these big AI companies then end up being a moneymaker and a customer? And what does that mean for the larger industry? TLDR, important people are talking about round-tripping a lot. So we think you should probably pay attention and we'll just keep you updated.

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generative AI news because once again it's a day of the week in 2023. I'm a big fan of this one though. This is a really interesting story. Neva N-E-E-V-A is a startup led by former Google executive Shridar Ramoswami. And it's building a paid subscription ad-free version of Google. So we've been talking about how Chad GPT should have Google on notice clearly does have Google on notice, but that this starts to become the way that serves. should look the way we would have all wanted search to look if advertising had not come in

and mucked it all up and if algorithms to feed you some sort of a personalized bubble like a filter bubble had not come in to make your results slightly suspect because of targeted advertising. A different business model for search is kind of long overdue, but Google's had such a monopoly on search for so long and there was this assumption that nobody would pay for it that we've never gotten it until potentially now. So Neva has come along. It is in fact paid search and it's doing citations. So when you see the search results, you actually see little footnotes that lead back to the news stories where this was reported. And they're charging $4.17 per month for searching. that's the premium annual plan if you pay all at once.

The premium monthly plan is six bucks a month. And then you just get these kind of super simple search results that are AI-A-I-Fed. AI-generative AI, I guess so. Neva, for background purposes, was founded back in 2019, launched this paid search project in 2021. And then according to Pitchbook, has raised about $78 million to date and was most recently valued at $300 million in a March 2021 series B led by Greylock. I want to like focus on that number for a minute, just side note because $78 million

actually isn't that much compared to what OpenAI and Anthropic are raising, although it's possible that Neva is more of a, you know, it's a delivery mechanism as opposed to a full like neural net AI engine on its own. But Ramoswamy posted some. some tweets showing these sort of quick summaries of events with Niva, and one of them was, you know, the U.S. military shot down a suspected Chinese spy balloon off the coast of South Carolina on Sunday. Footnote. With China expressing strong dissatisfaction over the incident, second footnote, the balloon was initially spotted over Billings, Montana on Wednesday.

Shout out to my aunt and uncle and Billings. Let me know if you saw it and is believed to have traveled over Western Canada and Alaska. It's just a super straightforward bullet point result that gives you the information that you want. And I keep going back to Jason's kind of accidental tagline for all of this, which is why search when you can get answers. Now, the question remains as we look at products like this. My initial response to this is like, I would absolutely pay for this.

I have every reason in the world to need fast, unfiltered information. I do not want to sit. I mean, I already use Duck, DuckGo, because I don't want to sift through Google's like 50 million, the button or the bubble over here and the like the summary and the ads and the this and that and all these things. I just want information without tracking. So Neva, I believe also includes that sort of basic privacy,

at least in the sense that they're not doing targeted advertising. They have this monthly and annual plan. And the free plan even offers limited ad-free searches, a limited number of devices on one account and no premium password manager or VPN. So a little bit less privacy. So this again, this has like been the dream. Like can I or would I be able to pay for search that doesn't track me and search that just gives me information? $6 a month?

I'm a hard yes on this. But I do think there's still a reasonable question about whether people would pay for this. So to give you a sense of how massive the search market potentially is, in 2021, Google was handling about three and a half billion searches per day. That's over 100 billion searches per month. So imagine that Neva is able to grab, you know, $50 a year from even 1% of that. At this moment, one of our producers is definitely doing that back of the envelope math because I'm not Jason and I can't do it that fast, but I'm going to like make it easy for you and

say, that's a lot. That's a lot. And then, you know, Neva has just sort of burst onto the scene. Let's check out, actually, a 77 second clip with Neva CEO Shradar Ramoswamy on CNBC's tech check from back in 2021. But this model, you're not doing any ads at all. No affiliate links either. So this is even more pure than Duck, Duck, Doe. You're just going to charge consumers a monthly subscription feed. What convinces you that people are ready to subscribe to search? Neva is the world's first completely ads-free private subscription search engine. Now, all of us use search. We don't really think that much about it, and it's a giant business, $150 billion across the globe. But the fact of the matter is that what started as a way to

get you and need great information has now become an enterprise where most of the energy is on advertisers. So Neva is super innovative here because we want to put you at the center of the service. By being a subscription service, we think we can create a much better experience for you, one that is more personalized, one that is deeply private because the model says we don't take money from anyone other than customers. And we are able to bring all of this together into this singular expedience. And more, we also support publishers from early on because search engines are based on great kinds. Right.

And so you're going to see lots of great content on Neva. It's all of these that we think will convince people that Neva is worth paying for. I mean, also, side note when you look at the pricing plans on Neva.com, there's a little note at the bottom that says choose premium and let's fight climate change together. And then there's a pop-up that says Neva will contribute 1% of our profits to fight climate change. And until they reach profitability, they'll contribute $5,000 a year to the Environment Defense Fund and 350.org. So like, you know they're talking to me.

I am privacy obsessed. I've been using DuckDuck Go for over a decade. And they're going to contribute to climate change. What I really want to know is, are you in? I'm obviously all in on this vision. I also think, though, as an interesting data point, it's really worth pointing out that Niva's CEO was at Google for almost 16 years. So he knows exactly what he's up against.

He was an engineering executive in Google's ads and commerce division. for his last six years at the company. He's very familiar with the business model, the incentives, I think that do potentially pervert search results. That's one of the things that people complain about a lot. And he knows exactly what kind of money he's facing and probably has a sense that there is a business opportunity. I can tell you I'm like so hungry for this.

And I can't wait to get the sort of chat GPT version too, where it's just like, I just want the answer. And then the sources, I think, is really important. Microacquire is a startup acquisition marketplace that helps you sell your business quickly and easily. And listen, the acquisition process was never described as quick or easy, but MicroAquire has changed that, just like they changed their name from Microacquire and rebranded asacquire.com. Yes, they want to show the world they can help any startup of any size get acquired. Acquire's mission has remained the same. Help founders achieve life-changing outcomes, build tools that make acquisitions easy, and foster a new generation of

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your startup or looking to acquire a business in 2023, sign up now for your freeacquire.com account. Get more information at try.d.acquire.com slash twist. That's try. Dot acquire.com slash twist. there's also a data angle here. So one of the things that Google has in general when it comes to search, and particularly to personalizing results, is a data advantage. They have a data advantage in terms of selling ads. And as we continue to talk about generative AI,

you've heard Jason and I am now many times, I think, mention the data problem, right? Fundamentally, AI doesn't work without data. And that data, you may or may not have permission to use it. It may or may not consist of a copyright or IP violation. And the quality of the data is directly correlated with the skill and the ability to learn of the AI. Garbage in, garbage out. We say it over and over and over.

And so the data sets and the training data become truly fundamental. If you don't have good data on which to train your model, you are at a disadvantage in a fast-growing arms race. and Jason has been saying for months now that the IP lawsuits are about to become a huge part of this. And I think even said last week that Open AI could find itself in a situation because it's not being rolled out with citations where people sue to prevent their data from being included in the training sets. And so,

Asrida Ramoswami had this 14 tweet thread starting over the weekend about how, publishers need to beware. He said, your content is going to get sucked into AI bots pulling your work into their large language models. Your referral traffic will go down. And if you just side note, if you know anybody who works at a media company that relies on referrals, and I am talking about my home base where I grew up CNET for 13 years,

I am intimately familiar with the situation where Google changes something in the algorithm to either punish or encourage certain behaviors or language or link procedures within their articles and all of a sudden your traffic plummets. Like everybody in media knows that they are 100% at the mercy of Google and have been for like two decades. And it is a really abusive relationship. And so he's pointing out that instead of bothering to refer back to the original source, a lot of these engines, something like Open A.S.,

He says, for example, if Google clones, Neva, which we expect, then publishers are at risk, because as search engines become answer engines, referral traffic will drop. This is an existential threat for publishers of news, publishers of recommendations, review sites, all kinds of publishers out there on the web. And he points out in this thread, it's happened before. Google featured snippets and the featured snippets are the thing I was just complaining about, the little box that's like, here's the actual. information that you want, don't worry, we took care of it for you. That caused a massive drop in

referral traffic on 10 to 20% of queries in the past, writes Shradar. This is dangerous for publications unless they take control of their relationship, which with their search overlords. There are three ways to do this, he says. One, don't get crawled, which we all know is virtually impossible. And then he says, unless publishers band together, unilateral disarmament is hard for a single publisher to achieve against a monopoly. Then he says, ask for payment for LLM inclusion. Again, tough against a monopoly. Niva, he says, is committed to pub revenue share.

That is, they're going to implement a revenue share model with publishers as part of their rollout. And then he says, or three, publishers take ownership of the relationships with their users. With AI transforming the web, what does it look like for referral traffic from an aggregating answer bot Google to become sticky traffic that originates? and stays on an app or website. So he gives the example of Adam DeAngelo and the Quora team, creating this vision where users can kind of use the best bots

for their various information needs. And in fact, this is a really interesting, this harkens back to my interview with Albert Wenger from USV. He talked about the idea that all of us should actually have the right to create and utilize our own bots, that we shouldn't necessarily have to use the bots that are given to us from any one of these companies. We should have agency over a bot that goes out and finds information on our behalf without us having to trade, for example, our data or our attention in terms of ads.

It's a long thread. I'm not going to necessarily read the whole thing, but I encourage you to check it out because I do think we are entering, you know, we've talked a lot about the AI race. We've talked a lot about all the different ways that this is going to change information delivery and change our relationship with information. And there are just so many, many, many, billions of dollars at stake here and an entire digital advertising universe and all of the publishers behind search. Like, if you think about the way in which search did ultimately change everything. It became the entry point for the information age in which we live. All of that is about to be disrupted again. And it is a huge deal. Huge deal. All right. I'm just

going to do one last mini update here, a startup of the week, if you will. ShiftMed is a company that has just raised $200 million to address and sort of digital. the massive nursing shortage that's going on in the United States right now. The U.S. unemployment rate is, of course, 3.5, 3.4%. All of the increase, many, a huge increase, 20% of the increase in jobs that were reported in the latest jobs report in the United States involved education and health care. Nursing shortages have been this huge problem since before the pandemic. The Bureau of Labor Statistics estimates there will be over 200,000 RN openings each year through

20, 31, we do not have enough nurses. And that has led to all kinds of things. It has led to this sort of travel nurse situation where you can actually make like three to four to five times as much money if you become a travel nurse as opposed to staying with one hospital. That has led to that on top of the fact that nurses, although there is a huge shortage are also underpaid and poorly treated. There have been strikes all over the United States. The pandemic led to tons and tons of burnout. Obviously, travel nurses, by the way, side note, single travel nurse can earn up to $10,000 a week and can cost a hospital as much as 10 times more than a regular staffed nurse, but meanwhile, a hospital might be paying this for a travel nurse while the other nurses are

outside striking over their pay. It's absolutely bananas. The whole nursing situation in the United States is banana pants, hot mess, disaster. So ShiftMed just came in, and this is kind of maybe why you can imagine a company raising $200 million that's not ungenerative AI. They want to reduce operating costs for hospitals by 30 to 40 percent, essentially by kind of gigafying the healthcare industry. So the app works by filling open shifts at hospitals or long-term care centers, assisted living communities, the company negotiates worker rates and then splits the difference with health systems and then also offers health facilities the option of white labeling the app so that then workers could use it to pick up shifts after hours so that maybe they can take advantage

of any capacity that exists in the community without having to hire these travel nurses, which is of course disrupting all of the economics of nursing within hospitals. Now, I don't want to understate how hard it is to deal with the healthcare industry in the United States. There are like unions. There are probably insurance rates to think about. There's sort of all of the hospital bureaucracy here. This is a very, very, very difficult industry to disrupt. But it's probably one of the industries that needs it the absolute most.

So as these labor shortages have grown significantly. We've seen actually a lot of other job placement platforms raise capital to combat this kind of lack of healthcare worker. Incredible Health raised an $80 million series B last August, valuing it at $1.65 billion, Gale Healthcare, raised $60 million from FTV Capital last January, and Bemlo, a YC alum, raised a $3.3 million seed round backed by Y Combinator, Long Journey Ventures and Uncommon capital in July of 2022. It's almost like instant delivery services or, you know, gig work, Uber and Lyft and DoorDash for healthcare. And it kind of is one, yet another example of where an ancient industry cannot

overhaul itself. And so startups want to come in and do it. And we'll see how the success works out. All right. We have, we don't normally do this on this show. We don't do the like, it's Valentine's Day. So we're going to do Valentine's Day content. But it accidentally happened and it's absolutely delightful.

I have an interview up next with the co-founder of So Sinked, Jessica Alderson. And so synced and is a dating app that was built by Jessica and her sister Luella, and it matches people based on their personality types. It is not a Myers-Briggs test specifically. They did all of these research, all this research and sort of determine that personality types are a huge indicator of compatibility and created this like Jason called it horoscopes for tech dudes. And I actually asked her, I was like, you know, we're in this point, this stage of like extreme self-examination and, astrology is super back and this is kind of exactly that. We have this great conversation about which personalities use the make for the best matches and the surprising age group that is taking to so synced. It's a great conversation with Jessica Alderson. That's coming up right now.

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That's eight single serving packets free with any element order. go try all eight flavors at drink l mn t.com slash twist element offers no question ask refunds so you got nothing to lose that's drink l mn t.com slash twist for a free sample pack with any purchase welcome to another interview in our seed and series a series. I should come up with a better way to phrase that but here we are today I'm super excited to talk to jessica alderson the co-founder and CEO of so synced which is is a dating app designed to match compatible personality types, which is, I feel like a big promise. Like, we've all been trying to do that, but you're taking a unique take in terms of how you're pulling it off. Welcome. And I can't wait to hear all about it. Yes, thank you so much for having me. Excited to be here. All right. So, tell me how this works. So you sign up to the app. The first part is kind of like a typical dating app. And then the big difference is we have a personality test and it's based on the 16 personality types model, which a lot of people probably

know already because it's the most popular personality framework in the world. And then, yeah, we essentially let you know your personality type. You get like a description, strength, weaknesses. It's, you know, hopefully quite fun. We have a very high completion rate, so I think people do enjoy it. And it is actually pretty quick. It takes, you know, just a few minutes for most people depending on, I guess, how well they know themselves. And then, yeah, you basically see different profiles on the app. You see their personality types. And we have like a unique matching algorithm based on personality compatibility,

which we, yeah, have now refined the data. We started off with the kind of theory ourselves. And now it's based on a pretty big data set, which is pretty, pretty fun, really. So let's talk, let's start a little bit of. bit on the with the personality test it it is the or it's based on or it's very similar to the meyer briggs test that people are familiar with it's kind of those letters yeah not not officially a Myers briggs test right not associated with the Myers briggs company um so it's yeah basically the 16 personality types framework is kind of how how we describe it um but yeah it's like

I-N-T-J, ESFP, E-N-F-P, those personality types. Got it. And then talk about the matching. Why, why that, I wonder, like, is, and also kind of, and I mean this as a compliment, how come nobody thought of that before? Like, this is something we're all so familiar with. We all do it for work. It's like a framework that we incorporate into lots of relationships, but not necessarily

dating up. Yes, and you're definitely not the first person to say, why hasn't this been done before? And we were really surprised. So my sister is my co-founder. And when we were kind of talking about this idea, we googled and we're like, why, why is no one doing this? It makes so much sense. It's such a popular personality test. People love it. It's used extensively in a kind of work environment. And so, yeah, basically we chose that because I used to work in finance. I worked at Morgan Stanley for five years, worked in London for the majority of that time. And I dated someone who was Australian. And we ended up moving to Australia together after like a couple of years of dating, which was, yeah, incredible love Australia a lot. Amazing. Yeah. And so I got a transfer with Morgan

Stanley, which is also amazing. and yeah, was there for a year and then unfortunately the relationship didn't work out and I was leaving my job at the same time. So these two natural ends happened and I had been super into personality types and personality tests, particularly the 16 personality types framework

for a long time but had mostly been using it in a work context. And when these two natural ends happened, I was like, right, I'm just going to take a bit of time out, like backpack around the world, just, you know, had been working with super long hours in investment banking. I was like, I'm just going to read about things I'm interested in. You know, it's very lucky to be in that kind of position where I could do that, right?

Like, not everyone gets that opportunity. So, yeah, and because I'd had this breakup, I started applying personality types to, like, love, dating and relationships. And I spent, like, yeah, I can't tell you how many hours kind of researching it, but it was the trip ended up being a year. and a lot of it was spent looking into personality type compatibility. You know, I met lots of people when I was traveling. They spent a lot of time on Reddit. There are people posting all day, every day on, you know, like E&P forums,

ISFJ for and saying, you know, I'm dating this person and this personality type, this is why it's great. This is why we're having challenges. So there was a lot of information out there, I guess, is my point. And I just saw really strong correlations between which types were, I guess more natural fits and relationships and which weren't. And then I got back to London and I was telling my sister about this over some drinks in Soho. And yeah, we decided to go for it because, yeah, like you said, we were kind of wondering why this hasn't been done before.

Yeah. Some of these, for people who are not familiar, like some of these are things we've been talking about a lot, I think, in society. like introversion, you know, I versus Z, introvert versus extrovert has been coming up a lot. There's a lot more sort of awareness, I think, about the introverted personality and what that can mean. The other letters are S for sensing, I for intuition, T for thinking, F for feeling, J for judging, and P for perceiving. And then you get this sort of four letter personality type. I wonder, talk to me about the matching then and where that comes from. because I'm assuming it's not, it's certainly not a one-to-one.

I can tell you I, you know, recently tried to date an ENFP like myself. And that didn't go, you know, it's like a hot mess. Nobody's in charge of anything. Yes. Oh, my God. That must have been quite fun and quite chaotic. Extremely fun and complete chaos all the time. Yeah.

Like, yes, no one ever wants to make it. You know, you can imagine. So it's not a, so I would imagine that a lot has gone into creating that algorithm around the matching, right? Yes. Exactly. And actually, ENFPs are one of the types that are most likely to find a relationship on our app. It's like the most kind of common couple that we see ENFP and INTJ. And it's kind of funny because it's this almost like magical couple that like lots of people in the personality type world talk about. And then actually now we have the data and it is the couple that we see get together the most. I know actually quite a lot of ENFP, INTJ couples. So. Okay, good to know. Yeah, the bigger picture concept is to match couples who have some similarities so that

on the same wavelength, they understand each other and they have great conversations on a daily basis. But then a certain amount of differences to create that spark and that sense of intrigue. And, you know, so it's kind of fun, exciting and there's that chemistry because I think sometimes when we talk about personality compatibility, people assume that it's like, it's not a not that kind of fun chemistry aspect as well, but it definitely is. It's kind of all of it packaged up. It's kind of great too because it gives you an immediate conversation starter. Yes. Yeah. That's a really good point. And we have a super, super high match to messaging conversion ratio. It's like close to 10 times higher than a typical dating app. Because, yeah, I mean,

I guess firstly there's the intention side of things. People sign up. They take a personality. test. The vast, vast majority we did a survey about this the other day, I'm looking for a long-term relationship, which, you know, you'd imagine, right. And then the second part of that is, yeah, there is this kind of more fun, interesting aspect to it that makes it easier to start a conversation. And you see this in people's bios on the app as well. They're like, oh, this is, I'm this personality type. This is really accurate. Or, oh, this has really intrigued me. And it's, yeah, a good, good starting point to chat, really. And then the rest of the mechanics of the app are pretty standard dating app, right?

Like you swipe or you, I mean, how does kind of the rest of the app work compared to what people are familiar with? The kind of the matching is similar to kind of, I guess, like most dating apps. We have a personality hub, which is again kind of where we're different, where we do daily polls. Like, you know, questions, do you believe in love at first sight? you know, do you usually make the first move, that kind of thing? We break the answers down by personality types. So say you're chatting to like an INTJ on the app, you can kind of see how INTJ's answer all these questions.

And we have like a compatibility calculator as well, which is kind of, I guess, like the start of the route we want to go down more in the future where you can kind of, you have your matches and you also have famous people as well if you want to see your compatibility with famous people. And then there's a kind of like detailed breakdown of different aspects of compatibility, say like how you would likely interact on a daily basis, the type of connection you'd likely have like sexual chemistry, all these kind of things. Because I guess like, yeah, where we kind of want to go with it more in the future is, I guess, really expand that kind of self-awareness, self-understanding part and then the understanding of the other.

person as well. Right. Can you just create a hub called How to Choose a Restaurant? Like, I feel like that's where it all breaks down. How to choose a restaurant. Yeah, yeah, that's true. Yeah, exactly. Just have like a spinner and just be like, right, yeah, let's just go here. Who is going to be in charge of choosing the restaurant is all I want to know. You are, it looks like, seed stage so far, right? Raised a seed round in 2021. What, how many, like, what can you tell us about your traction so far, users, who they are, you know, how it's been going. You were written up in Forbes almost immediately, which is great. Congratulations.

Thank you. Yeah. So in terms of traction, we now have like hundreds of thousands of users, which is, yeah, super exciting. Yeah, we do like a lot with like journalists and the press. So, yeah, as you mentioned, we're featured in Forbes as the next big thing in dating. We were the youngest company last year to be named by Fast Company. as a top tech startup to watch globally.

And yeah, we're like, yeah, featured a lot really in the press like Vice, Mashable, Huffman Post, daily mail, all kinds of publications because we do a lot on the kind of like relationship expert side of things. And we've actually like started now commenting more on like celebrity compatibility. So my sister's last time she did a column, a weekly column about Love Island. I don't know if it's as big of the US. Yes, yeah, yeah. And we're doing like a lot on that now because it's restarted.

We're not doing like a weekly call and we're kind of taking a slightly different approach. But yeah, so a lot of traction there. And we've helped, yeah, thousands and thousands of people now find relationships. Have like a lot of so-sync marriages. I'd say it's about probably about 20 that we know of. Already. Wow. Many, many, many more.

We actually found out about a marriage on TikTok last week, which was kind of of crazy. Just someone commented on a TikTok post and said, by the way, I downloaded your app a year ago and I'm now married to my partner who I met on it. Oh, that is so great. Okay, so now talk to, what is it like to go from investment banking to now I'm helping people get married? I mean, this must just be like a pretty fascinating journey overall. Yes, yeah, definitely fascinating. there isn't anything I would rather be doing right now. Like, I just love what we do and it is just so fulfilling. And, you know, sometimes if I'm having a bad day, I'll be like, but we've helped, like, loads of people, you know, find their life partner. And, like, you know, even if you

help just two people get together, like, that actually changes their lives. If, you know, someone that they stay with long term and they really kind of, I guess, you know, just have a great relationship. So, yeah, it's definitely been interesting. I'm, yeah, I'm really glad that I started an investment banking. That was great in terms of learning about, you know, businesses and financial modeling and all these things that definitely come in handy now with a startup. But yeah, I feel like, yeah, very happy with the kind of path that I've gone down, really. And then talk to me about, as long as we're talking about investment in business, How do you make money, pretty standard membership model?

Yes. So, yeah, exactly. Like a subscription package, like similar-ish features to probably ones that you've seen, kind of, you know, paying to see who's liked you, travel mode. We have like a golden message. So if you want to send a message to someone that you haven't yet matched with, if you pay for the membership package, you can send one golden message a day, kind of like profile boosts that kind of thing so yeah the golden message is like a more

thoughtful kind of mega like if that makes sense so you actually send a message with it so kind of gets more of people's personality across and yeah I mean like that is I would say like one of the great things about dating apps is they you know monetization has definitely been worked out there's quite a lot of I guess maybe like social apps that struggle to monetize. But, you know, people definitely do pay for love and they, yeah, pay for like hookups and short-term relationships as well in a kind of a different way. Yeah, absolutely. You mentioned that the more data you get, the more helpful it is to the algorithm. Like what, I mean, it is pretty, like, I will confess that I sent it to friends who are in relationships because I was like,

dude, you have to do this. Like, we have to know our personality types. Do you imagine, does that help you or hurt you? Was that a bad thing? Should I not do that again? No, no, that's, yeah, that's completely fine. Or does it, you know, it helps because you get more data or? Yeah, I mean, I guess the data set that we use at the moment is when we have success stories. So when people leave the app because they found their partner and, you know, we ask them what the personality type of their partner that they met on the app is. And then we also have quite a lot of people that write in or like, you know, even like I said on TikTok, just message on social media. And then we always ask them, you know, what is the personality type of?

of your partner that you met. So that's the kind of main data set that we use now. And then like going forwards, you know, we don't yet have, say, like a data scientist, but going forwards, there's a lot of interesting things we can do, I guess, like pre-success story that could increase people's chances as well. What have you found, do you have like high level? I mean, I think it's so interesting that, for example,

you said the ENFP and what was it, INTJ is really successful. Have any other kind of? insights like that that you've found about personality types and how they mesh or don't or go? What's the biggest disaster? Yes, the biggest disaster. Yeah. I mean, any, any personality type pairing can work. And I always, you know, want to be careful to say this.

Never would say to someone this is not going to work because it's simply not true. It's just that some pairings will, you know, require a bit more effort or, you know, obviously different people like different things as well. So I think the kind of the biggest learning from like a personality compatibility's perspective is, and it's something that we have the theory of in the beginning and the data has proved this, is that you tend to see like intuitives matching with intuitives or I guess pairing up with intuitives and then sensors pairing up with sensors. So that's the second letter N or S. and that's something we expected because they just kind of like tend to be more like on the same wavelength in terms of like daily conversations. There are like, you know, advantages to censor intuitive pairings as well. But that's, I guess, probably the biggest learning in the data.

Or it's just it's very consistent, it sounds like. Yes, yeah, yeah, exactly it is. How sticky are dating apps? Like do people bounce around once they find? find one. I mean, you know, it's a crowded world out there when it comes to options for dating. This is a great differentiator, but I also wonder how you continue to sort of keep and engage new people. Yeah. So I would say it kind of depends on the type of dating apps. So if you've got dating apps that are more focused on like short-term relationships, more kind of

hookups, then you know, you. you do have those kind of repeat users that will use it, and then they might not use it for a couple of weeks, and then they'll use it in like a couple of months, say, and, you know, because they're not getting into a long-term relationship, they're just using it repeatedly, essentially. And then you have a kind of like the other end of the spectrum where people are actually finding long-term relationships,

potentially lifelong relationships on your dating app. And this is actually really good in a different way because this is something that, you know, quite a few investors brought up when we were raising our funding round. And they're like, oh, but if you, you know, if your matching algorithm is so great, then you'll lose people. You put yourself better business. Yeah. Yeah, yeah, exactly. But it really, it doesn't happen like that because those success stories are literally like the best adverts for the app that you could ever imagine. imagine, like, how often you ask couples how they met to like, you know, when you're in a relationship, how much you talk about it yourself. And it's, you know, like literally, and I guess it has the added benefit of having this interesting talking point. So we've talked to our success stories about this and they say that, you know, they bring it up at dinner parties and things like that. And then people at dinner parties are doing the test around the table because they want to know their personality type. So, yeah, there are kind of like different ways that I guess you can have or can kind of grow. And if you don't have repeat users as such, then, you know, that kind of word of mouth from people telling their friends how they met is really, really powerful. And we see this with press as well, actually.

When there's a press article about a success story, we see like a lot of downloads because people just like to actually. see real people and hear their stories. Yeah, well, there's just a built-in kind of easy virality around. Like everybody, you know, every can grasp this immediately. Everybody's somewhat familiar. Although, I keep saying everybody, and I wonder about your demographics. Because I could imagine, like, a lot of us do this at work. I could imagine you might skew even a little older than a bumble or a Tinder,

which is very maybe millennial focused. But maybe I'm wrong. Yeah. Yeah, I mean, that was the exact theory that we had. But it actually hasn't really worked out like that. We thought the exact same thing, you know, lots of people take the test through work. And so you'd think it would kind of be, you know, lots of, say, like, professionals that have found out about it, then become interested. But actually, it's kind of, it's like quite a Gen Z audience.

And I think one of the reasons for this is that it's like a big thing on the, social media. So, you know, it's not, not unusual for a personality type, like TikTok video to get, say, like, you know, a million or sometimes millions of views. And particularly during lockdown, like, personality type Instagram really blew up. So I think that has kind of encouraged this, I guess, like slightly younger audience. And there are also probably people who spend, like, more time on Reddit and that kind of thing. it's interesting too because although it is not that astrology has been having a big moment

like i think that there's sort of like i think everyone's doing this right now like a lot of people especially genzies are like really into this particular type of examination and it feels a little bit like that like the way that you've it's it's quite clever i think the presentation and the writing and how you know kind of excited it is about your personality type that it's got that kind of vibe with more science behind it, more science. A hundred percent is that kind of self-reflection vibe. And that is very much a structural trend. It kind of ties in with, you know, therapy becoming a bigger thing over the past, say, like, five years.

And like the way I think about this is using like Maslow's hierarchy of needs. So like, you know, at the bottom you've got like food, water, shelter, that kind of thing. And then as you kind of like go up, it goes like all these different things. self-esteem and then like the top of the pyramid is self-actualization that's you know like essentially reaching your true potential and a lot of people use like frameworks to help them understand themselves and that's kind of where personality tests come in um so i think like i do kind of think we're just at the start of that really and that it's just going to like keep growing and growing when you look at data of how it's kind of trended over the past few years it does have that like

hockey stick growth curve. You know, like people are just going to come more and more kind of, I guess, like wanting to be self-aware and going down that route as we go on. Well, then, great timing. The app is called So Sync'd with No E, SYNCD, and you can find it at so-syncd. And you can find it at SoSynct.com. Jessica is the co-founder along with your sister, Luella, which, by the way, we didn't even get into with that as adorable.

Yeah, I love it. Yeah, it's great fun, actually. Oh, that's wonderful. Well, congratulations, and I'm sure we're going to be hearing a lot more about this in the future because I can tell you I'm already telling all my friends. Yes, thank you so much for having me. Congrats. Thanks for the time. All right, thanks for listening, everybody.

We have an awesome interview coming tomorrow about a potential calamity event coming for startups later this year. I'm not trying to bring you down. I'm just saying you might want to listen. So we'll see you then. We'll also have some quick news too. Stay tuned. Have a great rest of your day. Bye.