The below is a full (unedited), machine-generated transcript of a Youtube session / podcasting episode I recorded with Shmulik Fishman, co-founder of Argyle in Q1 of 2022. You can view the video/listen to the podcast on Youtube, Apple Podcast, Stitcher or wherever you get your podcasts.
Erasmus Elsner 0:06
All right, welcome everybody to another episode of Sandhill Road, the show where I talk to successful entrepreneurs and their investors about the companies that they built an invest in. And I’m super excited to have with me here today. Shmulik Fishman who’s the founder and CEO of Argyle. What is Argyle Argo is a universal platform for providing and accessing employment data. Think of it as a gateway or universal API for your employment data. Shmulik. Thanks for being with us. Where does it find you?
Shmulik Fishman 0:38
I’m in New York. It’s snowing outside, but all the same. Good to be talking with you.
Erasmus Elsner 0:43
Right? Yeah, it looks it looks nice. We can see the skyline. We have the feeling of Manhattan maybe to start out with Argyle It was founded in 2018. And it’s not a trivial company to understand that there are a couple of ways one is to just compare you with the traditional incumbents, the credit bureaus, but I found it more interesting to look at it through the lens of what you refer to as the personal profit and loss statement. What is an individual profit and loss statement? So if you think of a consumer, he earns his monthly salary, and he goes out and he spends it, the existing FinTech layer has so far mostly focused on the last side, if you like so on the expenses, where do they spend their money? How much do they spend in Starbucks? How much on Chipotle and you have incumbents like plaid who are doing that quite successfully. But so far, there has been a blind spot in a sense on the income side of the p&l statement, if you like. I found that analogy quite interesting and also maybe a good basis for us to unpack what Argyle is actually doing. Sure,
Shmulik Fishman 1:46
it’s so happens to be that there’s been a tonne of work to digitise a bank statement. When you think about Expensify, or you think about QuickBooks, you think about plaid, you think about a lot of different challenger banks. They’re doing a fabulous job at digitising, automating what you’re just talking about expenses, and what would otherwise have to be printed out from JPMorgan or from a Wells Fargo. The flip side of that is digitising a pay stub. And that is something that really actually today still exists as a PDF. And if you’re trying to rent an apartment, get a car, get a loan, get insurance, get a mortgage, open a bank account, keep going get a credit card, you’re going to be downloading a PDF copy of your pay stub, and you’re going to be emailing that to that financial institution. Sometimes if you’re if you’re doing a term loan, you’re going to be doing that every two weeks, repetitively, there’s nothing wrong with that. It’s just manual. And it’s the way that the world has existed, frankly, for about 50 years now, where you take a pay stub from your employer and you manually give it to a financial institution. And in essence, all we’re doing is we’re saying instead of that manual process, let’s use a computer, let’s use a tool to assist in moving that data from your employer, to this financial institution.
Erasmus Elsner 3:14
It’s interesting. And I imagine that you saw this, when you tried to connect to a third party, be it a loan provider, and you tried to sort of manually put in this data, and you saw there was sort of this bucket of data that needed a data stream, I want to be clear,
Shmulik Fishman 3:31
I definitely have to have experienced along with I’m sure almost everyone else. Somebody’s asking me for a pay stub. I’ve gotten a mortgage before I rented an apartment before. And so those experiences do include this process. And so I was familiar with it. But on the other side, I’m the lucky one. We’re the lucky ones. The people that probably listening to this podcast are the lucky ones. We are financially more secure on average than the normal American than the normal worker. Most people have to deal with this issue in a way that I don’t even think I can fully appreciate where you are really living paycheck to paycheck, I find it really interesting and quite sad that over half of Americans would go bankrupt if they had a $500 extra expense that they could not plan that just speaks to how tedious people’s income is. And so yes, everyone has to deal with pay stubs. Everyone has to deal with their income and making sure that it’s reported correctly. And it’s really hard to do that. The start of Argyle was very much not what it is today. Wish I could say that I really was forward thinking and we really had a 10 year plan all put together. That was not the case. This is an amazing accident that we’ve been involved in. But Argo actually started as a way to autofill job applications. If you think about a lot of high volume jobs, working at Target working at Chipotle work in a rental car company is a place where you have to hire a lot of people because there’s a lot of churn and you have to fill out a lot of forms. What’s your first name? What’s your last name? What you Email Address, what’s your phone number? What’s your marital status with Social Security number? These are fields on an application. And that’s where we started, how do we automate the fill out of these fields with data from your last employer, it’s so happens that that job application, we didn’t know it at the time. But that job application is the start of a mortgage application is the start of a loan application is to start a bank account origination process. And so that was our wedge. That was our foray into this data set, because the application component of it is the same across all these verticals.
Erasmus Elsner 5:33
Gotcha. But I want to take a step back now, and talk about the funding history, which is something I typically talk about later on in the podcast. But in your case, it is quite special, because the last round that you raced in October 2020, you raced by doing something quite unique and something quite innovative. Most companies are most startups who raise a Series A, they work weeks and weeks on their deck, they send it out to investors, they hope to get a response. But what you did was you prepared a series a investment memo. And for the listeners out there an investment memo, it’s typically what the leading partner at a venture firm prepares for the Investment Committee to basically pitch the deal to the other partners. So it includes things like tam founder history, background status of the company, potential risks, but also potential new verticals. And obviously use of funds. And what you did in a very creative way, you spun up a notion page where you prepared this investment memo proactively for the investors. And you touched upon all of these aspects basically being, in essence, quite empathetic to the way that these venture investors think right. And I think for any founder out there raising a Series A, it’s a great lesson on how to get this right, and how to think like the investors and you ended up closing a 20 million series, a led by Bain Capital ventures with the participation of bedrock, which is I think, Jeff Lewis’s firm, maybe talk a little bit about this initial idea. And then I want to use this session to go through the different chapters of this investment minimum. Like all
Shmulik Fishman 7:18
founders, I’ve spent a lot of time in PowerPoint. And by pitching to a lot of clients, you spend even more time in PowerPoint, and by doing board meetings, you spend even more time in PowerPoint, I’ve done enough PowerPoint slides from my lifetime, I make a point now, actually to not have PowerPoint on my computer. Because of all the work I’ve done on it before Argyle, I’m a storyteller by default. I like writing narratives and investors like hearing stories, and they want to be pitched versions of the future a story of the future. And that takes a very narrative form. It’s not about flashy graphics, and big logos and graphs and charts that go up into the right, that’s a part of his story. But that’s not how a story is written. And is dealing in something that is quite dry data, you can visualise it, but it’s not fun to talk about start date and birthdate and 401k contributions. This is dry material. And to create a story around it, you really need a narrative driven format. The way that we started this project actually was by looking at news articles on the New York Times and on the ft and how they weave together a story with graphics, images, interactive elements. And the thought was, can we take the narrative design and the narrative form of a news article, and make that the way that we’re pitching or we’re talking about our go? And you are very much right? We wanted to do as much work for our investors on their behalf as a founder, you don’t see the other side of the table as frequently, but we’re talking to enough of them, I picked it up, they have to do a tremendous amount of work on their end. And a lot of the reasons why some investors don’t get engaged with you is because they’re like, Well, I have so many resources, and I only have this number of analysts and they’re going to have to write a very long document, can I deploy more resources against your idea, if you can lower that barrier because you’ve done a bunch of work for them, that’s going to make them more interested to engage with you feel that as you’ve actually put in the work to understand their side of the table. And so it made for the need for a very different set of conversations. Investors would come to the initial meeting with having read the document having very strategic questions wanting to go to a specific place and the document first they did not need me to start with the big idea get to know me they read all of that. And that meant that we basically got to have an hour three conversation in the first minute
Erasmus Elsner 9:48
love it absolutely love it. It allowed you to start on page 10 In a way I want to start off with the title page and you did use a graphic there and I’m going to sports casted and showcase Acid. And for those people listening on YouTube, they, they will see the picture. So basically, you have a picture that shows different data holders, from workday to gussto, to stripe to Uber, and Starbucks. And then you basically have these data streams and Argyle featured at the centre of this as a central gateway. So I think it’s a, it’s a great picture that that sort of interesting, it’s almost artistic and you want to learn more about it. And then really going through it the first sentence, Argyll is a gateway to access employment data, I think it’s a good first sentence. The second sentence is basically the Uber for x section where you say similar to plaid, how plaid changed the FinTech industry by opening up access to financial institutions, Argyle is doing the same with employee databases. And so it’s it’s very helpful for the venture investor because they have a benchmark transaction plan. Everybody knows plaid knows it’s a huge success. And they know plaid has been opening up these dark pockets of data. And it took a while for them initially scraping. But the basically, this is a similar attempt, and it makes it an interesting read. And then it goes on. And instead of doing the typical tam slide, which is, you know, mostly times we know, you look at you know, macro reports on what’s the market size, and you, you do the top up bottom up tam market sizing exercise, but what you do, and I like that quite a lot as you talk about use cases. And if you have four different use cases there, you start out with the one that I think was the original sort of inspiration for Argyll, this automated form population. And instead of just having a small blip, and then leaving it to the reader, you go back and say what’s the current state of affairs? How does it work? And then what does Argyl do, and it makes for a very interesting read, because it takes it back to first principles. And as a venture investor, you want to engage in a conversation with you, just for the mere sake of learning more about this space, because you show cast in this investment moment that you’ve researched the space, and that you can bring value to that investor and and just for that matter, I think it’s something that probably got you a couple of first meetings, maybe talk about this first use case section.
Shmulik Fishman 12:25
Really powerful narrative device when talking other people, whether it’s an investor or client or team or prospect, team member or prospect is to be relatable, to talk about something that someone else can relate to. So they can empathise with your story. And they actually say, Oh, I have part of that story within me as well. And the reason why you want to use analogies like plaid, or analogies like a pay stub, as we were talking about earlier, we’re just digitising a pay stub is because of the things that you can attach yourself to where you’re not inventing something whole cloth. It’s very hard for anybody to buy into your vision or your story, if you’re talking about a world or something that people don’t know anything about, and they can’t relate to. And so it’s the reason again to that applications and autofill app is very powerful is we’ve all been through that experience of filling out an application or applying for a job and having that sensation of why am I typing this in for the 50th time. It’s a really good divisive way to drill into something and have people go down a rabbit hole with you because they can keep on saying yep, I know that. Yep, I relate to that. Oh, yeah. How can you make that better for me. And that’s the way you get somebody to attach themselves to your ID or to your story.
Erasmus Elsner 13:40
What I love about it is that you have attached to these different verticals or use cases, you have the potential tam still listed there as a very small note. And what strikes the reader is that this automated form population with which you started out is a 1.5 billion opportunity. But then it becomes clear what the broader market could be by looking at potential tamps there and there’s the real time income and employment verification use case I’m going to read what it says here. The current state lenders, credit card issuers, property management companies, the government, and employers themselves spent 100 million a year to verify an applicant’s income and employment. The current option set for the company seeking verification is to send a letter to the employer of the applicant or they can ask Equifax is the work number, T w n to generate the report. Both of these methodologies have shortcomings. And then what you do there, which is I think, the perfect way of capturing the attention of the investors you provide a very clear table with the different options currently available. And you benchmark yourself against that this approach that you can double click on different problem sets. It makes it very attractive. It makes it a fun and interesting reads not just for investors But for anyone, I guess, who wants to learn more about the industry?
Shmulik Fishman 15:04
So obscure notes there? One, it’s important to note that because we’re a data company, we have data elements. That’s what we had. If you think of us as a Ford factory, right? What are the widgets going into conveyor belt, different pieces of data. And the data comes live when it gets used for some purpose. And what we’re really doing in these boxes are in these use cases where if you compile certain widget, certain data elements together, you get a VoIP solution. If you compile another set of data elements, you can get an autofill use case, if you do it yet again, you can do direct deposit, but same set of widgets going down a conveyor belt, if you put them together in a different way, you get this package use case for a consumer. The reason why we did that way is it’s very clarifying for our team, for me, for the product team for the engineering team. Yes, we did this for investors. So it makes it easier to understand the business. But it also is very helpful to operate the business to understand okay, here are the data elements I’m working with, if you package them in a certain way I can offer this solution. This solution exists in market today, here is the value of this existing solution in market today. And that allows us to start to value our own enterprise, you are right, what’s called VoIP II are sometimes referred to income and employment verification, do you by the way just stands for verification of income and employment, leave it to American businesses to always come up with an acronym, but most businesses that runs some sort of decisioning logic, again, to that list of auto dealerships and rental agencies and mortgage processors, in all of those processes. Embedded at its core, is a verification of income and employment. So that is sort of a that is the wedge that makes the world turn from a financial services standpoint around the world. And so you are right. That’s the reason to I’ll make the joke, double click on that section as often as possible. I do think on the double clicking component, this is a great narrative device again, right? If you think again, about news articles, they have you go down these rabbit holes, where you click on another link, Wikipedia is a great example of this, where you click on a link to go further down that and then you can go back out to the main page. This is a really just great way to have concise ideas where you can give detail, but it doesn’t interrupt the flow of information.
Erasmus Elsner 17:22
Yeah. And I like how you list they’re really going back to first principles. Basically, I want to verify the employment, what can I do, I can go directly to the employer. Makes sense, I’m probably gonna get good data because it’s directly from the source, but it’s going to be a long and arduous process. Or I can look at, you know, how is it done normally today? What’s the industry standard? And that’s what you do there, you say, basically, you go to these credit bureaus. And I think this provides a great segue to talk a little bit about the broader industry and how it’s structured. Surely, it’s an interesting oligopoly, you have these credit bureaus, right Equifax, Experian, and TransUnion. And they’re privately owned, but at the same time, they’re highly regulated. And they are regulated by this great regulation called the Fair Credit Reporting Act, which protects them from ever being sued. But at the same time, their data and their data reports are so crucial for consumers when taking out loans and when interacting in the economy, that they should be public entities. And you should, you should have sort of ownership of this data, you would think and the ability to correct that. But the way that it is structured, currently is, is far from that, maybe as an expert on this gives us similar views on it.
Shmulik Fishman 18:38
So I’m going to leave whether they should be public or private to politicians. I think from a business standpoint, there’s so much to marvel at in terms of what credit bureaus have been able to achieve. It is very hard to have a business that’s worth a billion dollars and Equifax is worth 30. They’re doing a lot of things with a business standpoint immaculately well. And if you think about a long term view of how data is aggregated, pre internet, pre AI, a credit bureau is a really good business. If you have a bunch of employers and by the way, in America, last year, 9 million employers hate people. If you have a supply side of 9 million in the US how our financial institutions that need to verify employment, they cannot possibly call 9 million entities or have relationships with 9 million entities. That’s unrealistic. And so in that framework, having a central authority a central place where data is aggregated, stored, and then resold. That is a good formula. I’m going to use an analogy now. The Fed is very similar to a credit bureau. If you want to send a wire or an ACH The bank sends it to the Fed, and the Fed sends it to the next bank. And the reason why that happens is you need a central clearing house where everything could go to, and everything could be pushed out from the analogy continues, what is Bitcoin, but the removal of the Fed, you know, you now no longer need the central authority to transact, you can transact peer to peer. Why, because there’s technology, we can use a computer to find every node on the system. In a way, we’re just saying the same thing can now happen because of the advent of technology. Because the advent of the Internet, we now no longer need the central authority of a credit bureau. Nothing wrong with it, we’ll have that conversation about their practices another time, but need not have intermediary. Because you can now see every every part of the network, every node on the network. And if I’m Sarah, and I work at Starbucks, and I’m trying to get a car from the Toyota dealership, I have the two nodes. And with technology, I can connect them myself. I think really, that’s what’s at play here. That’s the shifts that we’re making. We’re just saying that you don’t need this middleman anymore to make these arrangements and have these relationships. Having said that there, there are a set of things about credit bureaus that we should all take pause, I do question things that are a black box. And what I commonly tell to people is that I don’t know the difference between a 650 and a 600, other than a 650 is a larger number than a 600. Other than that fact, you can’t understand why they are deriving the score they are deriving. And that should have us question What’s going on over there. Because if you bring everybody down to a single number, where you are somehow defined by this one number that you don’t have control over, if you don’t know how it was given to you, that’s a lot of space for bad things to happen. And when you give power back to the individual, and to the other business, to be able to make these evaluations themselves able to share their own data. That’s the place where better things happen. Transparency and flashlights are normally a good thing. And I’m proud that we’re on that side of the line. I think
Erasmus Elsner 22:09
what’s interesting, and you touched upon that is that, you know, credit bureaus, they gather information from all of these different data pockets. And this brings me to the next section in the memo, which is about the the technical modes that you’re building. And I think you have this great graphic there where basically, it shows different integrations that you’ve already accomplished, starting with tranche one, which is the gig economy. So getting data from Uber from Upwork, then trounced to which you also accomplished with a seed round digitally native companies like gusto and rippling. They’re where you get an API, and you don’t have to sort of scrape through the data or try to clean the data, but you get pretty clean data upfront. And you talk about how the next step or the purpose of the series A is to integrate a couple of other tranches or data pockets if you like, and it makes it very visible and concrete, what you’re going to accomplish in the next step of the company. And I think the purpose was basically to integrate tranche three and tranche four which are deskless, workers, and knowledge workers through you know, companies like Workday, or Upwork. I see here.
Shmulik Fishman 23:22
So I get asked by our board and by investors, and by clients all the time, about our roadmap, they say, what’s on your roadmap, what products we bring, and I’d say the same thing as we were yesterday and the same thing we are tomorrow, we build access, the only thing that we do is revoke this one thing called access. And in the United States, there’s 20,000 registered payroll service providers, which means the IRS has recognised 250,000 systems that are legally able to generate payouts. So you need to plug into all those databases. We’ve outlined a set of tranches for our own sanity on how to compartmentalise all these different variations of pay systems. And we can all go through the ones that we know about like ADP and paychecks and PAYCOM and Paylocity. Those are the names that are easy to know and, and frankly easier to integrate into. But there’s also something called 101. Right? And there’s many more iterations of that if you really start thinking about this, we’ve expanded our tranches quite some since this document tic toc is a way to get paid. YouTube is a way to get paid patrons way to get paid. Any system that pays you theoretically is a system where you are making money and you’re employed by that contractor or employee. I’ll let the regulation for somebody else and so we we do these tranches to keep ourselves honest about where we are in terms of building out connectivity and to make the world a little bit easier to understand. I will say that this level of granularity in terms of tranches is too complex. For even the even the most technical of client unfortunate no one should know I do that. I need that starbucks.com is how a Starbucks worker gets their pay stub in one.walmart.com is how a Walmart person gets their pay stub and partners that convert.com. This other Uber driver gets their earnings. Run dot Walmart adp.com Is the ADP one. This complexity is the reason why Argyl exists because no one should know that I shouldn’t either. You should have a system that understands all these different tranches all these different types. And the only thing you need to be presented with is how do you get paid? How do you make your money, who pays you, you type into your employer, we’re going to figure out the rest. That is the promise we’re giving to our clients and to those end users that we’re going to bury all these tranches all this complexity, these 250,000 registered payroll service writers, don’t worry about that no phone calls needed, you don’t need a credit bureau just type in your employer, we got the rest of it. And that’s we’re making an outline of if you want to go one level deeper than that sentence, this our system is architected it, it goes to your point really well. The moat is this knowledge, right? Understanding the connectivity between 20 or 30,000 registered payroll service providers is proprietary, it is hard to replicate very hard to understand very hard to have done with high levels of throughput. That’s the moat, the fact that we figure this out. So you don’t have to,
Erasmus Elsner 26:22
you have this great section in there that the credit bureaus spend 70 years to get to 35 to 65% coverage of the market, and that you are basically doing all this plumbing. Now. One question I had was, to what extent are you standing on the shoulders of giants here? In the sense that you are some of the first integrations you did where was digitally native companies, right, who had a decent API that you could plug into with this company, be able to have been built, say 10 years ago? Or is this really also in a sense this, you know, the quintessential why now slide that now you’re able to do these integrations, because you have enough advanced API’s on the employer side as well.
Shmulik Fishman 27:06
I’m proud that we are able to crib and take note from other wonderful technology companies and from other massive trends that are taking place. I’m a huge fan of Kirby’s work. It’s called Everything is a Remix. And you bet we are re mixing a tonne of things. So the idea that you can have a list of employers is like plaids idea that you can have a list of financial institutions, the idea that we can have global connectivity into any place that people work is kind of like Twilio, this idea that you can send a text message globally around the world. Our ability to move fast is our ability to learn about others. I’m really proud that we’re able to do it and collaborate with others. The part that we are doing that no one has done before is aggregate employment data. Twilio does not do that cloud does not do that. So that’s the part that is different. And I will say to original statement around taking 70 years to do what Equifax has done. The reason why we’re able to do it much quicker is not because we’re smarter than Equifax. And it’s sure surely not that we have more money than Equifax. And it’s surely not because we have more engineers or team members than Equifax. In all of those instances, Equifax wins many times over. The reason why we’re able to do this is because we’re using the internet and Equifax uses a phone to different tool, and the Internet moves faster than a phone. And
Erasmus Elsner 28:27
you have this sentence in there. Our moat is this brute force endeavour, constrained by the number of developers who are committed to the project to give us a sense, you know, if you do a typical API integration, how many engineers do you need? I can imagine for a digitally native employer, it might be, you know, one person and takes them half a day. But then in some of these more complex API’s, it’s a whole team.
Shmulik Fishman 28:53
You don’t know until you start. That’s what Andreas and me have learned after doing this many hundreds of times. And the some of them are not obvious. You would think Uber would be very easy. It’s a modern platform. It’s API built, it’s made by other Czech people. It’s very hard. They update that system daily, and we need to make sure that our plumbing is compatible with their updates. There is a maintenance effort on Uber is very high. And the engineering effort on Uber is very high. It’s a huge system. Go on the other side, Kroger never updates their system. The maintenance effort is extremely low. We built the scanner in under a week. It’s a very simple thing. It has Oracle HCM on the back end, that thing never gets updated. The system goes down from 1am to 5am. Every night, same time you set a clock it does it right. There are so many different ways that these paid systems are built. And the only way to figure out how long it takes is to start integrating with it ever really smart engineering team. That’s what we’re talking about, like people committed to the project to look into investigate and done Understand how to use the tools that we’ve built on other integrations on the integration that they’re building. And the truth is just like with Twilio, there is real maintenance time on every integration rebuild, there is no idea of integrate and step away. That’s not a thing. Every integration requires consistent maintenance. Just like every Twilio integration to every ISP also requires consistent maintenance.
Erasmus Elsner 30:24
Last question on this, which you’ve probably been asked 100 times, plaid is famously known for having done a lot of screen scraping in the early days before the banks opened up their API’s for them. And as far as I can tell, and you use the the term scanner and not scraper, you’re not doing any screen scraping, you’re, you’re actually plugging into API’s or doing what you’re calling scanning, right? Sure.
Shmulik Fishman 30:53
If I serve calls them harvesters, just so you can get there’s a lot of ways to describe this. If you ask an engineer, what is scraping, they will say that you render an HTML page, and then you have some type of automated system, read that HTML rendered page and pull out information. Under that definition. We don’t do that. We do not render HTML. There’s a lot of reasons why, from a technical perspective, it’s inefficient. It’s also really slow and unreliable. Every web site that you’ve ever gone to, whether documented or undocumented, is powered by an API. That is how the images show up in the right place, there is code that governs the placement of all the things on that website. If your skill did up, and you take the time, and it is more time than rendering HTML, you can look at the code that renders web pages and you can interact directly with that code, just like how Chrome does. And that is the technological way that we interact with all of these systems, we interact with the system, but with the code base that it has, on its terms, it’s a much more reliable and robust way to code. It also doesn’t get the ire of scrapey the way that it does by the industry. Again, back to that analogy, though, the way plaid did it and the way Equifax does it, right. If you’re going in through a phone call, it’s going to take 70 years, right? There’s definitely no legal concern on this. The question is, Do people understand the different methodologies at play to retrieve access to get data that is requested through the different means that are available phones, or internet are in that mix?
Erasmus Elsner 32:35
Very interesting. No, I like that that level of detail went to there, maybe on a higher level note, now going back to the traction slide in the investment memo, and most of it is blanked out in the public version, but you have the basic business metrics, we have the charts there that go far to the right, talk a little bit about traction and where the traction was back then how far you are now, and sort of how to founders should talk about the attraction.
Shmulik Fishman 33:04
So I always think about financial metrics, KPIs, these, these data elements that you’re given on your business, as both a way to value a company, right? The more transactions that you have, the more valuable it is, the more revenue you have, the more valuable it is, the more clients you have you keep going. But more importantly, I think that these KPIs, say a lot about the executive team and the founder team about how they look at the business they’re building. Because depending on what metrics you pick, right, we pick a metric like number of connected users. But we actually pick the metric of number of connected accounts, not users. This actually says something about how we’re looking at the business. We are not putting value or monetary association to Sarah. We’re putting monetary association to Sarah’s Starbucks account. And this is important because this says that we are interested in making sure that this Starbucks account is value. Not that Sara is that we’re making money off of Sarah, and these things matriculate themselves. Do you think about what metrics you’re talking to investors about? And I think that while investors don’t say that a lot, there’s a difference between? Are you talking about monthly revenue? Are you talking about arr? Are you talking about booking So figure out what metrics you want to use when you talk to investors because they’re taking notes about how you value the business. We don’t release our revenue numbers publicly. We’re a young company, but we’re public. We will but we last year, we regrew 800%. Now, the fun part about these metrics is we’re off of a low base, but this business is scaling quite rapidly. We some other metrics, just to bring us to 2022. We had about five clients at the beginning of the year, and now we have over one. So there definitely is a lot of scale happening here. We’re still at the very, very beginning of this journey. If you think about all the different institutions that run verification, or leverage income data, we’re effectively at Z about any number that doesn’t have, you know, it least eight zeros, you’re not really playing with Equifax
Erasmus Elsner 35:06
super interesting on how you talk about choosing the right metrics, whether it’s you know, financial data, but it can be something completely different, like the number of records downloaded you had there and the number of connected accounts, which are non financial metrics, but which can be leading indicators, and might be the better metrics, right, I want to move on to another aspect that you touched upon in the investment memo, which was around pricing, and pricing, it’s super important for any data business. And you described it in the manner that you were basically doing what the incumbents are doing at the moment, you’re charging on a data pull basis. So an API based pricing model, but you also mentioned there, that you might shift to a more subscription based revenue, and obviously rings bell in every SAS investor, they think about recurring revenue, they value recurring revenue higher than one off transaction based revenue. How do you think about this pricing page?
Shmulik Fishman 36:06
So back to what we talked about the beginning of this clients, like analogies, people like things that are familiar to them, if you’re trying to have a client, do something differently, they’re taking pay stubs today, you’re telling them, You can do that differently, they’re taking bureau data, you’re telling them, You can do that differently, you should look at how those products are being charged. And those products today are charged on a transaction basis, when I want to know somebody’s income, I get charged, or when an update, I get charged. I don’t think that’s the right way to do it. But I’m not the person that made it up. So I need to back into the current way that things work. So we’ve done that when you connect an account, you get charged from a relationship standpoint, it’s not transactional, I have a relationship with Sara, that means you want to charge that way. And so you, what we’re doing is we’re giving an entry point for people to start from a transactional basis, and we’re leaning them into a subscription service, where instead of being charged every single time you want to update, you get one fee, and you get unlimited updates. Don’t even think about the transaction thing, you’re just gonna be charged one thing, and you can ask these questions as often as you want. You’re not penalised for them. You don’t have to run calculations on how often as a side note, I’ve talked to many publicly traded companies that process huge volumes of VoIP runs. And what I find just immensely interesting is large financial institutions have come up with very sophisticated algorithms to optimise VoIP costs. They have things like in the state of Texas, if you’re over 50, and you’re male, I’m going to do the run 2.3 times. But if you’re a female, and we’re doing at 1.8, this is an immense amount of work, all to figure out how many transactions I want to be charged for, instead of just saying, I have so many loans in the market, here is the price per low to get the data on it. That’s the better way to do it. But because everybody’s on this transaction model, they’re doing all this unnecessary. So our pricing system is about understanding the world that is this date, and trying to move people to what we think is a better pricing system, but also for them and their consumers.
Erasmus Elsner 38:18
What I love about it is that again, you opening up a conversation, you’re not just saying this is how we do it, we figured it out. But you’re basically saying, I’m open to learning, exploring and testing a couple of different drugs, right. And then the last aspect, which could be the first aspect in many instances, the Team Read. And it’s an interesting topic, because you were a remote first company, way before remote was on everyone’s mind. Right, you and your co founder you started when you moved from the west coast to New York, and he moved back to his home country in Europe. And you were a remote company by design. And first of all, you addressed this front and centre so that people understand why you’re doing it. But then you also talk about hiring and how you have a special hiring strategy. If you want to find someone new that they should bring the three brightest individuals they’ve ever worked with, and help you with recruiting they’re talking about having think about team and building team and especially building team remotely.
Shmulik Fishman 39:21
The most crucial part of getting a successful business is getting a good team. If you have really smart, bright, capable, interesting people that are working with you every day, good things will take place. It’s really hard to get correct, but it’s the most important thing to get correct. So we focus on it a lot at Argyle, particularly because we have over 150 team members now in 23 different countries. So we really invest a lot into our human infrastructure, how we interact with each other, how we talk with each other, how document meetings, how we have meetings. This is really important to having really good culture and for there to be a sense of camaraderie. I’m really proud of all the different time zones we operate in. And we operate in nearly all of them. Because it leads to this true diversity of thought there are actually people from all over the world really working on our dial right now. And it really will set the playing field where just because you’re in San Francisco doesn’t mean you’re in control. And just because you’re in New Zealand doesn’t mean you have no control. Everyone gets to operate on the same infrastructure, the same decision making authorities. And it’s a way better way to work. It’s you have to take a leap of faith. But when you’re on the other side, this is way better. In terms of how we recruit, the reason why we’re really interested in you bringing people you go, is it makes it a lot easier to onboard them. I’ve had the experience, far too often of starting your job, it’d be not knowing anybody there. And the first couple of weeks are really hard because of that. But if you start your job, you’re like, Oh, I know, Joe, I know Sarah, very your buddy for the first month, and they get you involved in projects, right? People like being here, because their friends are here. Again, getting smart, capable, bright, interesting people to be at a company is what is most important, this is part of it. So we try as much as possible to have it be that you know, other people hear from other jobs or other projects before you start.
Erasmus Elsner 41:21
And I think it’s great that you address it front and centre also in the investment memo. I mean, I had said sobran G from GitLab on the pod. And he was also very early to that, yes, he told me how sort of the venture capitalists would assign a discount to being remote. And so I think it’s something that if you are remote, you have to bring it up early, and you have to discuss it.
Shmulik Fishman 41:44
And it’s important on this one, be proud of what makes you different. I think a lot of companies that have a part of them that are remote, try to push it under the rug, because they’re scared to your point that I’m gonna get a discount, people are gonna think I’m less valuable, less cool, because I have a remote part. If you think that way, that’s how they’re gonna feel. But if you if you were it is something you’re proud of, you’re better because we’re about we build better products, we have a more diverse team because we’re remote, then you’re using it as an advantage. And investors will feel that too, that you’re saying that this is actually this is something that you use as a way to get ahead of others right, then then you get you don’t get a discount, you get a premium.
Erasmus Elsner 42:26
Absolutely. I think that’s, that’s become more and more true, especially now that the pandemic has been the fire test for this matter. So, so Shmulik as we’re running against the clock, I want to talk about, you know, 2022, what’s under your mind, what do you want to build what you want to achieve with Argyle? And where can people be in touch with Argyle and follow what you’re up to personally?
Shmulik Fishman 42:49
Well, my email address is email@example.com. So if anybody wants to, at this point, at this point, I understand what my inbox is for. For us. This is first this year is the year where we move our product from development to rapid use, we have spent a considerable amount of time and energy and resources to make a very proficient system, we can now process transactions at scale, our conversion rate system wide is in the 70s. That is a very performance system. It takes a long time to build that. And frankly, scaled financial institutions are not going to use anything less than that. And this is the year where we’re going to take our performances and be able to offer it to publicly traded businesses. And so I think you’re gonna, you’re gonna see some news around that, again, back to what we build, we build access. So anybody asking us to build a new widget, or something very sexy and cool, we build assets, we do want to make sure that we’re investing in securitized experiences, where consumers feel safe about moving their data through our tools. And so we’re investing a lot in that and we’re also investing a lot in making this experience as slick and as simple as possible. Right the difference between 15 seconds and 14 seconds is real and any client we talk to really wants to shape up every second of the experience to make it as optimal as possible. And that is the as GABA I had a product says that is the art of 1000 arrows hitting a target. So you need to get a lot of things right just to get one second to be optimised and and so we’re working on touch on that as well.
Erasmus Elsner 44:25
Thank you so much Malik for being with us here today. Very complex business model, but I think it’s it’s not solving. It’s not a vitamin but it’s a painkiller kind of product. So excited. Good stuff, and looking for follow the journey. Thank you again.