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- [00:00]
A
This founder had human beings do the work of AI. Humans answered questions, uploaded files, organized financial data. It helped to raise $20 million for an AI based accounting software company. Copy her approach. Helen Hastings is the founder of Quanta Accounting Software that works fast because it uses a combination of humans and AI backed software. Helen, the interesting thing about you is that you basically had humans do AI in the beginning. How did you do it? Give me an example of something that a human being did then that today AI is doing because you noticed it back then.
- [00:37]
B
So we saw people just reading a lot of human written text is the biggest example of how AI has made a difference. So imagine you have purchased something with a corporate card, or maybe you need a reimbursement. You have to put a memo on that into your company's expense system. So that's just human written language. And this is something that bookkeepers were reading and then figuring out what it meant. And LLMs are very good at that. That people think that accounting is just numbers. Actually so much of it is just understanding what's going on in the business and so much of that is actually human written.
- [01:11]
A
So the example that you given me before was you said, look, there would be a human being that would see a bill come in from Amazon and analyze it and say, this is not an Amazon purchase, it's an AWS purchase. It's still the same company, but clearly those are two different buckets of expenses. And a human being would analyze it and then do it in the beginning. Right. And then eventually it was actual LLMs that were doing that kind of analysis.
- [01:35]
B
Yeah, exactly. So one reason that traditional bookkeeping tends to be so painful is that it's often outsourced to people that are maybe overseas and they're great, but they just don't have the context of what our software business is doing and what are the vendors that they're using. So. So they don't really actually understand the difference between I used Amazon to buy the coffee maker and this is my AWS bill. And that's even a company that's been around for a long time, aws, but they can't keep up with the very new vendors as well. So when Quanta inherit books from other providers, we see all of these things miscategorized. And it's actually very simple for us to get that understanding based on what we see as the memos and what we see as the receipt content and invoice content.
- [02:26]
A
Okay, so let's go back to even before you were doing this all by hand. As soon as you had the idea that you wanted to do this, you decided I'm going to go and shadow companies. Who did you shadow?
- [02:38]
B
It was really a wide range of just bookkeeping firms and bookkeepers that were working with a wide variety of companies. So like for example, someone who did a lot of bookkeeping for truckers and one off sole proprietors as well as firms that were working with venture backed software companies as well.
- [03:01]
A
So they just let you walk in and look at how they were doing their books so that you could create a software company that would do what they do.
- [03:09]
B
Not quite. This is very much user research phase. And you know, a lot of these companies are, they're looking for better software too. So they're looking to work with, with people like me who are interested in coming and saying hey, I want to build software here to, to make everyone's lives better. So it's. Yeah, Silicon Valley tends to be just a very open place also. And that's one thing I really like about that is I mean I chat with competitors and people believe in just the more we share the, the more everyone will learn and get better.
- [03:45]
A
You know what, that actually is a great point. I don't see this happening in the way that you experience it in many other cities where you can just go in and say, can watch what you're doing. Can we talk as competitors? Can we have lunch? Can you introduce me to people? Okay, so you said I'm building this and I'm assuming also your background from Stanford to Google to NerdWallet to a firm, I'm assuming all that background gave you the legitimacy and the credibility for them to invite you in. What are some of the things that you noticed when you were shadowing these accounting firms?
- [04:14]
B
And, and yeah, the background, I feel it was definitely helpful and I feel very lucky that so many people were just willing to talk to me in the user research phase of starting Quanta. I was just full time going through LinkedIn looking for finance managers, accounting managers, accountants to talk to and learn from and just ask for favors repeatedly. And was hard at the beginning but once I got in the groove of it, I really don't know how I would have started this company if I hadn't done that. So people, yes, they do see the background and that's helpful and I think I would recommend to a lot of founders out there just, just do that, just do all that user research. And to answer your question, it was.
- [04:58]
A
Cold messages on LinkedIn and cold emails and I'm assuming also some friendly introductions and that's how you got meetings.
- [05:05]
B
It started with warm, so it would be searching on LinkedIn, here's the title that I want to talk to. And then seeing do I have any mutuals with. With this person? LinkedIn is great for that. And then reaching out to the mutuals and saying, hey, I see you're connected to X. Can you please connect me? And they often would, because I knew them and I'd worked with them in my career. And then when I had that call with the person, I said, who should I talk to next? Who do you recommend? And then that is how I ended up talking with different firms and people doing this work in reality. And it just, it compounds. The more people you talk to, the more you meet. And that is how I got all the learnings that I really needed to to start this company.
- [05:48]
A
All right, before we started recording, you told me about some of the manual things that you saw that you said, wait a minute, software could really do this. Humans should not. What are some of those things?
- [05:57]
B
I think the, the biggest example is just how much time is spent logging into a financial tool, downloading some sort of data, massaging it, and then uploading it into a traditional accounting system. That is so much of what bookkeepers are doing today. And there's just plummet.
- [06:15]
A
Sorry to interrupt.
- [06:17]
B
So plaid isn't 100% accurate. I will say that we use a mix of Plaid Infinicity and other tools. But the best is when companies have APIs where the data is coming in. Well, the reason that Plaid isn't enough is that there's always small things that are missing and there often isn't enough data to really understand what was that big transaction needs to be augmented by a receipt or some sort of understanding. And we would often inherit books or see books where, yes, there was a Plaid connection, but the data was just off. And we have just built this really great understanding of all these different banks and we've been able to augment it. And yes, a lot of bookkeepers would just end up saying, we have to go and log in anyway because the data coming in through the best temp automation just wasn't cutting it.
- [07:06]
A
I'm shocked by how many bookkeeping companies I've used over the years that have done that. They've asked me to give them access to the CSV. They have gotten CSV files themselves. It's so frustrating that that's what they're doing. Okay. And so you noticed that and you said, okay, I definitely could build software that would do it. I get now that you understood what can be done. Why did you decide that you were essentially going to build a QuickBooks or zero replacement instead of saying this exists? People have tried to unseat them for years and I'm just going to build on top of them.
- [07:39]
B
The biggest limitation to everything I just told you about was actually QuickBooks. So for example, the Plaid connectors that everyone uses had all the problems that I just talked about. The ability to automate things in there is just so limited. And a lot of that is because it's trying to do everything for everyone. I mean, the market penetration of QuickBooks in the US is just crazy. And because it works for all small businesses, that means it's not specialized in any. And because of its limitations, there's so much manual work that is needed. So it was actually essential to me to say we're just going to build this for the ground up or else we're never going to be able to deliver on on our thesis. And then also, really the reason I started this company is I'm a software engineer who has built a lot of ledgers. That was what I did for my entire career in fintech. Building financial systems of record is the word that we use. That was my specialty and that was what I saw as the opportunity. If we can build the financial system of record for businesses from the ground up, we can solve all of this pain that I've been seeing that has been caused by just the limitations of that existing general ledger software.
- [08:48]
A
Would you give me an example? Like what couldn't you do with QuickBooks that beyond obviously the plaid connection that we just talked about.
- [08:56]
B
So one classic example is anytime someone changes something, all of the properties of the system are messed up. I could go in there and create something in QuickBooks that just changes the bank balance of my bank. And that's one reason the Plaid connectors only go so far, is that someone just makes some little edit thinking that they're doing something else. Suddenly my bank balance is wrong and my source of truth is wrong. So we've built something that enforces that edits are only made correctly because we're reconciling continuously all the time. And something that can track changes, changes of all different types, to know what is the history of what happened. So every change comes with the understanding of what happened here. And only good changes sort of make it through that reconciliation process.
- [09:45]
A
So that's why every time I go through my monthly check in with the bookkeepers, they always will say, I'll see something and I want to go and change it. They'll say, no, no, let me do it, because I might, in fixing it, screw everything up.
- [09:57]
B
Exactly, yes. And the way QuickBooks is set up is it just makes it really easy for, for you to make those mistakes because it doesn't have all these checks built in. It's really just sort of a blank slate you can write into. And the only way to verify that the data is correct is people manually looking at it. Versus, the thing that we've built from the ground up is checking itself all the time. Redundancy is a big thing that we talk about at Quanta. You need to have a bunch of redundant checks and they're running all the time to make sure that the data is accurate.
- [10:28]
A
For example, like what's a redundant check that catches? I guess it's the balance in a bank account. Right?
- [10:34]
B
The balance in the bank account is one. And then are all the transactions in the bank account matching what we see in our system? So that's two pieces of data that if one is right, this one is right, this one's going to be right. However, we should do both of them just to make sure. And then also, are all those bank transactions matching some other system? Bank transactions, usually in a vacuum, aren't the only piece of data. They're usually linked to something else. So. So for example, from my payroll system, I see that a payroll ran, and then in my bank I see that the money moved to run that payroll. We match those things together and make sure that they're consistent. And QuickBooks does not do that, but we built that from the ground up in our system.
- [11:15]
A
All right, let's go back even a little bit. Before all this, how did you know that this needed to be built? Where did you get the idea?
- [11:23]
B
So in my past job before starting Quanta, I was a software engineer at a firm, the Fintech and Lender. I was there for almost six years, joined when it was around 100 people. Got to grow it through over 2,000 people through IPO. And really all I did was build ledgers there. And I was building ledgers before I even really knew anything about accounting. But just the way we built things there was double entry ledgers and it just made sense. If you're running financial systems, if you're keeping track of balances and where money is and where it's owed and, and where it's moved and where it's moving, you build in this way, this immutable way of tracking every single change. And I saw that when you built in this way, you Solved a lot of pain and just understanding the system. And then I worked on the first iteration of Affirms in house accounting ledger and it was piping into netsuite, which is another just the dominant ERP right now. But the source of truth for all of the core foreign data was going through the in house ledger that we built. And I saw the limitations of existing systems and I saw just the lack of clarity that existed before our team worked on this. And I thought for a bit maybe this is just an affirm problem, maybe this is just a complex fintech problem. But then when I was doing user research after I left a firm, I thought actually all companies have this problem. They don't have visibility into sometimes just basic questions. How much money am I making? How much do my customers owe me, how much do I owe to others? And the root of it is the limitations with the underlying tracking of the finances. And I wanted to solve that problem because I saw if we do this there will just be so much pain solved in just understanding what is going on in your business. The core of it is very basic. There's really just no visibility right now. If you are waiting until the end of the month to understand what your finances are, the time has already passed to make the decisions that are important. You related to making decisions on a day to day basis and that requires understanding the fundamental numbers of your business.
- [13:40]
A
Yeah, those are the two things that have really made it easy for me to understand why people are working with you. The first is with most bookkeepers it takes at least until halfway through the next month before they're done with the month. And sometimes it takes you a little scheduling time. And so you're basically about a month out from what happened. And I always wondered why they couldn't get it done faster, especially since I'd interviewed so many people whose whole thesis was software can do a better job than bookkeepers. So that's the first thing. And the second thing is when you're trying to answer a question, it is so hard to get that answer from software that you have to go to a human being who did the books and find out like little things like how much are we spending in software? Well, we got software in all these different buckets. Let me go and add that up. And that seems like the two big, the two big exciting parts about this.
- [14:29]
B
Definitely. I mean it's even more than a month often. So it's just we're recording in early December right now. I mean, I talked to companies that do not have their October data Yet because their outsourced firm starts on their October data towards the end of November, because they have just a long queue of clients. The thing is, once you're doing something manual with humans, you're not doing it every day because that you just don't have enough humans to do that. So suddenly there's a long list of work. So as soon as something is manual, you are doing it on a very long time delay. So if you happen to be at the bottom of the queue, and sometimes the outsourced booking being firms charge you more to be at the top of the queue. So if you're at the bottom of the queue, they might not start on your data until the end of the next month and then to finish it. So it even sometimes is longer than just a month and by the time you get that information, it's just not useful at all. And we've really changed how companies see their financial data because if it's two months late, it's just useless. At the speed that startups are going, you can't be operating at that pace. But once you have it available to you and close to real time, you're actually looking at it and using it to make decisions. So it's interesting how some, with some of our customers, they used to see the bookkeeping as just something I have to do. It's around tax season, but now we've changed it into something that's strategic because you have data that you need to make decisions that are critical to your business.
- [16:00]
A
Okay, so first thing, you're discovering a problem, a pain, and you say, okay, I think software can do this, especially the way that it is today. The second thing is you're going and you're evaluating. You're shadowing people who are doing it already to see, okay, what are they doing that they may not be noticing. That I think is an opportunity for us. Before you do it yourself, do you validate, do you go to small businesses, do you go to startups and say, if I build this, would you be willing to pay? Or do you just say, I see enough of a problem, I'm ready to go?
- [16:25]
B
Oh, absolutely. I recommend to any founder, ask people if they're willing to pay for something. I think it's essential to start a business. I mean, you definitely need to trust your guts as well. But understanding how customers think about things is so important for go to markets. So there's one thing to say, I know this product is going to solve pain. And it's another to understand how do people perceive it and how do you talk about it such that they are going to purchase it?
- [16:53]
A
Okay, how much did you get? Like how much financial interest did they, were they willing to pay? Was there a story of somebody who said, let me wire you now?
- [17:02]
B
Yeah, I mean we, when I was talking to people, they said, yeah, I would, I would do this. I would totally switch over from my existing paper to just having them say.
- [17:11]
A
I would is enough.
- [17:13]
B
Yes, yes, that's a hard one because.
- [17:16]
A
Because you're taking on their full books, people would say sure, if you can build it. But you know there's always going to be some edge case, some little thing that they need that they have in QuickBooks, like access to the ability to give their accountants access, the ability to give their bookkeeper, all that stuff.
- [17:31]
B
Well, that's one reason that the, the hybrid software and services model is a great way to get started on a business like ours. Because that last mile edge case we do have humans do and it's helpful for onboarding and understanding the our customers, businesses and they also like, they want that peace of mind if there's a human as well. So we're able to automate the vast majority of it. But they have someone to talk to who has a CPA background and works at Quanta. And knowing that we can bridge that last mile edge case with that human in the loop process, which by the way is such a standard way to build software in the AI era, especially in this tech enabled services industry, it just gives us the confidence that let's just get off the ground running, working with customers as soon as possible because we know that we can bridge that last mile and then over time it gets more and more and more automated.
- [18:27]
A
I see. And if you could just give them, I guess, Excel spreadsheets with their data that that's enough. Is that what it was?
- [18:36]
B
I don't think there's been a time where we've just handed over an Excel spreadsheet of data the last mile. Things that we were doing mainly from the beginning were just like looking at the data ourselves before our engine could process it and handle it. Or maybe a new financial tool that we hadn't built an integration yet or we didn't understand. Or maybe you are using the latest type of payroll system and a new payroll provider and we hadn't built the understanding of it and automated it yet. That was the thing that we would bridge manually in the meantime and have engineers do that too and have me do that. And I think that, by the way, I think that's the best way to just build a great product, just really see the dirty parts of it instead of just handing it off to someone else. But we, in terms of just doing it in spreadsheets, that, that's not something that we wanted to do. It's been important to us from the beginning to have it all within the Quanta platform. But sometimes we would manually get the data in there to start, but once it's in there, it's in this well understood system that we've built that unlocks understanding for our customers.
- [19:43]
A
You know, when I, I interviewed the founder of Zenny, that's an AI bookkeeping company, this was back in April 2021 and I thought it's so compelling. But at the same time I had a hesitation. I said I don't know that I want to trust your software. And what the founder said to me was, you know what, worst case, you still have everything in QuickBooks so you can always switch us out. And I said, okay, that's a reassuring thing. That's what I meant with you. Was there any kind of backstop there in case people didn't like what you were doing?
- [20:12]
B
Sure. So by the way, we get this, the trust problem all the time. It's, it's so enormous in accounting and, and we still get it every single day. We actually recently announced our series A and announced a product which is agentic reporting. So it can really answer any question about your business. And I got so many messages that day of this is fantastic. Does it work? And if this works, I will buy it. But they don't trust that it works yet. It's almost too good to be, to be true. So it's, it's, this is a big problem in, in the AI era I think is these too good to be true problems? But when it comes to the, the QuickBooks and bookkeeping, actually we do have a product that we call a QuickBooks backup where if you for whatever reason want to do an export into QuickBooks or even keep a QuickBooks up to date, we support that. And it's a good way to get people in the door. Especially we work with a lot of companies who have had years of previous bookkeeping history and then they come to Quanta and they're kind of afraid to give up their QuickBooks and I think they should be. You think of companies like Bench going out of business and people have no access to their history of the most critical business data. So I definitely understand that there's that hesitancy. So one strategy that's worked well for us is saying, you know, we'll keep your QuickBooks up to date for you. Quanta becomes the source of truth. You can't touch the QuickBooks anymore because that would mess with all of the properties of our system that I was discussing earlier. But we'll let you keep that up to date, keep that live with quanta data as if someone was keeping it pristine from the beginning. But then we find that our customers will often just shut it down after they realize, okay, I don't need this anymore. Why should I pay for this system on the side?
- [22:00]
A
So funny. Like you mentioned bench. They I'm pretty sure were a sponsor of mine because bookkeeping is so popular. So they sponsored then all these companies I'd worked with in one way or the other. Pilot I think was a sponsor and I really loved what they were doing by adding automations into QuickBooks. I invested in Indero, I think it was the first startup I ever invested in. They were going to replace QuickBooks which at the time and still today I can't stand. I hate QuickBooks. But then there are all these issues with it. They eventually all seem to come back into QuickBooks. And the one company that survived is I interviewed the founder of Zero years ago and for some reason they're still around. I don't know what the difference is. Why, why are they around? And then I'll ask you about getting into the space where everyone's dying. Why do you think Zero survived?
- [22:48]
B
So Zero actually has a great market penetration outside of the US So they were founded in New Zealand actually and their international support is, is really incredible. So they, they're very popular in other countries. QuickBooks is the dominant player by far in the US but Xero has a great international footing. So I'll talk to some US companies that use Xero just because they started in another country or the person managing the books was from another country.
- [23:16]
A
And so what do they do differently? They work for other countries.
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B
Really. I think so much of it is about just knowledge, right. Mindshare people know about it because it is just dominant in that space. And every country has a little bit of difference in how do you set up what, what categories the tax authority in that country really cares about because a lot of the early stage bookkeeping is it's an input into tax. And because if your tax authority is different as it is across different countries, then maybe you want to structure things differently.
- [23:53]
A
Okay. Yeah. They also, I think were cloud before QuickBooks was fully cloud. They also did the thing QuickBooks is.
- [24:00]
B
Still not even fully Cloud. Who's funny? I think so. A lot of people still use QuickBooks Desktop. They will go buy. Yes. I think they might have started deprecating it very recently and it was a huge deal. A lot of people were up in arms about oh no, QuickBooks is saying that they're going to start not investing more in QuickBooks Desktop because people do assert that QuickBooks Desktop can do more than QuickBooks Online. It's funny, the acronym that everyone refers to for QuickBooks is QBO. Yes. The O stands for online.
- [24:35]
A
Yes.
- [24:36]
B
And that just shows how dated of a product this is. Is that the word that it's online is such an important characteristic of the company. Right. But I talked to so many accountants and bookkeepers who are just love QuickBooks Desktop and assert that it is better than QBO QuickBooks Online. And again, I think it just, it shows how dated this industry is.
- [25:00]
A
I'm going to be one of those people. I actually think if you're doing it individually and you're not trying to collaborate with other people, their desktop has less of the garbage that all of their online stuff has. And I understand why people would want to get rid of all that garbage. Every time you log in, there's more cruft. More of them trying to analyze how you're doing. Do a Qantas. Is that what it is? No. Quantalytics or whatever it is that they're using to figure out if I'm happy with them or not. And I keep telling them I'm not happy with them and they haven't changed anything. So why do you keep popping up that rectangle on the bottom of the screen? All right, I get it. But aren't you scared now considering how bad they are? They've been so bad for so long and still pilot Zenny Zero to some degree. You even posted on your LinkedIn a little while back about they're the second in the business and they have tiny market share. All these different Indoneso, all these companies failed. Why do you feel like you're ready to succeed in this space where they're all gone?
- [25:56]
B
This is your question earlier. Also, if there's so many, there's a graveyard here. There's a graveyard of companies that have tried. Why are you so crazy? And the reason so many companies have tried is because it's a massive problem and a massive pain. And the tam, the total market is just enormous. Every single company needs this. And that's also why it's so exciting. Right? If it's such a massive problem and we can change how all businesses work, then that is worth pursuing. And I and Quanta have taken a very different approach than the companies that we've just talked about. It was by no means easy. Our approach was we only work with companies that fit within the automation that we have built. So pilot Zenni, the ones we just talked about, they have hired a very large staff that is just using QuickBooks. So they did not start by building their own QuickBooks replacement. They started using QuickBooks and they started by hiring a lot of people. And they have gone very horizontal in the types of companies that they support. So we're talking anything from aquariums to coffee shops to physical machinery. And that is just very difficult to do if you haven't truly automated it first. So once you hire the people to do it and once you're supporting that, it's very hard to go the the other way and come back to the automation. Quanto we only work with companies that have a business model and a set of tools that fit within what our software does. And that was very hard from the beginning because I had to say no to so many customers that wanted to use us. And we still do. Even just earlier this morning. Every single day we get someone, you know, nonprofit that I would love to help and they say they hate QuickBooks and. But we just, we can't support their business model right now that that discipline has made sure that we actually have a viable business and we are operating at a quality level that you can't find elsewhere. But once you resort to, I'm just going to throw humans at the problem and have them use QuickBooks then you get stuck in this trap.
- [28:11]
A
And you know what? I shouldn't say that these all have failed Indinero. I think they ended their software, but I've been seeing their financials. You advocate that founders need to email their investors once a month with updates. I think they've been doing this now well over a decade consistently. And so I see that they're doing well, but they're not in the, in the. We're going to knock QuickBooks off business. They're in the we will work to do your books business. We've got people here and I guess every one of these companies has found their own little niche. They just didn't unsee QuickBooks. And I don't, I don't understand why. And I guess what you're saying is just like zero started with New Zealand, your New Zealand is these companies that can be fully automated. We're going to work with them. And then we're going to expand through zero expanded to Australia, then the uk, then the rest of the world. We're doing that.
- [29:00]
B
Exactly. And QuickBooks, it can solve for any sort of business model because it's so generic, but because of that it's sort of just, it's like I said, a blank slate, just little database, you can write anything into there. And because of that it can support any business. But also because of that, it doesn't do any one business incredibly well. And I believe the best way to start a company is to start with one area where you can really make a difference and really solve their pain and even just change how they're they're doing things. But if you're a bookkeeper that needs to be able to support any business in your neighborhood, you need the software that's going to work for all of those sorts of businesses. And QuickBooks can do that for you.
- [29:44]
A
So I'm on your site, it's usequanta. Com. I don't see that, that focus, it says full service accounting supported by intelligent platform to deliver the metrics that matter. Where is it that you're screening out the people who aren't a good fit or you're saying who it is a good fit for? I'm trying to understand what that focus is.
- [30:03]
B
Well, maybe it's a great point that we need to qualify that at the beginning because we do get a lot of demo requests and a lot of outreach from customers that we can't support. But all of our, our outreach in terms of who are we reaching out to, who are we marketing to, that's all within the early stage to growth stage software companies is what we focus on.
- [30:26]
A
So the fact that it's early stage and growth stage means and software means that if there's software, they're all probably using stripe or Paddle or a couple of other tools they're not using. They're not using one of these credit card machines that work in a store because they're software. It means that they all have the same type of tools that are easy to automate. That's, that's the, that's a distinction.
- [30:46]
B
If you look at our integrations page, you'll see the stack that is the modern financial stack for companies, for software companies. Although we work with services businesses as well and some agencies, the key thing we can't support right now is a lot of physical inventory. That's just a different type of accounting that we'll get there eventually. But we're very intentional if we're going to do it right. If we're going to support your business model and actually services and agencies and similar to software as a service when it comes to accounting. So it's not just SaaS, companies we support. But not having physical inventory is the key thing we focus on right now. Okay.
- [31:22]
A
Yeah. And I do see all these software tools that we use. It's like Mercury Ramp right at the top, rippling Gusto Stripe Carta. I'm surprised that that even matters to you.
- [31:32]
B
But actually, equity accounting is actually a very big pain to, to do it correctly. There's actually a lot of accounting nuance.
- [31:41]
A
And why do you need to do equity accounting? To keep my books.
- [31:46]
B
So we're, our focus is, yes, we serve day one companies just incorporated yesterday. And you can do that, you can do that bookkeeping in, in the minimal way. However, we support a lot of companies who are, we really care about their numbers and they're growing up and they're, they're looking towards getting audited. And the accounting for that for an equity perspective is actually not as simple as, let me take this wire from my investor and put it into equity. There's actually a lot more that you have to understand to do it correctly.
- [32:18]
A
Okay. All right, so let's go back. Actually, one other thing before we go back. I wonder if also, just like people are willing to reconsider their software when things went from desktop to the web, and again when things went from computer to mobile. The fact that we're now making a new leap into AI means that companies are saying, wait, I'm living in an AI world. My software is living in a pre AI world. I'm open to. In fact, I'm excited to explore what AI means for bookkeeping. I'm excited to explore what AI means for search and what AI means for writing. Is that part of it too for you?
- [32:53]
B
Absolutely. So when I was doing user research in 2022 and I talked to Controllers, which are the head of accounting and account coaching managers, they said NetSuite's the only option. We start with QuickBooks and you switch to NetSuite. And I would never choose anything different. But now people's minds are open and they're looking at a lot of different tools. And AI has been a big catalyst for that. They're saying, okay, the technology is changing. We could be taking advantage of better things. So I'm going to keep an open mind and I'm going to look. And there's a little bit of negativity there also in fomo. And I don't want to be left behind. I need to be taking advantage of the new, of the new technology. So that, that is a really big, really big part of it. And then I would say the other thing that the AI era has brought on that Quanta helps a lot with is you just need to keep up with your margins as a software company in a way that has never been important in the past 15 years. The past 15 years of SaaS businesses, everyone just assumes that their margins are incredible. But now companies are spending so much on the LLM API providers and because traditional bookkeepers don't understand those new vendors and how to treat them, they often get lost in operating expenses and their expenses and they're not being tracked as your cost of revenue. So we work with companies to make sure that they're tracking their margins. And these things are changing on a day to day basis, by the way, because of usage based pricing, which is very new and dominant for the AI era. Like you need to be keeping up with your margins on a day to day basis or else you're behind and you're doing that. So yes. So real time is a core component of Quanta. All of that real time reconciliation I was telling you about. We let companies be able to go in and see what's going on on a day to day basis, which is something that was not possible before and is really becoming a requirement in the AI era because your costs are so volatile and changing every day. And the margin profiles of software businesses have completely changed with how expensive their costs are and how those costs scale when their users use them more, which used to be something that was not big in SaaS with fixed monthly pricing.
- [35:07]
A
Okay, so it comes from, if I were to deconstruct how Quanta got where it is, comes from you discovering a real problem, but going the next step and saying, let me see if I fully understand it by shadowing companies that would experience this problem and saying, okay, as a developer, I know I can solve this. Then you and your team doing a lot of it manually as you're creating the software that does it. But actually I skipped a step. One is saying we will not do a lot of this stuff until we own the data. That actually having clean organized data is as important or it's critical to getting the next step, which is using AI and human intelligence to analyze it and make it useful. That's it.
- [35:51]
B
That's exactly right. I would say for anyone looking to use AI to start a company to displace what was traditionally done very manually by humans, first See what they're doing, really understand it. Then two, do it yourself as you bring on your first customers. So do the work yourself, don't outsource it. Make sure you understand the ins and outs of it. And then three, make sure you are in your data storage, really understanding and building up a clean, structured data. Because when you apply AI on top of that, it can be like magic. But if you're taking ChatGPT and putting on messy data, you can only get garbage out if you put garbage in. So make sure the data that you're storing is clean and understood. And then after that, you'll be able to to automate something that was manual before.
- [36:42]
A
All right, how much money did you raise? Tell us.
- [36:46]
B
And the recent Series a, we raised $15 million, led by Excel, and we also had a seed round previously, so it's been 20 million in total so far.
- [36:59]
A
And then how many customers do you have now?
- [37:03]
B
We have just under 100 right now.
- [37:05]
A
Wow. All right, Solid business. What's next? Where are you going with what's next now? Where are you going with the business?
- [37:13]
B
So the thing we're very excited about right now that we just announced with our Series A is a product called Prism. So what I just said about applying AI on top of clean and structured data is that if you understand all of the finances of your customers, you can really answer any question about it. So that's what Prism does, is you can ask a natural language question, really anything about your business, and we'll give you an answer. But what the really exciting thing is, is that answer explains itself. Itself. It can prove its logic and show evidence all the way back to the source data. So links back into your financial tools and showing all of the logic and helping understand that it's complete. It is covering all of its bases. And this is work that would previously take finance owners just many hours a week to do. It's always a new spreadsheet every day, going back to all your financial tools and digging up data. But because of the way that Quanta stores everything, we can actually automate answering that.
- [38:13]
A
Like what?
- [38:13]
B
So we're doubling down on that.
- [38:15]
A
I kept saying yes, because you're right to just get an answer. I don't trust it. What I want is the answer and then cite your source so that I can go back and understand that you did get it right. And that actually answers the question that people had asked you. How do I know if all this is okay?
- [38:30]
B
Give me.
- [38:30]
A
Before you go to the. Before you go to the next thing, I'm curious about an example. Do you have an example of something that people could ask now that they couldn't ask before, that they only could ask human beings before?
- [38:41]
B
Yeah, definitely. So the one thing I saw in how other bookkeepers were doing books for companies that eventually became my customers is that Stripe is the biggest example where they would go into Stripe, they download a report, they sum up all the numbers and then just take one number out, which is this much revenue last month. But what you've lost in that process is you've lost well. How many customers churned, how many upgraded, what products are they using? All of this really important information you need to understand your business. Quanto retains all of that and even if it's not every detailed entry in your eventual general ledger, we store up a lot of other operational data that we then can use for tools like Prism. So you can ask what products were being used, who has churned, who has upgraded, who has been refunded, really just what happened with my customers recently. And we can instantly spread out a report that talks about that versus with any other provider. You'd have to go back and log in and grab all that data and then log into your bank to see who paid you back over the bank and not Stripe, and then log into your contract track system. And that just takes hours and hours of digging.
- [39:57]
A
All right, you know, I actually want to close with this one thing. I'm going to interview one of your investors, Elad Gill. How well do you know him?
- [40:05]
B
I actually saw him last night at their holiday party and his chief of staff was in my office just yesterday. It's very funny that you bring that up, but he obviously, he invests in so many companies, but his team is incredibly supportive and they're a pleasure to work with.
- [40:26]
A
What makes him so. So interesting? Yeah, he's invested in Stripe, in Airbnb, Coinbase, Notion, a lot of AI companies Airtable. I can keep going through it. What makes him so good to work with or his team?
- [40:40]
B
So his team, like I said, is the Chief of staff was in our office yesterday and is directly helpful in terms of customer connections, recruiting, of course, advice, but really that. That boots on the ground. Let's do an event together. Let's. I'm going to connect you to potential customers and that is just an incredible value as a pounder.
- [41:02]
A
All right, thank you so much, Helen.
- [41:06]
B
Yeah, well, thank you. Appreciate you having me on. And this was a lot of fun.
- [41:09]
A
Hell, yeah. Congratulations.