00:00Give us the elevator pitch for Rillit. What are you actually doing and who is your audience here?
00:06Yeah, great to be here with you, Katie and Romain. We are building an AI native ERP.
00:11So what that means very specifically, we are helping accounting and finance team generate
00:17financial statements and reports a lot more quickly and accurately, and also help them
00:22be compliant in this day and age that is moves ever so much for fast with financial information,
00:26records to be transacted and accounted for, which is very powerful. So with that, we're powering
00:31some of the leading mid-market and lower enterprise companies like fast-growing startups like Mercor
00:36or Function Health, as well as public companies today. And Alex, we'd love to hear your perspective
00:41because I imagine that you are pitched and you are pitched often for a lot of AI-focused companies
00:48here. So what stood out specifically for Rillit to the point where you said, I want to be a part
00:54of
00:54this in some way. Yeah, well, I'd say two things. I like to think that the best companies are these
01:00filing cabinet companies. The history of software is you take a filing cabinet, you turn it into a
01:05database, and this is everything. Saber Systems was the first company that did this in 1960 for the
01:09airline industry. But every company, I mean, Salesforce for CRM, Workday for HRIS, the new AI generation
01:17of these now do the work. Like you would log into Workday if you're an HR person and you do
01:21HR stuff
01:22within Workday. You'd log into Salesforce if you're a salesperson and you do CRM stuff. You do sales
01:28logging within Salesforce. They just kind of keep track of things. What's happening right now is this new
01:33generation of AI-driven companies, the AI does the work, right? So what do I do if I have all
01:39of my
01:39financial statements and I give AI to them? It's like, oh, maybe I could do collections and automate that.
01:44Maybe I could figure out what my tariff exposure is. Not to mention the fact that I can close the
01:49books.
01:49When I was running my company, it used to take, I think, like 20 days. I wouldn't have like accurate
01:53financial statements for 20 days as opposed to, you know, with Realit, you've got a continuous
01:57close. So the concept of what's going to happen to software when you add AI is just transformative
02:03because you're no longer limited to the software market. You're limited to the labor market,
02:08right? Because all the people that we use in ERP, like now some of those jobs can be done by
02:14the
02:14software. So that's very exciting. Why we invested in this one was, you know, we see a lot of
02:18companies. And honestly, like we have a saying that we like a lot, which is never bet against
02:22the graph. The graph being the usage and revenue. And this is the fastest growing company of all of
02:29the AI ERP players. So the customer is always right. And we like to back the customer. And
02:35that's what brought us to Realit and Nick. So Nicholas, I am curious, though, too, just also about,
02:40I guess, the accountability for accounting, pun intended. But also the idea is like,
02:46like, who is shouldering that potential liability? Obviously, when we talk about accounting
02:50standards that a lot of companies have to follow, it's not just about, you know, making sure things
02:56are accurate. Even if you did it in good faith and you were wrong, there could potentially be
03:00consequences. So how have you sort of structured, I guess, from your side of the business to make
03:04sure that you're not shouldering too much of that liability and also to make sure that your customers
03:08feel confident that what they're getting is accurate?
03:11A hundred percent. So from an audit perspective, people will refer to financial statements as
03:16accurate and complete. So both of these, you obviously need to ensure whether you use AI or
03:21you don't use AI to generate these financial reports. And so what that means very technically
03:25in our concept of building an AI native ERP, humans are always in the loop for final decision
03:30makings. There's very detailed traceable audit logs as to why things are happening and what is
03:36happening. And at the end of the day, you can't rid the responsibility and accountability as a as a
03:42company for your financials in that regard. So whether AI has prepared it, there's always a human
03:47that will review the financial statements in its final form.
03:50I do want to ask you also, Nick, just about the pace of development that we've seen in the AI
03:54space
03:55and particularly with agents and obviously what you're doing there. But the on the ERP side, I mean,
04:00I'm actually been amazed by it. I mean, even certain products and services I saw maybe eight,
04:06nine months ago, and then I'm coming back to them today. It's almost mind blowing. And I'm just
04:11curious if you could maybe kind of look a little bit in around the corner as to sort of how
04:15much
04:15faster you think this development will be, or are we starting to hit stall speed? Like, where are we
04:20in all this?
04:22Yeah, it's phenomenal. So even just in the last, let's say, three to four months, the pace of change
04:27with these foundational models coming out with new iterations of their models, the ability for new
04:32customers to adopt software. So for context, ERP software is traditionally very hard to adopt,
04:37implement, install and maintain. AI helps a lot with a sort of the ability to accelerate that pace
04:43as well. It's just a compounding of R&D that's faster as well as customer adoption that's faster.
04:48So when I forecast or like look out at least six to nine months from here, I do see a
04:54world where
04:54some of the changes that it has on team structures, the changes it has on financial
04:59information that's available will actually keep moving faster at the current pace before it gets
05:04slower.
05:05And Alex, I do want to ask you a broader question here, because you do lead Andreessen Horowitz's
05:10$1 billion apps practice. And you mentioned, you know, what attracted you to Rillit. It was software
05:15combined with AI. And I wonder, you know, if that's really the sweet spot for you right now, when you're
05:21taking a look at pitches, evaluating them, what stands out to you as where the opportunities are?
05:27Yeah, so the worldwide software market kind of x cloud infrastructure is something like $300
05:32billion. And the like the US labor market is 1314 trillion. And this doesn't mean that labor goes
05:38away. There's not a fixed amount of labor to do. It's like everybody in 1789 was a farmer in America.
05:44But the really exciting thing right now, the thing that we're drawn to the most, and most of the
05:48companies that are growing like crazy, they do some element of like the software is doing the work
05:54that the human user of the software would do before. So if you think about like support,
05:59customer support, you would have a customer support software application that customer
06:04support agents would use. What if you get a call in Portuguese, and you don't have a Portuguese agent,
06:09you know, an actual human to go answer the call, like you can't do anything. The software now,
06:13you don't need the you don't need the humans to go do this not fun labor that they have to
06:18do.
06:19The software application can do it. And instead of charging $100 per seat per month,
06:24well, the labor costs like what were you paying the person that was in that seat, you might be paying
06:27them $50,000 a year. Now the software can do some of that labor. And in many cases, this is
06:33just it's
06:33not replacing the humans like that. That's the biggest fallacy that we see. A lot of it is just
06:38expanding the market. I wish I mean, think about like Macy's, they hire Black Friday cashiers,
06:44then they don't need Black Friday cashiers two weeks from from then. A lot of businesses have
06:48just intermittent demand. And one of the things that's great about a lot of these companies is
06:52they can flex into the demand that their customers have and support is a great example of that. So
06:57the main thing that we're really looking at right now, and I've never I've been in this business for
07:0210 years of investing in high tech. And I've never seen companies go from like zero to 100 in a
07:07year
07:07before zero to 100 million dollars in high margin, like often profitable revenue. Many cases, we're
07:13competing not with somebody like Sequoia to win a deal. We're competing with the fact that the company
07:17is profitable, because they're no longer selling per seat per month licenses. Like, I think that's
07:22dying. What's the future is like some outcome based pricing, like the software does so much more than
07:29what you would ever think of software doing before. And that's entirely because of AI.
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