I'm Devin Au. I'm with the broader KeyBanc software research team, covering education software and vertical software. Glad to have iLearningEngines with us today, and my colleague here. I'll just let Jason kick things off for us.
Yeah. Thanks, everyone, for coming. I want to thank Farhan, the CFO of iLearningEngines, for making it today. I want to thank everyone for making it to our conference. Maybe just to start it off, Farhan, maybe just talk about yourself, iLearningEngines-
Sure.
What you guys do, and, maybe a little bit about your background?
Sure. So I'll start with an introduction to iLearningEngines. We are a learning and process workflow automation firm. And, don't take this as a brag, but we've been doing AI much before the world started talking about AI, and AI became the buzzword. The company was started in 2011, and, we have been building AI tech since then. So, AI has always been a fairly capital-intensive technology, so it took us four or five years to actually get a product, out in the market. I think 2016 was the first year when we went commercial, and, after that, our growth has followed that classic hockey stick growth. So-
Okay.
That's the background about iLearningEngines. About me, I come from the investment banking world. I did 10 years of technology investment banking on the West Coast, focused on disruptive technology companies. So did capital markets, M&A activity for companies like Uber, Alibaba, Facebook, and then moved to iLearningEngines in 2019.
Mm-hmm.
have been with the firm as it is. It has grown from, like, from where we were in 2019, about $40 million to close to $420 million-plus in revenue last year.
Maybe just as an intro to the group and people on the webcast, maybe just recap your path to the public markets.
So our path to the public markets has been fairly unique in the sense that we never raised a lot of equity capital. We've been able to build this business on the back of partner financing. So one of the first channel partners who took us to market, they realized the kind of value that our business was or our technology was creating for their clients. So they invested into our product development. And right until 2022, that was the only financing that we had access to. Right until 2020, sorry. So it was in 2020 that we first took external capital through venture debt providers in Silicon Valley, and then we went public through the De-SPAC route in April of this year.
Excellent. Excellent. And we'll try to keep it interactive, so feel free to ask questions if things come up. But maybe just to level set it, Farhan, you know, if we think about the business, can you talk about maybe some use cases of maybe when an education use case-
Absolutely.
-and how that would be used with your platform?
Yep. So, let me talk about two things. First is the technology part of it. So if when you talk about AI, large language models are all the rage. Now, large language models require a lot of compute, require a lot of storage, and that, like... So the technology is absolutely marvelous, it's novel, but companies are still trying to find how to build use cases, real-life business use cases on top of that. What we've realized is that in normal business settings, small language models actually work better than larger language models. Require a lesser amount of compute, lesser amount of training, and the results are far more effective than taking a generic large language model and trying to train it for business use cases. So that is the path that we've followed.
We've built 40-plus proprietary models of our own, and we deploy them as per the need of our customers. So those are easier to train, easier to customize, and produce better, if not equal, results.
Okay. Maybe just speak to some of the data that is evaluated in some of these models, and then how a customer specifically would be using it to gain insights and what would be the kind of outcome on that education example, if you're-
Well, so if you think about education, and that holds true in a very broad sense for corporate training as well. If you think about education, the way the education industry has evolved up till now is the thought process has been you get more and more, and curated content into the hands of more and more users, and expect them to learn. So all the businesses in the edtech space have almost followed that logic. What we've realized is upskilling or learning happens far more effectively if you're able to create customized learning pathways for the learner. So you and I, for example, have different strengths and weaknesses when it comes to things that we learn. We learn very differently, right?
So for me to make you learn, the best way to do that is I create a customized learning pathway for you. And that is the approach that we've followed, at least on our education vertical.
Mm-hmm.
Right? So students, our platform allows educators to create customized learning pathways for the students that they're trying to teach, and that is what supercharges the learning.
Okay, interesting. Good example.
Question for me here, Farhan. Wanted me to take a step back. I mean, you guys obviously leverage AI since, you know, quite a, quite a while-
Yes.
-before this whole GenAI wave.
Yes.
But I think a recent, like, investor debate or question is, you know, with GenAI, it seems like it makes it a lot easier for companies and users to maybe, like, program or maybe, like, make it easier to, like...
So, yes-
create better internal efficiencies. I guess my question here is: do you see GenAI as kinda like a headwind to your business, or do you think GenAI has become, like, a tailwind for you guys since customers are more acceptable of AI?
It's the latter.
Okay.
It's clearly the latter. There's a lot of excitement that's been created because of GenAI, startups, and that is providing a lot of tailwinds, in terms of acceptability, in terms of, the speed to deployment. Like, earlier, if our sales cycle would be 6-9 months, now that has reduced to 3-6 months because customers are far more aware. Like, we don't have to educate them from scratch for them to be able to make the purchase decision. They come in knowing a lot, lot more about how this thing works-
Mm.
and how this, they can leverage it.
Got it, got it. And then, I don't know if you have any sense of when you talk to customers or maybe some of the customers that you landed recently, do you get a sense of, like, where that budget is coming from? Is it, like, incrementally-
So-
you know, new for investing in AI, or are they competing from, like, other-
So-
Software spend or budgets?
Well, so you would typically start by competing with somebody, an existing vendor. But, like, very quickly, the business unit leaders realized that this software platform can be used for so much more.
Mm.
Starting from learning automation to workflow automation. You can deploy the same tech and same platform with a little bit of customization for workflow automation as well. Right? So that's how that land and expand thing works. At least that's, that's been our experience.
Okay, and then maybe taking a step back here, you talked about learning automation, workflow automation. Maybe just, you know, help, help us, like, level set or frame just how big of the opportunity that you're addressing.
Oh.
Any numbers you can put around?
Yeah, sure. In the U.S. alone, the TAM that we are looking at is about $300 billion.
Oh, wow! Quite large, yeah.
Massive. And it's, it's massive in size. It's growing very, very quickly because of this acceptability that we just talked about, and it's fragmented. You have hundreds of thousands of companies in the $20-$200 million EV range, who have had legacy customers for, like, two, three decades. And their technology, like, they, they built their technology two decades back. So now they, they are basically unable to scale up because their tech stack is archaic.
Got it, and then maybe just double-clicking on the market opportunity. I mean, you talked about education as a vertical.
Mm-hmm.
Can you just give us, like, a little bit more on, like, where else have you expanded?
Yeah. So if, if you think about the usage of our platform, especially on the corporate training side, the more critical training of employees is for any certain sector or vertical or a particular company, the more useful our platform tends to be. So what that translates to is, on our, on our revenue book, the biggest sectors that are represented: oil and gas, healthcare, insurance-
Mm.
-financial services, where there's a direct impact of corporate training or the correct training of employees on the top line as well as on the bottom line. Those are the customers who adopt this the fastest.
Got it. Out of-
Can we maybe double-click on that oil and gas example?
Yeah.
I thought it was quite interesting. Oil and gas can be a very technical industry.
Yep.
So is iLearning being used to help upskill those employees? Or because you also mentioned workflow automation, is it being used as, like, a process mining tool?
It's, it's both. So oil and gas is one of those sectors where, the impact of errors can be huge, on the top line as well as on the bottom line. I'm not sure if many people remember this, but about 10 years back, there was this, Macondo disaster in the Gulf of Mexico.
Mm-hmm.
BP ended up paying $50 billion because of that, that disaster, and on investigation, that disaster was found to be-- the cause for that disaster was human error. An operator who was not trained for a particular job was allowed to get onto that rig and do that job. So, that was, that was the root cause of that error. Now, think about, if BP had a platform like ours, which ensured that either the operators were trained right, or if they were not trained and were not certified, they weren't allowed to get onto that rig. That is one way they could have avoided that disaster, and that would have saved them a $50 billion mistake that, that they ended up doing.
That's, that's a real-life scenario where this thing could have prevented such a huge impact.
Interesting.
Sure. Go ahead.
A couple questions, Farhan. Maybe some examples of some of your largest customers, just logos that, that folks are familiar with. And then, just to maybe run through how sort of like and expand, or it's like, what module do they start with? How's the product priced?
Mm-hmm.
You know, is it they buy? Is it kind of all-you-can-eat buffet, or there's some volume-based components, but just basically, yeah.
So, our purchase decision is right, based on two things. One, so we charge on a per-seat basis.
Yeah.
So a company has 1,000 employees, they would probably start getting started with 100 of their employees using certain specific functionalities of our software, right? And then the land and expand happens on both vectors. You would get more employees to start using our platform. You would also start letting them use more functionalities. And the more functionalities they that they use, the more we charge on that.
What are some examples of three or four, like, key customer logos for you guys?
So you would have Munich Re, the insurance provider, that's a huge customer of ours. We have American Hospital Association here in the US, that's a big customer of ours. There are another, I'm forgetting the name of another insurance company here, another one which you'll be very familiar with. So as I said, like oil and gas, and then there's marine engineering companies based out of the Middle East, who are customers of ours. So the customer spectrum is fairly wide, but the four sectors that I mentioned, those are the biggest, the most represented sectors: oil and gas, healthcare, insurance, and financial services.
Maybe just to follow up on that, you mentioned sort of here versus there. I mean, roughly, how much of your business is U.S. domestic, and then how much is the rest of the world?
Close to 45%, somewhere between 45%-50% is US.
Okay.
The rest of it comes from Asia, Middle East, Europe.
Okay, I mean, that's a good segue. So maybe with your go-to-market, who is the purchaser within an organization? Is it the CIO? Is it-- Who, who would it be?
So, it's typically the business unit leader. So, in a different scenario, if you're selling learning or training software, you'd probably go to the HR department. But given the applicability of our platform, it is applicable to a lot more than just human resource management. You're talking about workflow automation as well, right? So our purchasers tend to be more on the business unit manager side than the HR people.
Okay. And then, within your go-to-market, is it mostly direct sales? Do you leverage the channel or-
We leverage channel partners extensively.
Who would some of those partners look like?
So, that is a trade secret.
Okay. Sure
... that we'd like to keep confidential.
Okay.
But yeah, so the way this works is you have channel partners, and then with each channel partners, there are hundreds of thousands of end users or end customers behind those channel partners.
Okay. I think you touched on a little bit, but I think average sales cycle is maybe 1-2 quarters, and I think you've-
Yes
... seen that come down in the past years.
So we do POC-driven sales. So in, when you do that, once a potential client has taken a POC, then our hit rate after that is, like, very, very high. But to get that POC done, completed, that itself takes about three months.
Okay.
The sales cycle would be 6-9 months from start to finish, finish being when the customer is onboarded and deployed.
Got it. Got it. And that includes the implementation time?
Well, so the nine months includes the implementation-
Got it
... which is the onboarding part.
Okay.
I want to touch on maybe competition a little bit. I think-
Sorry?
Competition.
Okay.
It seems like, you know, you guys offer a pretty unique offering, but also maybe some of the automation, workflow automation side of things. Are you guys-- Do you guys see yourself competing with, like, a UiPath or, like, a-
Well, so-
Automation Anywhere?
... it's our competitor universe is actually fairly wide. So you have Palantir and C3 AI of the world who have been pioneers of AI technology. Then you have custom software application builders, who, like, there are thousands of those as well. So our platform allows enterprises to build customized apps for the company itself. So at one end, we are also competing with these small custom software builders, and at the other end, we have the C3 AI and Palantir of the world, who are providing the core tech. And the reason is, we're doing everything. Then we have our proprietary models, and we allow our customers to build apps on top of that.
Okay.
So it's the entire spectrum.
Yeah. I mean, when you have a $30 billion opportunity, you're gonna have a competition, right? So-
$300 billion.
Oh, $300 billion, sorry, even bigger. So more competition.
Yes.
Perfect. Well, I think we're almost out of time, but is there any final questions from the audience? Sure.
Well, why do you win? If you have a customer that's looking at your solution and someone else's, what are your selling points that you think gets you over them, you know?
So let me give you a more detailed answer on that. Data is the lifeblood of any AI. AI solution wins or loses on the basis of the data that is being used to train that, right? One of the very amazing things that we've been able to do is we've been able to procure or like put in motion a data pipeline, wherein we actually buy data that is gonna be used for training our AI. Right? So that differentiates us, as in the quality of the data that we use to train the AI, that itself is a huge differentiator. Right?
So, what that does is, and because we have this data pipeline set up in motion, we are able to get refreshed data, and use that to train our AI. So in turn, what that does is the customers see the most advanced or the latest platform that they engage with every time they engage with it. Right? In fact, the customers, as they engage with the platform, they create data. We call that the Engagement Footprint. That data is also used to train the AI, which is what makes that customization possible, right? And that's where the differentiation comes in. So just in terms of, like, what it means in terms of numbers, our net retention numbers have been at, like, 130% consistently over the past four or five years.
Okay, great. Big question. Well, sure, one last question. Yeah.
It's really interesting, I think, the evolution of the company's history, raising very little traditional institutional capital.
Mm-hmm.
Obviously, you know, went publicly as SPAC. I mean, take us through sort of the thought process in staying relatively lightly capitalized for so many years.
Yeah.
You have the privilege of being able to do that, not all companies do.
Yeah.
Also, you know, the decision to go via SPAC, and you guys have performed better than most-
Yes
and all of that, right? So
And we're still not where we would like this to be in terms of stock performance. But, so I'll answer the second part of your question first. So we started thinking about... The reason why we started thinking about going public was, as I said, the market that we operate in, that's a $300 billion market now, and it's fragmented like crazy. You have literally thousands of companies in the $20 million-$200 million EV range who have legacy customers that are cash cows. So for a company like ours, which has disruptive tech, the way to grow here is through acquisitions. Like, everybody, we realize that very, very well, that there's no need for us to pursue organic growth alone in a market like this.
And the playbook for us would be, you go in, buy these companies, replace their tech stack with ours, and upsell. That's how you grow faster. So, but to be able to do that, we needed currency. So we've been EBITDA positive for four years now, but we are not generating enough cash to be able to make these acquisitions. So we needed currency for that. Now, once it was decided that we have to go public, the option was to go public through the straight IPO route or through the De-SPAC route. De-SPAC helps us get public faster, right?
And the industry environment that we have been in, the companies that we would like to acquire or we have been looking to acquire, their valuations have dipped dramatically over the past 2-3 years. Three years ago, the companies that wouldn't even talk to us are now reaching out to us to see if we would be interested in acquiring them. So this is a perfect moment for us to go in and start making these acquisitions. That's why the urgency to get to market and be a public company sooner rather than later.
Okay, great. Well, I wanna thank everyone for coming, and for Farhan and iLearningEngines for coming to our conference. Thank you. Thank you, Farhan.