Balakrishnan A.P., president and CEO of iLearningEngines AILE, was recently a guest on Benzinga's All-Access.
iLearningEngines is an Applied AI platform for learning & work automation. It is one of the fastest-growing technology companies in North America. AI can help revolutionize learning in big and small organizations, and iLearningEngines is proving that.
The company has grown rapidly, with a nearly 50% average CAGR over the last 5 years. It has done this by consistently delivering a product customers are satisfied with, leading to a retention rate that well exceeds the industry standard.
iLearningEngines is an Applied AI platform for learning & work automation. It is one of the fastest-growing technology companies in North America. AI can help revolutionize learning in big and small organizations, and iLearningEngines is proving that.
The company has grown rapidly, with a nearly 50% average CAGR over the last 5 years. It has done this by consistently delivering a product customers are satisfied with, leading to a retention rate that well exceeds the industry standard.
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NewsTranscript
00:00Good afternoon, Bala. How are you?
00:07Good afternoon, Zuned. I'm good, thank you. How are you?
00:10I'm doing great. Happy to kind of have this conversation with you.
00:13There's so many things to talk about, but before we kind of get started,
00:16give the viewers a quick overview of what is it that your company does.
00:19Sure. We are iLearning Engines, and my name is Bala Krishnan.
00:26I'm the President of the Chief Business Officer.
00:28We are a leading applied AI platform for learning and work automation.
00:33We enable enterprises to rapidly productize and deploy a wide range of AI applications
00:40and a lot of use cases at scale.
00:44At the core, we are powered by proprietary vertical-specific AI models and data
00:48with a very flexible no-code AI canvas to drive out-of-the-box deployments.
00:55We are deployed in over 1,000-plus enterprise customers,
01:00have about 4 million licensed users across 12 global vertical markets,
01:05which include healthcare, education, insurance, energy, and so forth.
01:10From an operational viewpoint, we are at a recurring revenue of 97% of our total revenue.
01:16Our trailing five-year CAGR is 48%.
01:20Positive adjusted EBITDA each year since 2020.
01:24I have a rule of 40 company for the past five years. Zunay?
01:29Yeah. You mentioned a lot of great stats there.
01:31One question I have for you is what's the company's current net retention rate, right?
01:36And how does it kind of compare to the industry's benchmark, especially in the AI sector itself?
01:41Right. Very good question.
01:42Our current net retention rate is about 132%,
01:48which operationally significantly outperforms the industry average,
01:53which is at about 101% to 102% for tech companies in the SaaS domain.
02:00Again, there's a key indicator that we are retaining our clients,
02:04very high customer retention, and also very successfully expanding our relationships
02:10through upsells and cross-sells. Zunay?
02:13Got it. And then what are the strategies, though, that go behind your company
02:17to implement these and achieve what you've got going on with the net retention rate?
02:22Great. At IME, what we drive across all our engagements is a proof-of-concept,
02:30a POC-led strategy, which helps us get closer to our customers
02:35and build very strong, scalable client relationships.
02:39That is one key aspect of our strategy to drive a very high net retention rate.
02:45Besides that, we've got dedicated success managers who ensure our clients maximize the value
02:51from our AI engagements and touchpoints deployed into the client premises.
02:57Thirdly, we invest significantly into R&D to ensure our AI solutions remain cutting-edge
03:05and continuously innovate our product offerings based on what the clients tell us constantly,
03:10and we continue to meet their evolving needs.
03:14Bottom line, Zunay, is we set a benchmark in terms of support services
03:19that we've learned from our customers that no competitor has been able to match.
03:23And this is supported through a very, very strong channel partner relationship model,
03:30which helps us to keep scaling in the markets that we operate in.
03:35Now, when you're working with these companies,
03:37so many companies want to be a part of the AI revolution, right?
03:40They want to be engaging in it.
03:42They want to go ahead and have it be a part of their business
03:44and streamline their processes for them.
03:46What are some challenges that you see these companies facing?
03:49But also, more importantly, how are you helping them face these challenges
03:54and provide those solutions?
03:57See, at the core, I mean, most of the organizations have been struggling
04:02with long deployment timelines in terms of the time taken for AI to be deployed,
04:10which includes one of the outcomes or offsets of that is high initial costs,
04:15deep integration costs with their existing systems,
04:18and a very, very steep learning curve for employees.
04:22What ILE does is we have driven by a no-code canvas,
04:26which makes the whole platform configurable and provides rapid deployment
04:30with, we would say, minimal disruption to the enterprise's way of working.
04:35So the AI engines, which is created on our platform,
04:39they leverage what we call pre-built modules and data
04:44that is pre-trained for specific industries.
04:47So what this essentially means to a customer is that a client starts benefiting
04:52from very accurate insights and automation almost immediately from deployment.
04:57So we are able to deploy this platform in about three to six weeks
05:02from when we begin the engagement and the discovery session with the customer,
05:07which is something that helps drive very measurable outcomes
05:12across our client engagements.
05:14Let's continue on the topic of challenges,
05:16because I like where you kind of provided the solutions
05:18that you have to help these companies.
05:20But data security has got to be one of the top key ones as well, right?
05:23So much data is not being collected in terms of AI on the consumer
05:27on the other side.
05:28And, of course, now who knows what the future of EV looks like.
05:30And I'm hearing even planes might be automated there.
05:34But when it comes to data security, what measures are you taking
05:38to make sure that it's protected from getting into the wrong hands?
05:44Well, at ILE, we provide the platform in multiple modes to the customer
05:50based on what the customer prefers.
05:51So while data security is critical and the cornerstone of what we provide,
05:56we offer multiple models in terms of on-premise.
06:00We offer a private cloud deployment for industries like, say, for example,
06:05education, banking, and finance.
06:07The data security and compliance are very, very critical parameters
06:12that have a great say in decision-making.
06:15So by allowing our customers to opt for on-premise
06:19or a private cloud deployment, we help address these concerns
06:22and also provide the safeguard mitigants for sensitive information.
06:27Now, our implementation process is compliant with global industry standards
06:33which exist across these regulatory frameworks and which also ensures
06:38that customer data at every point is protected at the highest level.
06:43Do you have any examples of companies that you've successfully integrated with
06:47in terms of these legacy systems of what you're working on?
06:51I'd like to take a quick example, if that may help explain the context.
06:56One of our large customers is a global manufacturing conglomerate
06:59with about 22 business units and 40,000 employees
07:03in about six to eight locations globally.
07:06So at some point, they had a great deal of trouble
07:11aligning the subject matter experts inside the company
07:14to drive company-specific training for their 40,000 employees
07:18and plus an ancillary dealer network of around 10,000 plus.
07:22So they had no ways to get this done.
07:24So while the company was struggling with two critical parameters,
07:27which is siloed knowledge and expertise not being carried through the organization.
07:33So they wanted to get a handle on performance dynamics
07:36on a daily basis across the network.
07:39So what ILE did specifically with an account was we did an enterprise-wide,
07:46used our enterprise-wide knowledge cloud to ingest and aggregate
07:51and curate all the enterprise content from multiple touch points
07:54within the industry, within the company,
07:57creating an institutional IP repository for them.
08:00So from there on, we integrated with their SAP and SuccessFactors
08:05and they also had a platform called BMC Remedy
08:08and a host of other homegrown bespoke platforms,
08:12which seamlessly integrated into the ILE framework
08:16through the no-code canvas to capture every event trigger in one single place.
08:21So by doing that, Sunedh, we were able to drive learning automation
08:26by integrating ILE into the enterprise
08:29and also having the enterprise content indexed at scale,
08:32which is the bulwark of our ability to provide learning
08:36and workflow automation across the enterprise.
08:39Yeah, the seamlessness of making sure everything is aligned is critical, right?
08:43We see that on our end in terms of Benzinga.
08:45Heck, I even see it in my personal life about how things hectic can be
08:48and I would love automation in my life in many ways.
08:51Final question for you, how big can this get, right?
08:55What is the upper limit to this market, especially in terms of AI as well?
09:00We see the market converging with multiple tailwinds across multiple areas.
09:07The artificial intelligence market is predicted to be a market
09:11of around $135 plus billion with a five-year CAGR of about 25%.
09:17By 2025, we've got a global e-learning market,
09:21which is a $250 plus billion market with a CAGR of about 16%.
09:27Now, dovetailing into both of these is what we call the hyperautomation
09:31and the insights market, which is, again, a $60 to $65 billion market by 2026.
09:39Now, we operate at the sweet spot where all these forces converge.
09:43So we bring in AI, we bring in a no-code canvas,
09:47and we layer all of that with what is a sweet spot, which is configurability.
09:53So by bringing in configurability, we are able to address a total market size,
09:57a total time of about on the e-learning side of about $250 billion
10:06and hyperautomation of around $65 billion.
10:08So we believe the ceiling is pretty high for a lot of people
10:13to operate in this market successfully.
10:16I look forward to the growth.
10:17Obviously, you've already had great success.
10:18I was looking at your earnings transcript and things like that.
10:21But before I let you go, any final thoughts from you,
10:23anything I didn't get a chance to bring up?
10:24The viewers are all yours.
10:26Yeah, thank you.
10:27I would like to say that we would continue to stay focused on driving growth
10:35and keeping our growth margins, scaling,
10:40and ensuring that we continue to invest significantly into R&D,
10:44which has been the big pivot which has helped us to create differentiators
10:49in the market.
10:50And we look forward to our growth in the global markets and the verticals,
10:56which include healthcare, education, insurance, retail, and energy.
10:59Absolutely.
11:00And very happy to be here with you, Zuned.
11:02Well, hey, as you reach those milestones,
11:04I'd love to have you come back and kind of explain it to the viewers
11:07what exactly that means and where else the business is continuing to grow.
11:10Thank you so much for your time, Bala.
11:12Great, Zuned.
11:13Thank you.