iLearningEngines – Hear From The Chief Architect Of This Applied AI Platform
Sanjeev Menon, Chief Architect – AI/ML for iLearningEngines, was recently a guest on Benzinga's All-Access.
iLearningEngines is an Applied AI platform for learning & work automation. It reports being 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 with a nearly 50% CAGR over the last 5 years. It says it has done this by consistently delivering a product customers are satisfied with, leading to a retention rate that well exceeds the industry standard.
As Chief Architect, Mr. Menon shared his deep insights into how his company's AI functions and what makes it unique.
iLearningEngines is an Applied AI platform for learning & work automation. It reports being 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 with a nearly 50% CAGR over the last 5 years. It says it has done this by consistently delivering a product customers are satisfied with, leading to a retention rate that well exceeds the industry standard.
As Chief Architect, Mr. Menon shared his deep insights into how his company's AI functions and what makes it unique.
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NewsTranscript
00:00Sanjeev, good morning and welcome to the show.
00:07Good morning.
00:08Thank you for having me here, Zined.
00:10It's my pleasure.
00:12Absolutely.
00:13So there's so many things to talk about when it comes to AI, right?
00:16I mentioned this a lot where I wish I had AI access to it when I was in school,
00:20because I think, you know, all jokes aside, it would have helped me learn better
00:24and not just give me the answers, if that makes sense.
00:27So before we kind of dive in and look under the hood,
00:29give us the folks at home a quick idea of what is it that you do.
00:33So I'm Chief Architect at iLearning Engine.
00:36So basically we are into developing the iLearning Applied AI platform.
00:40So basically, like, you know, what the platform allows is basically looking at
00:44the enterprise learning and work automation.
00:48And eventually our idea is to drive the enterprise intelligence towards that,
00:52right, because as we know, it's a transformative technology
00:56and we're really super excited to be here in this time and space,
00:59spearheading this transformation as we have never seen it earlier.
01:03There's some, yeah, it's a great time to be alive in terms of what the technology
01:08is available to us here in this space that we're able to take advantage of.
01:11What do you, I mean, there are a lot of, like I said,
01:13buzzwords of AI has been in this space for quite some time.
01:15There are a lot of companies that are kind of using AI in their industries as well.
01:19What do you think is the unique value proposition that sets, you know,
01:23your company apart from the other AI applications in the development platforms
01:27that we see?
01:29Yeah, so basically in terms of, from a value proposition point of view,
01:34we focus on delivering actual business value.
01:38We do this through AI engines.
01:41To explain a little bit more, the problem that we see today is that enterprises
01:45are not getting actual business value out of AI.
01:49What makes Islanding Engines stand out is our rapid deployment of customized AI
01:56in a secure environment that drives business value and enterprise intelligence.
02:01That is basically like Islanding Engines allows organizations to quickly realize
02:06specific business value with AI by protecting and productizing enterprise
02:11knowledge in the form of AI engines.
02:14What does this mean?
02:15This means that we enable businesses to take the enterprise knowledge,
02:20store it, protect it, and learn from it to secure AI assets
02:27that is unique to that organization.
02:29This allows the AI engines built on our platform to fit into any kind of an
02:34enterprise in a flexible way, and our clients' success are testament
02:39to this value delivery.
02:41Then how does your platform and the AI applications developed on it compare
02:45against, say, the horizontal generative AI?
02:50Basically, Islanding Engines' generative AI is customized and specifically
02:55trained on enterprise data, focusing on solving a specific business problem
03:00which makes it usable for a wide variety of industry use cases.
03:05Generative AI, like you rightly said in the starting of this interview,
03:08it's a hyped-up word as it stands today, but the generative AI solutions
03:13broadly available have three things that they don't do well,
03:17which inhibits their usage and adoption in the business settings.
03:21One is basically they are very generic.
03:24They are not customized for a specific use case or trained on enterprise data.
03:28They are unsecured.
03:31Businesses need AI solutions, but they are also trained on their data,
03:36but they also want to protect that data.
03:39These generic generative AI solutions, they are incomplete because most
03:44business solutions need a combination of AI models and components
03:48to truly solve business problems end-to-end.
03:52That's where we completely fail in terms of against any of the generic
03:56generative AI components that is out there in the market.
03:59It's like a complete end-to-end platform that focuses on business value delivery.
04:04You mentioned the word adoption.
04:06Let me go ahead and say, in my opinion, there's been a lot of discussion
04:09about the promise of AI for enterprises.
04:11You kind of mentioned it.
04:12We've seen it.
04:13I can't remember some fast-food place which is now integrating AI when it
04:16comes to drive-through aspects of it.
04:18You have apps that are using AI to respond back, whether it's in the
04:21medical field, the airline field, or whatever the case may be.
04:24But there now seems to be maybe a little bit of not as fast of an
04:28acceleration of the pace as some people may have expected.
04:31In your opinion, can you explain the viewpoint on the delayed AI adoption,
04:34or do you not agree with that at all, and do you feel like, no,
04:36they have been adopting at a pace that you're happy with?
04:39No, no.
04:40The adoption definitely, like now, we need to go a long way there.
04:44But many people still seem to think that AI is not a big deal.
04:48And frankly speaking, they are wrong.
04:50They are not considering the reality.
04:52Because in today's world, AI may not replace humans, but the reality is
04:58companies and people using AI will end up replacing companies and
05:03people not using AI.
05:05The problem today is that most of the AI solutions are generic and
05:09takes too long to deploy and haven't been designed to solve specific
05:13enterprise use cases.
05:15It is not secure and does not add to the enterprise intelligence.
05:19The customizations, I mean, in our case, the customization and
05:22specific models provided by our platform are what is driving our
05:26success by driving business value for end customers, right?
05:29Yeah.
05:30So typically what happens is that businesses need a way to drive value
05:34with AI, solving specific problems end-to-end without human intervention,
05:39without having to process the deep AI technical know-how.
05:44There are too many, like you rightly said, there are too many AI
05:46solutions, takes too long to deploy, does not deliver on the value
05:50promised by the hype of AI.
05:52This is exactly where ILE Applied AI Platform with our no-code canvas,
05:58AI engines, and our global partner ecosystem comes into the picture
06:03to help the enterprises to overcome these AI challenges and essentially
06:08driving enterprise adoption of AI and enterprise intelligence.
06:12That's the holy grail that we are driving for.
06:14Yeah.
06:15There was an article that I read on CNN.
06:17It said more than half, so approximately 61%, is what they quoted,
06:20of large U.S. firms had planned to use AI within the next year to
06:23automate tasks previously done by employees, by humans.
06:27And then, I mean, I know for me in my personal life as well,
06:30AI makes me better in my critical thinking.
06:33It lets me think outside the box.
06:35Let me think of different ways to attack strategies that I might not
06:38be familiar with.
06:39So not only does it kind of elevate the thinking, but also speed is a
06:43factor as well.
06:44So I'm no longer spending an hour, two hours thinking of like a strategy.
06:47I'm just a consumer of it, right?
06:49I'm not an enterprise.
06:50So you can only imagine how often they use it.
06:52I think there was another company that's using AI to replace their
06:56customer service employees because you are able to respond faster and
07:00you're able to respond to a lot more individuals and solve their problems
07:04with more accuracy as well.
07:06I think that's incredible there.
07:09Those are good things.
07:11What are some challenges that you see in having this adoption be as
07:15widespread as we would like, or at least I would like?
07:18What are some challenges you see in the AI adoption space, especially
07:21when it comes to enterprises?
07:23So one of these, basically, I would say that some level of distress
07:27with AI itself in terms of people know that AI, and then especially
07:31with large language models, there were so many instances of
07:34hallucinations to data leakage to various different aspects there.
07:38That is one, definitely.
07:40So basically in any large enterprise, when you look at, they are hesitant
07:43from an adoption point of view, that is where.
07:46But what we have been seeing is that we have been pretty successful
07:49in terms of converting our prospects into customers because of the
07:52value delivery that we are looking at.
07:54Because now suddenly, like, you know, with our platform, what the
07:57enterprises are looking at is that they are able to productize
08:01their institutional knowledge and deliver that at the right place,
08:05at the right time, to the right stakeholders, right?
08:09And the enterprises are sure that the AI works only within their data,
08:14and they are sure that the learnings are not leaking out of the
08:17organization for a larger model training and stuff like that.
08:22So basically we are able to provide that kind of a comfort as well
08:25as assurance to our customers.
08:27And that's definitely driving our adoption.
08:29And that shows in terms of our scale as well, because right now
08:33we started on this journey of enterprise intelligence in 2010.
08:37Now today we have global offices.
08:39We have around 4 million users, around 1,000 plus enterprise customers.
08:43You know, I have a wide range of partner ecosystems.
08:46So it's testament to that, our credibility there.
08:50Yeah, and, you know, we've seen what happened with CrowdStrike,
08:52and, you know, it wasn't anything, you know, it wasn't a negative thing
08:57in terms of it didn't get hacked or anything like that, but it was
08:59something that did impact so many different businesses.
09:01Their stock price took such a big hit as well.
09:03So it is very important to make sure that things run effectively,
09:07but also securely as well in terms of data, because now we are sharing
09:10more and more and more of our, you know, habits and our tendencies
09:15for these targeted ads and for anything else that might be used.
09:18I want to give you the floor.
09:20I've only got a minute here with you, but any final thoughts,
09:22any topics that you want to talk about that I didn't get a chance
09:24to bring up, the floor is yours with our viewers.
09:27So, yeah, so basically what I wanted to talk about is basically
09:30in terms of our AI engine.
09:32So basically the concept is that the AI engines are sometimes called
09:35as hyperapps that allows any business to get the value out of AI
09:39very quickly because of the pre-trained models, data and model pipelines
09:44and ease of deployment.
09:45So basically like, you know, the AI engines, coordinating AI engines
09:50along with humans is the kind of an enterprise workforce that we envision
09:55in the future where AI works, and if I may say so, shoulder to shoulder
10:01with humans to drive the outcomes that you desire and in a very, very,
10:06very secure, safe, and ethical way, you know, because that's also
10:11a very, very important consideration because it's a new space
10:14that we are in and we are to be like, you know, the environment
10:18as well as ethical consideration has to go in.
10:21So we drive that engagement there.
10:23Awesome. Well, I appreciate your insights.
10:25It's always good to talk AI, especially from the enterprise side
10:27because, again, I know about it from the consumer end,
10:29but it's always great to get the other side of it as well.
10:31Thank you so much for your time. I really appreciate it here today, Sanjeev.
10:34Thank you. Thank you for having me here, Sunit.