iLearningEngines – Hear From The Chief Architect Of This Applied AI Platform - video Dailymotion

Benzinga

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.

Transcript

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.

iLearningEngines – Hear From The Chief Architect Of This Applied AI Platform

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