AI and The Future of Enterprise Knowledge Access: Arvind Jain, CEO Glean – Ep 1

Welcome to What the futr Podcast — where we dive into what’s next in AI, tech, sales, and the messy, brilliant human hustle behind it all.

This episode features Sandesh Patel and Chris Brandt in conversation with Arvind Jain, Founder & CEO of Glean - the AI-powered search engine that’s quietly killing your team’s knowledge discovery chaos. 

In this episode of What the futr, Arvind Jain, Sandesh Patel, and Chris Brandt get into the real story behind Glean — how it started, what makes it tick, and how it's helping teams ditch the chaos and get things done. The conversation delves into security concerns, building AI that won’t leak your secrets, and why it is important to stop overthinking and start experimenting with AI.

From RAG prototypes to building trustworthy agentic AI, this episode’s a no-fluff download for founders, sellers, builders, and anyone trying to make sense of AI’s wild new frontier.

Happy to have you, Arvind.

Arvind Jain is a serial founder who made Google Search smarter. Ex-Google, ex-Rubrik, now CEO of Glean — he’s built billion-dollar companies by doing what most won’t: solving real problems.

LinkedIn: https://www.linkedin.com/in/jain-arvind/

Glean: https://www.glean.com/

Subscribe for regular episodes.

👉 Explore the platform: https://futrconnect.io

👉 Business inquiries: sandesh@futrconnect.io

Transcript

00:00:00:05 - 00:00:21:15
Sandesh
Welcome and thank you for tuning in to What the Future podcast. Today is a special one. We are showcasing our very first AI startup, glean, with their CEO and founder, Arvind Jain. Now, you might know Arvind from his days at Google where he worked on this little project called Google Search, which obviously has gone on to be the largest, most popular search engine in the world.

00:00:21:17 - 00:00:42:08
Sandesh
He later on to be co-founder of Rubrik with just went public last year and now he's moved on to clean. Why do I like these guys so much? First, it's the people. Not only does Arvind have the chops to be a CEO and founder of glean, but he's also surrounded himself with great leaders, including great investors, advisors, and he's recruiting great salespeople.

00:00:42:10 - 00:01:04:21
Sandesh
Second, the numbers the numbers don't lie. 600 million in funding at a $4.6 billion valuation. They have over 400 customers. And within three years, they got to a 100 million IRR, which is very rare in this business. And last. I love that they're going after a huge market. There's going to be a lot of competition in this space.

00:01:04:22 - 00:01:20:05
Sandesh
So it's going to be very interesting to see what happens. Glen, start off as more of a search engine and now they move on moved on more till now. I know if you don't know what a genetic AI is or agents, you will soon and hopefully we can help you understand that a little bit better. Thank you for tuning in.

00:01:20:09 - 00:01:24:16
Sandesh
Hope you enjoy the show.

00:01:24:18 - 00:01:30:13
Sandesh
You got to change the game.

00:01:30:15 - 00:01:34:18
Sandesh
So.

00:01:34:19 - 00:01:57:18
Sandesh
I'm often talking to people about what's that next great technology or what's that next new trend or what's the next great company. What I always find myself promoting for the last year has been glean. And so I'm super excited today to have their CEO and founder, Mr. Arvind Jain, thank you so much for joining us.

00:01:57:20 - 00:01:59:12
Arvind
Thank you for having me.

00:01:59:13 - 00:02:02:18
Chris
Welcome. It's exciting to get a chance to talk to you for sure.

00:02:02:20 - 00:02:29:03
Sandesh
So Arvind, I have been in sales tech sales my entire career. I talk to salespeople all the time, talk to sales leaders, Cros. It's a group, a community that's really tight. And when I see certain salespeople go to certain companies, I start to take notice. And you did that. And I also understand you went from 0 to 100, million in, in three years.

00:02:29:07 - 00:02:49:13
Sandesh
Okay. So those salespeople that went there early are now benefiting from your growth. So I have seen you guys from the outside. I'm so excited to hear the whole story. But maybe if you can start first with, like, your founder story and how did you end up with glean?

00:02:49:15 - 00:03:20:06
Arvind
Sure. So my background is I grew up in India. Went to, study computer science, got engineering degree and then came to the states, worked at quite a few companies, many startups. Google being one of them. And then we started Rubrik in 2014. And that's, that was, that was the first time that I was actually, you know, learned how to be an entrepreneur.

00:03:20:08 - 00:04:00:21
Arvind
We had good success with the company, grew fast. And but five years in, we started to realize that the company was actually not, you know, doing as well as we wanted it to be. Our productivity was dropping as we were growing the team. And and that's when we this idea for green came about, because one of the big reasons for why we were struggling to, have the same level of efficiency and productivity as we used to have when we were smaller, was that as a company grew, people started to get lost, like they couldn't figure out, you know, where the right information was that they needed to do their work.

00:04:00:22 - 00:04:15:21
Arvind
They couldn't figure out who were the people who could help them. And and that's a problem that, you know, you know, that's not a new problem. Like, you know, I always face that, I faced that at Google, like, you know, ironically, where we were working hard on making it easy for people to find information in their personal lives.

00:04:15:21 - 00:04:37:15
Arvind
But we're not helping any one of us inside the company find anything. You couldn't find anything inside Google. And and so is the problem that has often like, you know, made me struggle. And 2019 was the time when I when I felt was enough and I wanted to just solve this, solve enterprise search. As a, as a as a challenge and started clean.

00:04:37:17 - 00:04:46:00
Sandesh
So you've had this amazing success. What do you attribute that to? What did you guys get? Right?

00:04:46:01 - 00:05:10:00
Arvind
Well, I mean, the the first thing first, like, this is a large problem when you think about any person in any company in the world, when they work, of course you need knowledge. You need information, to do your work. You know, as, as a knowledge worker, and we living in this world where we are inundated with information, there's a lot of data inside of companies.

00:05:10:00 - 00:05:43:14
Arvind
There's a lot of documentation. Also spread across many, many different systems. The SAS transformation and the revolution that we went through, it further fragmented our enterprise data and knowledge into many different silos. So the problem of like, you know, I need some information to do my work. This is very fundamental. And unfortunately it wasn't solved. So that allows us to actually be in this market where every single company in the world is a potential customer.

00:05:43:16 - 00:06:14:17
Arvind
In fact, every employee in the in that company is going to be a user of our product. So we are in a very, very large market, which is also, not created yet in the sense that the, we are not there is not a lot of competition. There's not a lot of other great products out there. And we get to shine, you know, with the product because, you know, we we, we took interest in this solving this problem before other people did in some ways.

00:06:14:18 - 00:06:32:12
Arvind
So I guess that's that's the that's the core for whatever level of success, you know, it's, you know, attaining right achieving right now. I mean, it's very early, just to be clear. Like, you know, I think you made it sound like, you know, we have within this world that's not the case. But, but but I think, you know, we have a good start.

00:06:32:12 - 00:06:34:08
Arvind
We have a good technology for sure.

00:06:34:08 - 00:06:56:21
Sandesh
For sure. But I do want to call out that from we are in a focused podcast. Right. And so we are going to be focusing on this market specifically with businesses and enterprise. That's going to be our focus. But I look at the AI space and I see so much investment going in, and I just don't see as much returns coming in.

00:06:56:23 - 00:07:24:06
Sandesh
And that has been such a huge gap. And so, like, as much as you're humble about the 100 million, you know, there are three years. I totally understand what you're saying. But I also think what you're backing up, what I've been suspecting has been AI is creating this amazing opportunity to do things differently. Yeah. So it seems like it's not just your your brilliance and, you know, the people and everything else.

00:07:24:06 - 00:07:30:03
Sandesh
There's some market wins that are in your favor. Yeah, there are helping you with that growth, right?

00:07:30:05 - 00:07:54:11
Arvind
Hundred percent. Like, if you think about the what is the largest application of AI today in consumer or in enterprise, it is knowledge access. It is. Yes. You know, people using AI as a tool to ask questions, get answers back or ask a AI to do some work for them, which AI is able to complete with a human like intelligence.

00:07:54:12 - 00:08:25:12
Arvind
So so knowledge access is the largest application. And so the fact that, you know, we were working on, knowledge access as our core problem actually put us in the right time, in the right place. The there's a desert like when think about enterprises is actually a very hard problem to make AI work inside your enterprise. You have lots of data, but it's actually spread across many, many different systems.

00:08:25:14 - 00:08:48:17
Arvind
This data is actually not like the data on the public web, that everybody in their company can access. All the data is permissioned, is secured. And so you can't actually just take the same AI technology, how it was built outside enterprise and actually make it work in enterprise. You have to sort of you have to figure out different solutions and be able to figuring out those solutions.

00:08:48:19 - 00:09:07:12
Arvind
For the last six years, because, you know, this was our goal, that people come and ask questions in glean and we answer those questions for them. We had we had access to the Transformers models. In fact, when we probably the first company to bring Transformers into the enterprise, we're working on these models in 2019. But those models were not as good at the time.

00:09:07:14 - 00:09:28:14
Arvind
So we couldn't imagine in 2019 that using these models, we can take people's questions and answer them. You know, we could only go as far as like, you know, we could take their questions and understand them to at some degree of conception, you know, like, you know, conceptually and, and surface the right information matched up with the right information inside your company.

00:09:28:19 - 00:09:47:23
Arvind
But we're still thinking in the realm of, people ask questions and we surface information. But as, as these models, as AI models got better and better, it allowed us to create this amazing ChatGPT like experience where you come to glean, you ask questions, and we can answer all of those questions using all of the world's knowledge, but also all of internal knowledge.

00:09:48:05 - 00:10:13:18
Arvind
So, so AI has been a big factor both in terms of technology, like how it actually made our product so much better. Help us achieve our mission, you know, in a much more accelerated fashion. But it also created that demand in the market. So before we to evangelize, remember I told you that we had to create the market and we had to go in and convince people that, hey, like, you should usually go and invest in a good search product.

00:10:13:20 - 00:10:32:04
Arvind
And but now once people, once people start at GPT, everybody wants to take Jupiter inside their company. And that's what we are. So so it actually created that, you know, demand also instantly. And and so those are some of the factors. So you write that like, you know, AI has played a big role in actually making us successful.

00:10:32:06 - 00:10:45:12
Chris
Cool. Can we take a step back just a second. And for the people who aren't haven't used clean in the past, could you just tell us, you know, the bigger value proposition? Because we're talking about a lot of AI search and things like that, but glean is a lot.

00:10:45:14 - 00:11:11:08
Arvind
Yeah. So so glean like first, you know, think of glean just like, you know, jagged is the jagged inside your company. Glean is connected with all of your enterprise systems. It knows what people are talking about in slack. It knows, what documents people are writing in Google Drive are are SharePoint. It's connected to your Salesforce, workday or ServiceNow, like all the different systems in inside your enterprise.

00:11:11:10 - 00:11:33:21
Arvind
And and using all of that, it basically builds an understanding of your company. It understands your people, your business, your documents and knowledge and relationships between them. After we do all of that, now, we give you a attribute like experience. You come in to ask questions, and we will use all of the world's knowledge, as well as all of internal company's data and knowledge in a safe, safe and secure way.

00:11:33:23 - 00:11:58:03
Arvind
To deliver those answers back to you. But it's the AI product, so you can also give it some work and will actually do that work for you. And so that's the that's the core of what VR is. It's a, it's a more powerful version of ChatGPT. Inside your business. But the the same platform that we've used to build this product, we also make it directly available to our customers.

00:11:58:05 - 00:12:24:16
Arvind
And that actually makes us a very powerful AI agent building platform. So you can take the clean product inside your company, and now you can actually start to build these, you know, functional agents across different departments. You can build an agent, in your H.R. team to help answer people's questions. You can build a agent in your legal team to automatically red line third party contracts.

00:12:24:18 - 00:12:42:11
Arvind
You can build an agent, you know, in your sales team to prospect and find new customers. We are a horizontal platform since we are connected with all of your enterprise systems. We're able to actually give you one single unified platform where you can build agents, you know, for all the different business use cases.

00:12:42:12 - 00:13:05:04
Chris
Yeah. So, I mean, the thing that's interesting about this is what you're talking about, you know, when when, OpenAI created ChatGPT and everybody started taking a look at that and like you say, everybody wanted that inside their company, you know, and then what we saw was the advent of sort of the rag model resource augmented generation that went along with, you know, ChatGPT and integrated into that.

00:13:05:06 - 00:13:23:12
Chris
But there's a lot of complexity with that, right? I mean, you had to have things in the right format. You had to have them accessible to, you know, various databases and things like that. You had aggregate that information. And, and basically what you're doing is you're connecting to all these different platforms and just integrating that data. So that work is kind of already done.

00:13:23:12 - 00:14:02:19
Chris
Right. And then, you know, like, as somebody who uses glean pretty much on a daily basis, I would say, I gotta say, you mentioned the agents and I will say, I think that's one of the, the best features because, you know, one of the things that's challenging about a big search is how much data you surface, you know, and, and the, the two things that I think are super useful in glean are the agents, you know, the sort of like you have a bot that just specifically tailors itself to information, you know, like I want all the competitive information and that goes here.

00:14:02:19 - 00:14:18:09
Chris
I want all the engineering information that goes here. And you have an agent that that surfaces that, and then and then I think the other thing that is really interesting about it, too, is the the concept of collections, where you can organize all that into collections. Can you talk about how that all interacts?

00:14:18:11 - 00:14:42:10
Arvind
So we start first with the building, the core platform, you know, connecting all the different systems. Now, you know, typically in a business, you know, they will do two things. You they will take our general purpose assistant and they'll give it to all of their employees. And the model there is that. Well, look, this is a safer, more comprehensive version of ChatGPT.

00:14:42:12 - 00:15:04:18
Arvind
Do whatever you want to do with it. Is connected to all of the world's data. Is connected to all of your internal data. So it's not. It's not targeted to solve a specific problem. It's supposed to be this general purpose AI assistant. And and so the goal, the goal behind that is that like, you know, like let's I bring AI to everybody's, you know, day to day work.

00:15:04:20 - 00:15:28:03
Arvind
Help people, become experts. You know, in terms of using AI, make it part of their day to day habit. And actually hopefully save them a few hours of time every, every week, as they do their work, like, you know, they can offload some of that to this personal assistant. So that's the that's the the first thing that typically companies will do.

00:15:28:05 - 00:15:54:23
Arvind
But then like once you once the platform is running inside, inside your organization. Now we will actually go and work with each of our functional teams. We'll spend some time with our, you know, it team, with your team, engineering team, sales support, legal. And the idea is to understand what are some of those key business processes that consume a lot of time, today, for them.

00:15:55:01 - 00:16:22:20
Arvind
And so for the legal team, it could be, this, that is a you need a lot of people to red line third party contracts that are coming your way. And and so then we will say that, look, you know, we'll take these time consuming business processes and we're going to build a specific agent that works with only the relevant knowledge, that is needed for that particular task.

00:16:22:22 - 00:16:45:19
Arvind
And, and it will actually have a few additional capabilities. So, you know, you'll have specific instructions. For example, in this case, a paralegal, they have a process, you know, they have something in their mind, like, you know, how when they go to view a third party contract, what are the things they're looking for? The thinking they're looking at indemnity clause and they'll compare it with, you know, with your standard paper to see like what the differences are.

00:16:46:01 - 00:17:08:22
Arvind
So there's a, there's a lot of like, embedded knowledge that you can actually now tell AI when you building this agent, you can tell that, hey, this is how I do this work. Now you have to do it for me. So these agents are typically, built where they solve a very specific functional use case. They're connected with only a subset of your company's information.

00:17:09:00 - 00:17:37:19
Arvind
They have some extra instruction and logic, and and then finally, you know, they have the ability to actually make changes in your, in your system. So they're not just answering questions and actually doing some work and saving that work in your enterprise systems. So that's typically the process that we follow. And then we see like agents across all these different teams that, you know, companies have built like, you know, like we've taken about like 100 million agent take actions like in the in the last one year as we started to sort of roll out this platform.

00:17:37:21 - 00:17:39:08
Arvind
Wow, wow.

00:17:39:10 - 00:18:04:07
Chris
You know, I'll say there's another really interesting, use case for glean that I really like. And, you know, there's so many people out there using slack but surfacing and there's so much information in slack. I mean, especially in an organization that's centered around slack, for example. And, and like getting at that information is really hard but so incredibly useful.

00:18:04:07 - 00:18:18:02
Chris
And Glenn does a great job of finding those threads inside of, inside of slack to, to surface those so that you can really get useful information out of them. You talk to.

00:18:18:04 - 00:18:38:20
Arvind
A lot of times, first of all, like, you know, AI works well if it learns from the humans, you know, inside your company, and there is no better place to learn, how people are interacting and how they're working. But to go in slack, that's the melting pot. That's where, yeah, discussions happen. That's where people ask questions as well.

00:18:38:23 - 00:18:57:07
Arvind
You know, other people answer those questions. And the interesting thing is that so we are connected like, you know, slack is one of our data sources, just like any others, you know, like all the other systems that I mentioned. But one of the most important ones, because this is where we learn things like, you know, who are subject matter experts on different topics.

00:18:57:09 - 00:19:36:17
Arvind
Sure. You know, in the past, like, you know, this was something that companies would try to catalog and those catalogs will become obsolete, you know, before they actually even get, you know, get built out. And but now you can actually see, like you can see on any given topic, any given subject matter, what the people who are most active, who are the ones who are, responding to answers that people, people have and, and so that that serves as a, as a very good, sort of input for us to, to understand and enterprise, to understand people and, understand also like what knowledge is the most meaningful one, what people, what what knowledge

00:19:36:17 - 00:19:55:03
Arvind
has high engagement. But we do that same work across many, many different systems. We're doing the same thing within Google, right? Right. You know, like think about like a simple question like, let's let's say I'm looking for a product roadmap. In our company we must have 10,000 product products. And, you know, they've all been built over the years.

00:19:55:05 - 00:20:12:01
Arvind
So when I'm asking for one, right now, most likely I actually we tend to look for a new one, like not once. So. So the AI systems have to learn how to ignore the old ones. I'm also probably looking for one that's written by the head of product or somebody in the product team. Not I'm not looking for the product.

00:20:12:02 - 00:20:28:05
Arvind
You know, a copy of the document that a sales person made to to actually share with the customer. They have to sort of go and understand these kind of nuances about the business. You really have to learn like how a human learns inside a company. And that's when your system actually works.

00:20:28:07 - 00:20:44:10
Chris
Yeah, I find that because, you know, a lot of individuals in a company will create bits of content and presentations, and they'll slightly adapt them for very specific kind of scenarios and the ability to, like, surface that stuff so that you can actually access it is is really valuable.

00:20:44:11 - 00:20:46:04
Arvind
Absolutely.

00:20:46:06 - 00:21:05:00
Sandesh
So we establish that there's a a nice, momentum going into AI. Where do you think it goes from here? What do you envision for the future of AI search and specifically for glean?

00:21:05:02 - 00:21:36:04
Arvind
We are in a very early stages. The market today, first of all, from an AI perspective, the AI is going to be a fundamental part of our lives. A lot of work that we do as a knowledge worker, we won't be doing that anymore five years from now. And. Search is going to be a core, one of the top use cases of AI.

00:21:36:04 - 00:21:58:19
Arvind
It is today and will remain the top use cases for AI in the next five years. What it means for us as a company is that I think we believe we have a big opportunity to to succeed here as the first as the first mover, as the recognized leader, in this space today. And, and we're excited about that.

00:21:58:19 - 00:22:25:02
Arvind
We're excited about transforming work for people and, and, and get to this, this future world, like, you know, the world that we think we are going to be in where imagine, like today, like if you're a CEO of a company, you get a lot of luxuries, you know, with that role, you you got assistants, you have a chief of staff, you have an executive team.

00:22:25:04 - 00:22:52:21
Arvind
You wouldn't get coaches like, you know, just like professional sports players, CEOs these days, you don't get great coaches. That is this amazing team of people around you that makes you the superstar, that makes you the person that makes a lot of impact inside the company. But if you look at a, a new graduate that joins your company, they got none of that luxuries that to be on their own.

00:22:52:23 - 00:23:22:07
Arvind
Now, I think in the future we believe that everyone, regardless of your seniority, you're going to have this amazing team around you, a team of assistants, coworkers and coaches that are not only going to be doing most of your work for you, but they're also going to help you become better at at why? At what you do. They will coach you, offer that personalized coaching.

00:23:22:09 - 00:23:51:05
Arvind
And the only difference is that this team is not a team of humans anymore. Of course, you know, this is a team of AI agents that is helping you continuously with your work. And that's the that's the opportunity for us. When you think about search, search actually evolves. We started with a search, which is a Google like experience where well, give me a few keywords or ask me a question and I'll try to surface a few links to the right information.

00:23:51:07 - 00:24:11:02
Arvind
And then you're on your own. Like go and read those documents. Hopefully you will find what you're looking for. So evolve from there to this new model which is ChatGPT where? Well, no, ask the question I give. I'll give you the precise answer. I am not going to make you go read a 30 page document. But it just keeps evolving from there.

00:24:11:04 - 00:24:39:15
Arvind
The next, the next stage of it is that it's not just it's not just sitting there waiting for you to go and ask a question and then it responds with an answer is going to become proactive. It actually is always with you. It knows your work life, it knows what you're doing right now. It detects that you have a question or to do working on this piece, and it can actually help you by surfacing some information back to you.

00:24:39:17 - 00:24:52:04
Arvind
It becomes proactive. So that's sort of like, you know, that's the that's how like when you think about the evolution of search, we're going to continuously go and see it becoming more and more powerful, and more and more proactive.

00:24:52:06 - 00:25:18:12
Chris
Yeah. Yeah. You know, you one of the things that you guys have done in a very short amount of time is you've scaled, you know, very quickly. And I think, you know, there's a couple things that go along with that. Like, you know, when you're working with AI and you're working with confidential documents internally, you know, scaling for large enterprises is is really a challenging thing.

00:25:18:14 - 00:25:28:22
Chris
But beyond that, scaling and keeping everything secure is a really difficult challenge. How did you approach that?

00:25:29:00 - 00:25:58:10
Arvind
Great question. The security is actually one of the most important, you know, prerequisite, to rolling out AI in a, in a, in a, in a, you know, in a effective, scalable manner inside your company. You have to you to solve for a lot of different types of security problems here to make sure that none of your data leaves your enterprise.

00:25:58:12 - 00:26:22:17
Arvind
So when you build your technology, you know, we from day one built our product in a way where it can actually live within your own cloud premises. Because imagine this. Like as a startup, you know, I go and ask Coca-Cola that people like, you know, I'll build a great search experience for you. All you have to do is give me all of your data across all of your different systems and.

00:26:22:19 - 00:26:23:17
Chris
And your recipes.

00:26:23:17 - 00:26:50:07
Arvind
And so that's that's not going to fly. So you have to build the system where you can tell them that, look I'm not taking anything away. None of your data is going to leave your environment. So that was the first security problem that we had to solve. And this applies to AI, and the model and inferencing, like no company wants, you know, those sensitive data that now people are putting into this chatbot interfaces to leave their company and become part of the training data set of these models.

00:26:50:09 - 00:26:59:08
Chris
And that's a big problem for a lot of companies. I think a lot of companies don't realize they've got a lot of employees out there that are just going to the free version of ChatGPT.

00:26:59:10 - 00:26:59:19
Arvind
Doing that.

00:27:00:00 - 00:27:03:14
Chris
And basically leaking all their private information out onto the internet.

00:27:03:14 - 00:27:18:20
Arvind
The problems you got to solve for that, and I think, like, you know, the enterprise version of these products as well as clean, of course, you know, we we will give you that guarantee that none of your data is ever going to be used to train these models. Right. And but that's actually only part of the challenge.

00:27:18:20 - 00:27:38:04
Arvind
The second challenge, is that when information inside the company is, is, you know, is protected. You may have a document that you write and you kept it for only for yourself. It's private to you. Or you can share it with two other people. And so everybody else in the company should not be able to make use of that information.

00:27:38:06 - 00:27:56:06
Arvind
You can't train all of your, you can't train your models on all of your enterprise data. So to do this safely and any AI experience that you build, you have to understand what knowledge does the individual has access to and only use that to help them with AI on it. So that's why we do so we do a lot of work on that.

00:27:56:06 - 00:28:16:21
Arvind
Understanding permissions and governance architecture across these systems, across these and, you know, applications at the company. And, and, you know, go above and beyond that too, because oftentimes companies don't have great control, governance, you know, controls in place, like they have gaps in sensitive documents that are sitting somewhere in SharePoint. Nobody but, you know, nobody can find it.

00:28:16:21 - 00:28:40:15
Arvind
So it's okay today, but they're not protected. Like, you know, somehow somehow discovered some somebody discovered them, they could access it. So we like, you know, we do a lot of work on that front to understand, like if there are over exposed sensitive documents inside the company and how do you keep how do you make sure that you are above and beyond permissions and protect, you know, exposure of that document in AI?

00:28:40:17 - 00:29:02:00
Arvind
And then like, you know, this is a new space. I, is, you know, is helping you do things in a different way. And similarly, there are new types of security attacks, you know, that are not possible. For example, they can be prompt injection attacks. And before you realize it, like, you know, sensitive information is leaking, you know, company.

00:29:02:02 - 00:29:21:20
Arvind
And so you have to sort of be robust to that. So, so this is a place where we spend so much of our time. In fact, the, the I think we're in a sales cycle because you talk about sales, the I would say that 50% of our time, when we're trying to sell is actually talking about these problems.

00:29:21:22 - 00:29:34:22
Arvind
And over time or over the years here to figure out how to change those conversations from being defensive and try to win the hearts of of the security team.

00:29:35:00 - 00:29:36:07
Chris
Yeah, hearts of mine to.

00:29:36:07 - 00:29:54:08
Arvind
To actually go on the offensive. And as we try to understand what they are worried about and like as I, you know, get rolled out, they know this and what are the things they need to do to actually be ready for it. And so like a lot of our features now, I see features are being built for the security teams.

00:29:54:10 - 00:30:30:01
Chris
Well, and that's got to be a really big differentiator for you guys. And when I say differentiator, you know some of the competition you're going up against, you know there's other competitors out in the field. But the probably the bigger one is like doing it yourself inside your company. And you know, from what I've seen out there, a lot of folks, you know, they're trying to build a drag model, you know, for use inside their company and they don't have the expertise or the experience or quite frankly, you know, the vast user base to test it against to really surface a lot of those security challenges.

00:30:30:01 - 00:30:48:07
Chris
So, you know, they start rolling these models out and these these rag, you know, augmented, search functions within their company. And it's it's it's a train wreck. Right. So I mean, that's got to be something you can walk in and just say, hey, wow. You know, don't don't waste your time doing that. We've already got that problem solved.

00:30:48:07 - 00:30:48:11
Chris
Yeah.

00:30:48:11 - 00:31:09:11
Arvind
That's that's definitely a big one. I think DIY is it has been the largest competition in some ways, but I think it's not a bad idea. Like I think it's good for enterprises to actually get their hands dirty, to actually play with these systems, to actually understand, like, you know, what are some of the key challenges as they build these AI systems.

00:31:09:13 - 00:31:10:17
Chris
So they appreciate you more?

00:31:10:17 - 00:31:34:20
Arvind
Yeah. Well, one thing that that's true, but but also like, you know, I think they need to learn like I think I think like any every enterprise out there, they need to make sure that there's enough exposure to both using and building AI systems internally. So for us, like, you know, what has happened here more is, you know, people build these initial drag prototypes and they will take that, okay.

00:31:34:20 - 00:31:54:15
Arvind
Like, you know, I want this, you know, this application I want to work on this set of files that I have in this, you know, in this particular folder in Google Drive. And I'm going to take all of them. I'm going to stand up a vector database, chunk those contents, put them in. And now I actually have a nice experience.

00:31:54:15 - 00:32:11:16
Arvind
And then they realize that, oh, I have to do this every day because there's more content being generated. And then they also realize that, well, I mean, you know, this content like, in it had permission sets on it, and I'm not going to actually go and work on figuring out what information can be accessed by home and build all these access controls.

00:32:11:21 - 00:32:34:05
Arvind
So that's when they come to us and they say that, look, you know, we figured out like, you know, there's a use case, there's value, we know what we're doing and not just help us take care of those infrastructure type, you know, level level level technologies. And so it actually was, you know, pretty good for us. So like DIY I would say has been has been a good has been a good source of leads for us.

00:32:34:07 - 00:32:38:17
Chris
Do you do a lot of professional services with your deployments. Is that a big part of it?

00:32:38:18 - 00:33:17:04
Arvind
We we don't do as we, we, we do have, professional services team. In fact, we also have a team that's called the AI Outcomes team. And this team will actually help our customers build agents, build prompts and the but but I think like the our core model is, that we're bringing a technology to you and we will bring some support with that, but but we're not actually building for example, we're not writing a lot of code for our customers as professional services.

00:33:17:06 - 00:33:36:02
Arvind
We may write some in some agents for them, but most of it is like, think of it as initial training and onboarding like services that are sort of meant for that. Goal is to make the customer self-sufficient, you know, with our system. And so, like, you know, in like in six months, for example.

00:33:36:04 - 00:33:43:17
Sandesh
I'm curious who is your ideal customer, who are you selling to?

00:33:43:19 - 00:34:01:22
Arvind
So we typically work with the large enterprises and midsize enterprises. This is actually a very interesting problem. We have a product that appears to everyone I think would be the smallest. My banking in the largest in the largest company. And you could be engineer or you could be a marketer, or it could be a person. Legal.

00:34:02:04 - 00:34:45:18
Arvind
This is so fundamental. So like internally, like we have we have different teams like we, we actually cater to, you know, any company that is 100 employees all the way to 2000 employees, more than 50% of our effort is on the large enterprises. But we've segmented the markets. This is, you know, this is a, and then within like, within industry verticals, we have largely like, focused on, like around 5 to 6, key industry verticals, including, of course, technology, financials, health care, manufacturing, retail, telco, the but but, but we are realizing increasingly that, you know, we need to figure out some other magic formula to scale ourselves and bring the

00:34:45:18 - 00:34:50:08
Arvind
product to everybody in the company. There's a there's a big need for it.

00:34:50:10 - 00:34:57:09
Chris
You got to find companies that have enough data to, to actually surface to make it worthwhile. I would imagine that's why the enterprise is so good.

00:34:57:09 - 00:35:16:12
Arvind
Yeah, I think I actually like I think the look, look, the data like we, we are in a very data rich world these days. And the you could actually be 100% company and you still are producing so much information you can't keep up with it. Like this. Go and slack and look at your slack and see you at 100% company.

00:35:16:12 - 00:35:30:03
Arvind
Like how many, how many messages are being exchanged every day. So data data is available at the, and that's why the product actually works very well. Like, you know, regardless of whether you are 100% company or a 1000 person company.

00:35:30:05 - 00:35:54:20
Sandesh
You know, what's really interesting to me is as a sales guy selling tech for so long, every company is asking themselves, how do you get to the business? How do you get to the business? We've always been selling to the tech. We've always been selling the CEO, CTO, you know, this is just such a great example of how AI is going to break so many of those silos that like now everyone is in technology.

00:35:54:20 - 00:36:13:12
Sandesh
If you're a CFO or a chief marketing officer or whatever sales officer, you need technology to be successful and AI is breaking that. So like I, I love that, you know, it's, it's pretty cool.

00:36:13:14 - 00:36:16:15
Chris
Exciting times. Totally.

00:36:16:17 - 00:36:29:06
Sandesh
So before we close it up, Arvin, please wrap it up for us. Like, what are the things that you want our viewers to know about glean and anything, any color you want to add about the future?

00:36:29:08 - 00:36:57:10
Arvind
Yeah. Well, first, I think the I think the advice that I have for everyone is like, go embrace AI today. Like whether it is our product or some other product. I think playing with AI is just incredible. The world collectively doesn't know what I can do for it today, like it's you only figured it out the more we actually, you know, ask, agree or ask screen to do something and see like you know how I fares at that.

00:36:57:15 - 00:37:17:21
Arvind
So I think being, you know, being in that mode where you can be experimental, where you can tinker and we can change your habit and instinct like it's my habit and thing now is that you ask me to do anything and I become lazy. Like the first thing I want to try do is when I see the AI is actually going to do it for me, they ask me to write, you know, my my note for the all hands.

00:37:17:21 - 00:37:50:01
Arvind
Like what? I'm going to speak with the people and first actually ask, you know, I do actually write the write the draft for me. And then of course I will tweak it. So and, but but in terms of like glean where we are headed. So so we are if you like, you know, if you are a company, with, you know, with the, you know, with a hundred people or more, we are part that can be useful to you, think of us as a horizontal AI investment, that you will make one product that you bring connected with all of your systems, and it will actually, you know, bring, you know, AI to

00:37:50:01 - 00:38:20:05
Arvind
you, to all of your different functions with a single platform. So it is effective, cost efficient strategy to bring clean, as your core AI platform for your entire enterprise. There's a lot of new stuff that is coming out, really excited about agents. The we've been shipping agents, for the last 18 months, but but the there's a lot of progress that the industry has made on on agent, systems with our agent platform.

00:38:20:10 - 00:38:40:10
Arvind
You don't have to be a developer. You don't have to be an ID. You can be an entire person. You could be a legal, lawyer. You could be a, you know, finance specialist. And yet you can take that painful business process that you have that you have to spend so much time and you don't like it and actually get command AI to actually do that work for you by building an agent.

00:38:40:10 - 00:38:43:19
Arvind
So that's what we're super excited about,

00:38:43:21 - 00:39:05:12
Sandesh
Agent tastic. That's going to be the word, that's going to be searched a lot as agents, for the next 12 months. That's going to be could be a big SEO word for sure. For sure. Yeah. Well, Mr. Jain, very cool stuff that you're doing. So proud of you. The whole team there glean doing what you guys are doing.

00:39:05:12 - 00:39:27:09
Sandesh
I wish you the best. Thank you so much for coming on the show. If anybody is interested in meeting with Glenn, please reach out to me personally and I'll make sure you are in good hands. Because this is, this is something that I think everybody needs to know about. Doesn't matter what role you are in the organization, you should know about.

00:39:27:09 - 00:39:29:19
Sandesh
Glenn. Thank you again.

00:39:29:21 - 00:39:30:12
Arvind
Thank you so much.

00:39:30:16 - 00:39:31:15
Chris
Thank you so much.

00:39:31:17 - 00:39:33:16
Arvind
Thank you.

00:39:33:18 - 00:40:06:23
Sandesh
Well, that's the show. But before you roll, sales pitch warning might get a bit scary. Ohio. We're building more than just a brand here. We're building a community of alphas. So do what all the other cool kids are doing and gas us up, bruh. Like, comment, subscribe. Follow. Leave. No crumbs. I'm being dead ass. Woof! Damn, I just ate that piece.