AI, Human Evidence, and Better Business Decisions

Amir: On this episode of the show, I have with me Sagar Kadakia. He is CEO and founder of Qualitate. And we're gonna be talking about intelligence, and we're gonna talk about how you're gonna sell that buyer intelligence, and what Sagar sees in terms of that and the emerging growth of AI, and how it's allowing us to get into areas that we could not.

And he mentioned something about human evidence is scarce, and I'm sure I'll ask him to tell us what that means. And also talking about capturing real-world evidence. We all do this. We just might not actually understand what we're doing. We're out searching for information, and Sagar's gonna walk us through all that stuff, and I'm excited to have you on the show.

Thanks for taking the time.

Sagar: Awesome. Amir, thank you so much. Uh, really, uh, really excited to be on here today. Abs- So thank you for having me.

Amir: Absolutely. All right, Qualitate. Tell us what you guys do at a high level.

Sagar: Yeah, just, uh, high level Qualitate, you know, we are helping businesses, you know, deeply understand their, their, their company, right, their industry, just like the whole world around them, right?

Their customers, their competitors, uh, their targets. We're, we're kinda giving them that information that you can only get from, from talking to people, right? That is the, the function of, of what primary, uh, research or primary information is. That is what we are doing here at Qualitate, right, at its core.

Uh, except for making it incredibly fast and, and cheap and integrated and embedded and, and, and accessible, right? So all the things that primary research is not today. Um, we have built these, uh, uh, AI-powered systems. Uh, they are just continuously going out there and, and capturing real-world evidence, right?

Uh, whether it's cybersecurity experts or, or hospital administrators or, or folks running HVAC businesses, uh, we are going out there just capturing all this real-world evidence, all this kind of human intelligence, right, using these AI- powered systems, uh, to do it on our behalf. We're taking all that information.

We're, we're, we're creating this really massive knowledge graph right around it, and then we are giving people access to this kind of, uh, agentic software application, right, where they can go in and, and they can start kind of querying, uh, uh, you know, people's minds, right, so to speak. And so when you kinda start to think about Qualitate, you think about a...

what does kind of, uh, the next generation of information look like, right? Today, a lot of folks use, you know, the traditional search engines or the frontier labs, right, which are really just kinda scraping the web and, and capturing information. Qualitate is, is, is like scraping people's minds effectively, right?

And, and, and our customers are able to kinda dig through all that information. And so this is ultimately at like a very high level, right, what Qualitate is, is, is doing and, and how we've started to kinda think through, you know, the most, uh, important information is the stuff in, in people's heads, and, and how do you get that information at scale using AI and deliver all that information to people.

Amir: Fantastic. I, I was gonna... I was probably gonna jump forward and ask you a couple questions, but as you were, as you were ex- you know, explaining what you guys do, it, it made me think of something that I've, um- held for these last couple years that, uh, these, uh, frontier models have come on the scene is you mentioned search, and, uh, everyone has run a Google search on Earth at this point, or n-nearly, I won't say everyone, but nearly everyone has run a Google search in their life.

And we're all used to getting results back and then having to go through to determine is that piece of information fit what we want? And we're trying to also understand, 'cause Google, and I-I'm not an SEO expert, but they go through, they try to make sure that there is, uh, some kind of, uh, uh, rank as to who the expert is within the room, and they provide those results.

We still have to go through that Uh, that, that is changing 'cause now we're going into solutions where we're looking something up on your favorite, uh, LLM and it's giving you back a, an answer, a single answer. And the thought is, is that that is now the correct answer. And, uh, it is interesting 'cause, uh, I think if, if, if you ask somebody two years ago whether or not a single answer would suffice if Google just showed up one link, people would have been up in arms. They're not now. Long-winded question, sorry. Um, but talk to us a little bit about that, that notion of searching, the understanding of d- domain, uh, expertise and, and just us humans, how we are viewing that.

Sagar: Yeah. Um, no, look, you, you bring up a, a lot of like interesting points and I'll, I'll try to break them down in, in a few pieces, maybe starting a little high level, which is I think, uh, maybe what you're getting at on the, on the latter point is like AI is kind of like the new interface for decision-making, right?

And so I, I think you're right. I think probably if you had just given someone a single result 5 or 10 years ago, maybe, uh, that's not what they wanted. Um, but now certainly the frontier, uh, models, right? Uh, uh, that's how people make decisions, right? I use them. Everybody uses them. But they have also made, uh, uh, intelligence like a commodity.

It's like abundant, right? Uh, like reasoning is no, is no longer scarce, right? And so, you know, where, how I kind of think about this is like there's almost like, uh, like two inputs that go into a, a, a, a decision like, uh, like intelligence, which I kind of mentioned is, is pretty much free at this point, right?

You can pretty much prompt your way through everything. Um, but then, but then like, like context, um, and, and like real world context and that's kind of what Qualitate is doing, right? It's, it's giving you that real world evidence that's, that's, that, that's scarce, right? You need that information along with intelligence, right?

Along with reasoning, right? To ultimately, um, uh, uh, make the most informed decision. Like I, I almost think about it this way. Um, in a world of, of let's-- we're in a world of AGI, right? What goes up in value? What do you absolutely need? You need services that require like... Or the, the, the most, uh, the most valuable services are gonna be the ones where there's like a human in the loop, right?

That is what Qualitate's doing, right? You can't query what's in people's heads. Uh, you have to go out there and, and capture all of that information. And so that's how I kind of think about, um- where Qualitate is and kind of this whole like net new decision-making architecture, right? Where yes, people are absolutely using, um, uh, whether it's traditional search engines or, uh, LLMs, but you're still missing the most valuable component, right? Which is the real world evidence. And, and that will only be more true, right? Every, every day perhaps that becomes more true, right? As the value of information publicly, right, goes, goes to zero, right? And really the, then the only value there is your ability to, you know, maybe, uh, aggregate that data, but really on primary evidence, right?

That's where all the, all, all the value, that's where the edge lives and, and that's how I think about how kind of Qualitate kind of fits into this whole like net new decision-making interface.

Amir: Yeah. I, I, I mean, absolutely. And, and I think w- when you're talking about that and, and we're, and we're looking at what people are, have always wanted, I mean, I think even, uh, a site like Yelp first started because people needed some confidence, uh, as to whether a service or a vendor, uh, was legitimately good.

I think that's just what humans have done. When you're looking at AI and you're looking at the opportunity to I, I, I don't know if the term is to come up with s- a single source of the truth, 'cause I, I think that's hard. But at least as you mentioned, bring that evidence to light so people are more confident, and if obviously this goes in the human loop and how AI is gonna really work in parallel.

Right now, a lot of us look at AI answers, and we're trying to use our best expertise in areas that we do not quite maybe understand, that we are not experts in. I mean, we're just assuming the AI's really great at grammar, so if it fixes something for you, you just go, "Wow, that's better than I would've done."

Um, maybe. I don't know. I mean, maybe it is r- better than I do. But going back to that human evidence and, and the scarcity, and, and you mentioned the fact that intelligence is becoming commodity. How does that translate? So if you're, if you're someone out there listening and you have a job and you're like, "Well, AI's coming for my job," does that narrative fit with that human evidence is going to be more scarce?

I mean, c- can both be true? Uh, what are your thoughts?

Sagar: Yeah, yeah. I, I, I, I, I do think both, both can be true. I think, um- You know, the way I kind of think about, uh, uh, AI today, right, um, is, and, and you can kind of see how it's been playing out the last couple of years, which is, um, where is AI having the impact now and where is AI going to have an impact, right? Uh, or start to have, have, have an impact. Um, and I'll use research as like a, uh, uh, as the example 'cause that's like an easy way to kind of ground the conversation, right? Since that's kind of what the, the business of what Qualitate is doing, right? You have a lot of, um, think about a lot of like the standalone research providers, right?

They were producing reports. They were selling the seats. Like that whole market has just gotten, you know, disintermediated, right? And the, it's unclear what the future of that is, right? And, and then you have, um, all these information providers that are like deeply embedded because they sell APIs or, or data feeds, right?

They're much harder to kind of like, you know, get out of an organization, right? Unless you have like very talented folks, right, who can kind of remove all that. And then you have this last layer, which is maybe what you're getting to, uh, which is this services layer, right? So all the big consulting firms and, and, and, and all the other service providers, which is like, can you use AI to create a product, right, that can ultimately, uh, uh, compete against that service, right?

Because services inherently exist because the, the requirements that are coming in are highly complex, right? Someone wants something so specific and so unique that they have to work with a human on the other side, and then that human's gonna charge them a lot of money and, and there's gonna be a transaction that occurs, and then they're gonna give them back the information.

That's the bet that we are placing with Qualitate, right? That we can build a product using AI that is just as sophisticated as a service. And so in the, in the research domain, I would say yes. I think if you're working at a services business today, what that industry looks like in the next probably 12, 24, 36 months is gonna be a lot different than what it is today.

We've already seen the standalones heavily, heavily impacted, right? I won't mention who those are, but everyone knows who the standalone market researchers houses are. They've gotten really impacted and, and now it's going further and further along that journey all the way to, to where we are today. And so I do believe, um, from a services standpoint, right, there are some industries like research, right?

I can't say that for every services industry, but some service industries, right, where it has historically required a lot of human intervention, uh, that there is a clear path, uh, at least in my view from where I sit, uh, and from what I'm doing day to day, that a product can be built using AI that can take on even the most complex requirements, uh, and produce good if not better, um, uh, uh, uh, information on, on the other side.

And so I mean, that's the business that Qualitate's in, right? That's, you know, folks that have ultimately provided us funding are essentially making that bet, right? That that is in fact going to, going to happen. And so that's how I think like the future will kind of shape here, um, over the next, you know, couple, couple, couple, couple of years here.

Amir: And you, you'd mentioned that, um, leveraging AI to actually get to that, you know, get, get to that expertise and getting the experts to provide the information you guys are looking for. You, you mentioned that AI is actually facilitating that. I think it'd be really interesting to kind of talk about how AI is actually- Yeah

helping that pa- part of it.

Sagar: Yeah. I think, you know, part of, um, part of getting like information from individuals, um, it's a complicated... It was a complicated process, right? Like, it was, it was hard to justify, right? You have to call someone, you've gotta email someone, you gotta set up like a bunch of phone calls, or you gotta set up some type of engagement.

Uh, there was all these steps. You gotta schedule all the calls, and someone has to take all the calls, and there are all these assets that need to be generated, right? Then someone has to make a decision. So there was all this complexity that needed to, um Uh, there's all this-- It was, it was hard to, to justify the complexity behind it.

Like if-- How many people have actually done an expert call in their lives? Probably not many. Uh, and because it's very expensive, uh, or worked with like a major consulting firm, it's expensive, it's, it's, it's, it's costly, uh, not just your time, but your resources. And so the idea behind using AI in all of this was ultimately how do we remove all of these, these barriers, right?

How do we make it so cheap and so fast and so accessible and affordable, um, uh, uh, and reliable, right? That someone will essentially say, "This is the much better version, right, of, of this, and now I can get all of it." And so the way that the AI ultimately works is rather than a human doing all of the calls, right, the AI moderator in this case is the one that's doing all of the calls, right? It's, it's very straightforward, right? We reach out to folks in a traditional manner, right? Maybe it could be over email, it could be over LinkedIn, right? Other mediums. Um, but rather than saying, "Hey, would you like to get on a call tomorrow?" and, and gives us information, they're gonna talk right to the AI moderator just like I am right now with you, just going back and forth.

And that AI moderator is gonna have a full conversation, right? There's, there's no latency, there's no nothing, right? It's a full back and forth conversation. It could be thirty-five, forty-five, fifty-five minutes. It could be on, uh, AI security, could be on, you know, uh, design software, could be on, uh, you know, uh, healthcare payers, providers, right?

Whatever it may be, right? This moderator's gonna have that full conversation, again, just like we are today. And part of it was building the technology, right? And having the moderator being able to, quote unquote, like hold its own, right? Um, and what does that mean? Like, you know, you have to... When you release a product like this, like people need to be confident that what that technology or AI is gonna do is gonna be just as good as them or better.

No one will adopt something that is worse, right? And people even will be hesitant to adopt something even if it's at parity. It has to be better than they are, right? That's the only way to get mass adoption. And so we have spent years now, right, uh, uh, um, grounding the moderator on like, "Hey, here's how, here's how to ask questions and probe Right?

The-- all these small little things, right? Which is like when you and I are going back and forth and asking why, we know when to go down the rabbit hole, and we know when to, uh, just kinda maybe gently ask why, right? 'Cause maybe we got enough information up front. Uh, a-and then it was all about, well, how do we, how, how do we, how do we make the moderator, uh, custom to that individual, right?

Every individual has a certain, like, interviewing style. Every, every company, every firm, right? Some people are think more in, in, in, in, in the short term. Some people think longer, the longer term. All of these types of things, right? And so we had to bake all of this into this kind of, uh, this moderator, which is, you know, how do we get it to think and feel like we do, right?

And so everyone has their, their own approach, so to speak. And then, of course, how do we make this thing really, really smart? Right? And how is it constantly learning? And so these are all the things that we, we had to ultimately, uh, figure out and, and that we did figure out and that we built. Um, and so now our clients have this incredible confidence that when they go out and they send this technology out, it is meeting their barriers of what we would consider human parity or above human parity.

And, and I think that is, uh, what I have dedicated my life to the last three or four years, is building out all of this technology and AI to... You have to-- People have to have confidence and trust when they hit launch on a application that's gonna go out and do it. Uh, and, and they gotta have confidence and trust in the AI, right?

That it's gonna essentially be able to generate the same level of results as they would. And so that I think ultimately is, is, is kinda how we built this, which was around this concept of confidence and trust. And if people have those, then they will use these AI tools to go out and, and do something that was very manual, very costly, um, and the s- the, the, the stakes of the decision are very high, uh, very high, right?

Uh, the folks that we work with are making multi-million, multi-billion dollar investment decisions. They're making multi-billion dollar product decisions. You can't be wrong, right? Uh, or there's a very small margin for being wrong, hence why this industry, uh, exists as it is today with, with so many phone calls.

And so I think we've gotten to a point now with the technology that we've built where we're giving people the confidence to make those decisions using the latest AI.

Amir: That's very interesting. I, I, you know, I guess one thing that popped into my mind, I actually had a conversation with somebody who said, um, and I think this is very true, that people like talking to their AI.

It's becoming-

Sagar: Yeah ...

Amir: I don't know if I had the word companion, but the, uh, it's becoming a form of dialogue with some, I don't know, something that actually will converse back to you. That's, uh, I, I guess how I'll just leave it for, for now. Um, when you're looking at these, um, you know, these, these, these interviews that you have these AIs doing, um, is that helping? I mean, is, is that helping in terms of just lowering the friction, making it faster, all those different things that you-

Sagar: Yeah. Yeah, I think that the beauty of... Uh, so to hit on your first point, I, I, I see it all the time when the AI moderator is talking to folks where folks, like, you know, like, "Whoa," right?

That's like sometimes the first response, which is this, this is reasoning, uh, at the same level that I'm reasoning, or like this is very in-depth follow-ups, right, that you would not expect, um, from a sy- from a system. And so I think people, uh, part of why people love talking to these things is because, uh, where we are right now in kind of the, uh, AI adoption life cycle, which is like this is incredible, right?

That, uh, I can effectively have a conversation, um, uh, with, uh, uh, uh, you know, uh, with, with a moderator that is not a human. And so there's always fascination. That I still see fascination. I still see so many follow-ups, right, when folks are going back and forth, where you'll just be like, "Wow, that's an incredible follow-up."

Uh, uh, and so you see that in the conversations, I think, because people the other side are like, "Wow, that's, that... Even I would have n- would not have been able to process that informa- much information." And then obviously the memory capacity, right, that AI has, where it can go back and pull stuff and, and ask the best follow-up questions.

And so I absolutely think that's why people love talking to it. We see the same things. Um- In, in our work. And, and your second question, I apologize. Uh, what, what, what was the second question that you had on that?

Amir: Yeah. I, I, I, uh, I guess the question was going down the path of, you know, obviously with lowering friction, uh, people can, people can do this anytime they want.

Uh, I mean, I think, and I think anytime you lower friction, uh, throughout a- any process, more people will participate.

Sagar: Yeah. That's right. And so, uh, that is the... I think that's the hypothesis behind Qualitate, right? Which is if you lower the friction and cost enough, people will reach for primary evidence for every single decision, right? And so, uh, that's absolutely right. Whether the AI moderator is always ready, right? It's, it's, it's fluent in lots of languages. There's no geographic barriers, right? It can take calls at midnight, at 2:00 AM, at 5:00 AM, right? Mornings, nights, Fridays at 5:00, right? All the times when people actually can't.

Um, it's no different than, uh, uh... and this is like a, maybe a simplistic analogy, but like, you know, you remember, I used to do it too. I mean, I was a consultant when I started my career. I had to call a taxi dispatcher and, you know, the night before I wanted to go to the airport, and it was really expensive, and it cost a lot of money, and there was a lot of like humans that I had to go through and, uh, all that stuff.

And, and, and then obviously, you know, all the ride sharing applications came out, and it kind of created an exchange around that business. And, you know, all of a sudden the volume probably went up, you know, dramatically, right? Because of how the s- how simple it was and, and you removed all the barriers to entry and, and it was much cheaper at the time, right?

It's the same concept here, uh, which is once you remove all the friction and you remove the, the high price tags and you remove the complexity, um, people will reach... I mean, that's what we get back from our customers all the time. This is so much faster, better, and higher quality. I'm not going back to the way I was doing it, right?

No one in, in their right mind today would ever call a, a travel agent or a, uh, a taxi dispatcher unless it was for a very unique circumstance, right? There will always be, there will always be a market, right, for, for high-end or, or, or one- off engagements. But in this case, it's all about people make lots of decisions every day, and if you could use primary evidence in every decision, you would.

But as I mentioned earlier, it's too complex to just by getting on a phone call or, or doing that whole process, right, and engaging with folks. But now it's not, right? That is what Qualitate is doing, right? We are dramatically reducing the complexity, the cost, the barriers, making it highly accessible. So with the idea that everybody on every decision can effectively use Qualitate, right, to gather primary evidence, right?

Everyone would talk to five people if they could before they make a, make a decision, especially, right, if you're at a, a major corporation, a major, uh, investment firm. That's what we're trying to do, right? That's what we have been doing here for the last couple of years, and that's what we're gonna try to hyper-accelerate now.

Amir: Yeah. You said something really interesting about, um- You wouldn't turn to a travel agent, for instance, unless it's a really difficult, uh, situation. And, and it kind of actually made me think about what AI has done, these, these, these, uh, various AIs people interact with is it's so hard to go into, um, a field and start typing out, uh, whatever it is you want, just because, uh, A, we speak faster than we can potentially type out.

In those hard situations, those, those, those difficult situations that you do need to, you know, or have traditionally needed to call a travel agent, it's interesting 'cause we're probably gonna see some of those edge cases get eaten up by AI even because it'll be just be easier to explain to some AI that this is my problem, and I'll let the AI go break it into pieces.

And I think as you kind of were talking about that, I'm like, you know, the human in the loop, and you mentioned that early on, we're, we're very worried about where we sit. And I think most technology challenges, I, I feel, is you have a subject matter expert, um, they are understanding of their problem.

Translating that into a f- uh, uh, I guess a f- a, a way that somebody else or something else could digest it and produce a solution has been a big challenge, I mean, for technology bridge. I think as you're talking about these AI models, this is the first time we're seeing we can use, you know, uh, human language to describe problems that have required teams to be able to articulate previously.

Yeah.

Sagar: That's right. Yeah, I think, um, uh, you know, it's, it's creating kind of like this bifurcation, right? Which is like, hey, and this is kind of what we were maybe chatting just a few minutes ago, which is like, w- what's gonna get r- what jobs, uh, are, are, are, or, or what is the world going to look like in, in 12 and, and 24 months from now, right?

What, what areas can AI ultimately, um Have a massive impact in, and what areas is AI not gonna have a massive impact in until we are much further along where you have things like, like, like physical, uh, AI, robotics, all that type of stuff, right? And so I think you, you see a lot of times, uh, right, on, in the news where you'll have like a, like a CEO of a big AI company saying, you know, plumbers and electricians, right, because of data centers or whatever it may be, right, they're gonna be making six figures or whatever.

I think some of that's probably true, right? Which is like, you know, there, there's some areas that like AI is not gonna go in and disintermediate, right? It's gonna have to require like physical AI, robots, all that type of stuff, right, uh, before there's, there's really any movement, uh, on, on, on many jobs. I think likely, um, uh, any type of like services, like white collar services, like that feels like the natural place of where it's happening today.

Um, but I'm not like a huge believer in like, hey, uh, uh, AI is just gonna like drastically reduce like jobs across the board. In some areas it will. Like if you play like an orchestration role in an organization, I think there's gonna be challenges there. Um, right? So project managers, product managers, all those types of things, like people who are coordinating, they're just, the tools are too good now.

You need very few folks, right, to go from like vision to like actual, you know, engineering. Um, so those will have... There'll be a lot of impact there. I think, um, I'm not like on the boat of like engineering is gonna be disappearing. I'm trying to hire more engineers than ever, and so I, I, I don't... I, I'm not seeing it in my role.

Uh, uh, right? I think if you can build faster, you're not going... Like great, if, if engineers are 10 times more productive now because of AI coding tools, then I'm just gonna hire more engineers and they're gonna be more productive. There's gonna be more output. This is a capitalist society, like people are gonna wanna keep generating more and more money.

There's, there's no chance, uh, that people are going to, uh, say, "Hey, let's, let's, let's work less. Let's do less." I, I, I don't see that. Um, maybe, maybe other folks do. And so I, I just think like it depends on like where it is in the organization, right? Is it a service? Is it like a, like a physical... Is it like a, is it a service that someone can provide on a computer?

Is it a service that someone provides physically? Right? AI is gonna have all these different impacts on, on folks, but like it's very clear, like at least from my seat, what I see is like that orchestration, like if you play like, like an orchestrator role in an organization, right? There are less folks even today within, within qualitate, right? There's, there's not a lot of folks, right? We, we, we go from high-level vision, you know, things get recorded very quickly. They get transcribed, they get fed into all of our, our, our tools. Uh, it gets moved into wireframing tools. It, PRDs get created. It moves right into engineering. Things that used to take weeks uh, and, and months and lots of people, uh, uh, it's, it's no longer there.

Right now it's just about, hey, how many engineers can we have, right? How fast can we build things? How fast can we sell things? We're trying to hire more AEs than ever, right? So on, on, on those sides, like I'm-- we're trying to hire as fast as we can and, and, and I, I see the same thing with all the labs, right?

I'm not seeing engineering posts go down. They're hiring more engineers than ever, right? They're hiring more salespeople than ever, right? Because you gotta build and you gotta sell. Um, but a lot of folks in the middle, yeah, I think will probably be impacted. And I think outside of, you know, when you get out of, outside of maybe like just traditional services where folks sit in computers, I think that- that's probably gonna be further along.

I, I, I don't see that right now, so.

Amir: I, I love that. I, I think, um- I think I've, I think I've mentioned this before on this show, and I, and I, I f- I f- I firmly believe what you believe. Uh, I feel like every technology... I think AI is big, and I think it's going to have massive impact 'cause it is... it can touch almost everything.

I could argue electricity was probably as monumental a shift. It touched everything and everybody that could possibly exist on Earth. Uh, combustion engine. I mean, we could go down the line. There, there, there have been things that have, um, only accelerated productivity. The personal computer. I mean, we... AI is huge.

But I also think sometimes we forget that throughout human civilization, technology has actually only accelerated what we're capable of. I don't know if we've... I don't know. I don't know every invention out there, but I, I sometimes think about what invention has come to market that has actually limited humans and their potential.

Like, that said, "You know what? It caps what we can do." And we're all just going doomsday. This is the one. We're all like, uh, have seen I, Robot way too many times and go, "Well, here it is. It's finally here. The robots are gonna take over, or the AI's gonna take over." And to your point, you're, you're, you're seeing an AI come in, uh, actually accelerating output and productivity from the people you're talking to and actually collecting more information, which will allow you to expand your capabilities.

I mean, sounds like a dream.

Sagar: Yeah. I, I, I'm not a big... I'm, like, the opposite on fear-mongering. I... That, that's a marketing strategy that a lot of folks use, which is, like, you know, you'll see a lot of it, like, we're moving to the four-day work week or, like, you know, we're gonna be able to, uh, cut, you know, half our organization.

And I think when those things happen and folks, like, it's because of AI, I, I don't think so. I think probably there was a lot of over-hiring during COVID. Um, and now people are, you know, starting to pull back on that. And so, uh, that's probably more, like, the reality of, of probably, like, you know, how to ground, like, real, real world, uh, uh, you know, layouts.

Um, yeah, I, I think AI's, like... I almost think about it, like, as, as, as this, right? Like, if you're from, like, a customer standpoint, like, are you adopting these tools? 'Cause if you're not, you know, what will happen over time is, like, you won't be able to compete with fo- Like, you, you, you... If you don't do it, you're not going to compete in the market, like, period, right?

If you don't adopt AI tool. That's why the adoption of AI has been so swift because you know it, right? If, if you are in any other world, like, there's one organization that's using, you know, tools like Qualitate and, and all the other AI tools and, and, and they're using the LLMs, and then there's another firm that's not doing any of that Yeah, maybe right now at this moment, there's like, okay, I can see s- right, wait till 12 and 24 months, because what happens is it's all compounding.

When you start using AI tools, you start hiring different types of people. The infrastructure that you start laying down is totally dramatic because you have to be able to absorb all the information, right? Like if Qualitate is doing thousands of calls for you, right, versus the 10 or 15, well, you have to have the infrastructure, right, to ingest that and make decisions off of that.

So every day that if there's two comparable firms, right, and one's not doing anything and the other one is, is doing a lot of it, right, it, it, it, it doesn't just go like this all of a sudden, right? It takes time to compound, right? But after a year or two, now you-- all your, all your folks are trained on these tools. You have the organizational, uh, uh, mindset, right? So the, the inertia to adopt is, is not there. Uh, all the folks are highly talented in these tools. You build all the systems to ingest this information, make better decisions, right, as it pertains to research. Um, that other firm cannot compete anymore. You are moving at, at, at, at 1,000 miles an hour, and this firm is stuck, right, in, in its own legacy ways.

And so this is actually what I think will happen over the next few years, is you're gonna see some organizations, whether big, mid-size or small, adopt these tools, and you're gonna see other folks that are more resistant to it. I think probably you'll, you'll see just a massive bifurcation in, in the outperformance of the businesses that do.

Like, that's how I almost... That-- I think that's how I kinda think about it, and that's why I'm not in like the doom and gloom scenario, which is I actually think, like there's gonna be a whole bucket of people in that, in, right, which is there's lots of businesses providing lots of AI, you know, products and services, and there's gonna be a whole set of people that wanna use them, and it's, it's gonna increase the productivity, uh, for everyone across the board.

Um, and then there's gonna be firms that, that do not adopt it or are slower adopters and, and we'll have to see whether they make it out.

Amir: I love that. That's, that's a, a great view. Um, uh, and, and, and I was gonna say, I appreciate you coming on the show and sharing these views 'cause I think it's a, it's an interesting time.

You guys are doing something interesting with how, uh, you're leveraging AI to actually help us, uh, improve our understanding and knowledge base, so I think it's fantastic. If someone does wanna ask a follow-up question, if they wanna learn more, what are some good ways of getting in touch?

Sagar: I mean, they could, they could, they could, they could email me, they can, uh, uh, my, uh...

They could email some of our, uh, uh, folks that work here. And so, uh, what I can do is, yeah, happy to, to drop all those, those email addresses. I think that's a easy way. Uh, I'm, I'm, I'm always, I'm always working. Uh, and so that's, that's a good way to do it. Uh, so myself, and then we have a few other folks here that, that typically handle inbound. And so, uh, I can drop you all those, all those email addresses and, and, and you're welcome to share those.

Amir: Absolutely. Sagar, I appreciate the time. Thank you for coming on.

Sagar: Yeah. Absolutely. Thank you so much, Ray. I really enjoyed this conversation. Thank you so much for having me on.

Amir: Absolutely. Thank you. All right.

That's it for this episode. Be back again, different guest, different topic. Until then, two things. One, love it if you guys could share this episode with somebody else who would find it interesting, and I'm pretty sure a lot of people right now are still interested in understanding how AI's impacting us.

And Sagar talked to us about how AI's actually helping facilitate gathering expertise and where that expertise lies within the human in the loop. We talked about, uh, some of the, uh, forecasts of what, uh, AI looks like. And obviously, we won't hold him to that, but I, I agree with his viewpoints and I'm very, uh, bullish on this.

And they're doing some exciting stuff, so please share this episode with someone else. Also, like, subscribe, comment, leave me a review on Apple Podcasts. I'd appreciate that. Until next time, thank you and goodbye.