2113 – The Future of Business Research: Embracing Technology for Better Decision-Making with Graph IQ’s Malcolm De Leo

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1:05With us right now, it's Malcolm DeLeo. Malcolm, you are the co-founder of Graph IQ. You're on the web at graphiq.ai. Malcolm, thank you for joining us. It's a pleasure to be here, Josh. Always a pleasure to talk to you. Yeah, well, listen, tell me about the work that you have been doing. You guys have been doing at Graph IQ because you're getting some traction. Yes. Yeah. So we started Graph IQ about 18 months ago. Actually, we just changed our name. It was GeoFlow. And we decided to change it because it better reflects what we do. We started the company 18 months ago, actually trying to head into the supply chain space and trying to map using geospatial data and all sorts of crazy stuff.

1:50And what we realized is when we interviewed over 40 executives, we got the same response about what their problem was over and over and over again, which is there's really no good way to find companies to do business with. It's a problem everyone asks. If you stop and ask somebody, hey, when you're doing business research, how do you do it? They either use Google, they call who they know, or they use a consultant. And we took that insight and built our software. And essentially what we build is a search engine for business research. Yeah. It simply put. Okay. So let's talk about the current lay of the land, Malcolm, why this is so critical today.

2:25and I'd love to kind of dip our toe a little bit into the waters of what are organizations currently doing. So leaders who are listening right now, getting them to think about what they are, what is their team doing? And how can we improve systems? Are we operating on antiquated technology? Are we relying on solutions that are just way too broad and unspecific? And so as a result, we're making suboptimal decisions. We're wasting time. In today's AI-enabled age, with some thought, with some direction, that just doesn't have to be today. Sure. So it's interesting because you ask what people are doing today.

3:19and I've been helping sell software for until I started my company for, I don't know, 15 years. And one of the things that's always amazed me is that it's hard to figure out what ROI you're giving people. And so there's lots of different products that you can use in addition to what we do. I mean, there's products that are in the space of helping you drive new sales leads, which is a huge part of what we do. There are companies that are out there helping to map, like I said, direct pieces of supply chain or using AI to understand inside the organization how to use their data better. And frankly, I'm running into a lot of large organizations that kind of say, we bought ChatGPT and we're going to use that.

4:02Yeah. Yeah. What we're finding is, you know, our system from an ROI perspective, I've never had the opportunity to sell something that the ROI is pretty easy to explain. I kind of look at people and I say, listen, if your people or you are doing research on google every day then you're wasting your time and 100 yeah based on our pricing which is pretty pretty low i really have to save people about five hours a month for it yes but but you go all the way out people are spending hundreds of thousands of dollars with gigantic uh consulting firms to solve problems that take months and months And some of those we're working on, we could shrink down to a manager doing it in a week, right?

4:47100%. 100%. Malcolm, let's talk a little bit about knowledge and, you know, factual knowledge and accurate knowledge and accuracy and why that is so critical today. And you brought up a really important point. I just want to explain or, you know, kind of just illustrate this and I'll have you kind of take the board on with it. Google is inherently not like it wants to give you relevant information. It does not care about accurate information. Now, oftentimes, hopefully that's in alignment. But we know that just like on social media, it's social media like YouTube is designed for it's those are all designed to keep you on the platform.

5:34And so what you have is, you know, you have a tenured, you know, PhD, someone, you know, is at the top of their field for the past four decades, right? And they are sharing evidence-based, you know, research that is peer-reviewed. And you have that. That's one instance, right? So that's one YouTube video, or that's one bit of information. That's one blog post. Then you have Joe Schmuckatelli in his basement with the aluminum foil on his head, you know, raving about some lunatic conspiracy theory. in YouTube's eyes. And unfortunately too often in Google's eyes, those voices are equal. And that is, that is absolutely, that's a danger spot for your company.

6:26And guess what? It's already happening. Go for it. Yeah. So it's interesting. I think my answer will be somewhere between what you're saying. One of the things is the way we do this, we actually scrape all the sentences all over the web, 1.2 billion websites a day. And we use natural language processing, which is an older form. And with that NLP, we understand the grammar. And what we do is grab bits and facts that we find across articles all over the web, news articles, Dun & Bradstreet, Yahoo, company websites, it doesn't matter. And we store all that and allow you to search on all these different aspects.

7:03Most importantly, search by capability. We don't QA anything actually, because it's all open source data. You could find it on Google. And we made that decision. However, we have attribution on every fact that you're looking at. So when you look in our system at a dossier of information about a company, address, employees, any news about it, the people that work there, the capabilities they have, subsidiaries and the dossiers of those subsidiaries, partners, customers, suppliers, each one of those facts has attribution. And so, you know, we're continuing to work to express it. So it's just easy to find.

7:40You'd be surprised people don't actually ask as much as you'd hope, but we do that. And by saying up front, it's open source, you could find it on Google, we don't QA anything, we're solving part of that problem, because then we leave the data that they're looking at up to them, versus, you know, Gen AI could be hallucinating and giving you BS, right? We try to be kind of we kind of put a lens on a boiling ocean. And the goal is to bring that information to people faster, better, quicker, with more control. So they're more confident in what they're reading. So in your case, you're right. You know, as a scientist, yes.

8:16You know, peer reviewed articles are where the answers are. Even that sometimes has been compromised over the years because people are creating journals and marketing their science online, which is bad. So the best way to do it is to try to give attribution. But unfortunately, until somebody really figures it out, we're going to be relying on people's wherewithal to find the best, highest quality information and use their critical thinking skills as opposed to let the computer do the work for them. Yep, yep. Yeah, we're really entering into, I'd say, a phase really quickly. And I'd say in some cases abruptly.

8:52and um so it's almost like you know imagine you know living in the 1800s and all of a sudden you have like uh someone just gave you a car from like the 1960s or something like that and they're like here you go kid and you're like you know i i feel like you know if you've never seen a car like that before well you're probably going to make a lot of mistakes with it because no one's ever taught you how to drive this. Like no one has really, none of us went to school for how to engage with information in the way that we're able to engage now with AI. Yeah. And it's interesting because the reason the explosion happened, if you take a step back, I think about this a lot, we've been interacting with AI for years, right?

9:36When you email on Google, it tells you what to write. However, again, being a consumer packaged goods person, one of the things that was really interesting. My boss taught me about consumer perceivable benefit. And so when Gen AI came out and your work could interact directly with the AI and it would spit back to you, that's the first time we've had direct interaction on our work with AI. And it was like, you're right. It's like being given a car from the future and, and, you know, being from another time, it, it, it, it blew up because the consumer perceivable benefit to your own work was so great that it's directly in your face now.

10:14So now everyone's running around thinking, wow, this works for me. Now it should work for everything. I mean, I've had fairly experienced VC people say, isn't it just going to replace everything? Well, you know, everyone's finding out pretty quickly right now that the AI bubble, I wouldn't say it's bursting, but you can only develop your model so well. In fact, I would actually want to make this point. The model is only as good as the data you pointed at. And so actually one of the things that we've done, which we talk about somewhat, but I think it's going to become a bigger deal is because we have this huge company multi-relational database, we have over 267 million companies, 900 million people.

10:54And like, you know, we process like 4 million news articles every day. The scale of that, but also the control to use the engine to find, for example, find all the chicken farms in Nebraska. And I can do that in five seconds. you now have created and curated a data set that you can then point the AI to. So for example, in our world, I like to say we use AI as the chocolate chips in the cookie. You might want butterscotch chips. You want my dark chocolate chips. You might want to have vanilla chips. You might want a different brand because as the AI models evolve and commoditize, we're going to be able to push and pull them in so that we can use them in small spaces as part of a cookie.

11:34And it's really made a difference because we have control of the data. Yeah. You know, some of this stuff is, you know, again, it's clunky. But what I will say is, you know, and I'm going to really date myself here. Go. People who had the ability to work WordPress in the, or not WordPress, Wordperf, was it, what am I, what am I thinking of? There was Word and WordPerfect. WordPerfect. Yeah, WordPerfect. WordPerfect, right. It was WordPerfect. And if you knew all the commands and the function keys and stuff like that, like you could rock it. And when they started upgrading the UI, it's like if you became so, it's the foundational, like, so like working with AI to me is less about the interaction.

12:23Well, it's about the strategy with it. It's about understanding how AI operates, right? So if you are just sitting around as a leader with your company and you're sitting on your hands, I'm going to argue that that's probably something you might want to reevaluate because you need to be experimenting. You need to get your hands dirty in this because, Malcolm, technologies and platforms like yours are coming along and they are improving the user experience. Do you mind maybe just maybe touching on what I was talking about right now about maybe being a little bullish on AI? And then certainly let's kind of get into graphic AI.

13:05Yeah, yeah. Graph IQ, excuse me. That's okay. Either way is fine. We're still figuring that out sometimes, right? So, I mean, yeah, to be bullish, I mean, I would say this just from all my years working in innovation. if you're not investing and trying and experimenting with new systems and new tools that come to you, you're crazy. And I've been an executive at large companies and I've been, you know, a partner manager at large companies before I worked in, you know, startups. And any CEO, you're right, who's sitting on their hands or using a monolithic approach and isn't investing, you don't have to invest millions of dollars.

13:40You can invest 10 ,000 there, 30 ,000 here to try and work and partner with small companies that are bringing the best technology to you, you're nuts because sometimes you got to figure out what you're not going to do from the technology you partner with. And it's important to even try. Just thinking that you can do things the way you have is impossible, right? And what we found is we're up to almost 40 clients in less than 18 months, right? And one of the things I would tell you, this is user feedback, right? I have two kinds of users. You think, oh, you have the analyst who's in the system doing due diligence all day.

14:17Yeah, we have those. I also have people and there's a real conversation. Hey, how's it going? Good. Are you using it? Well, yeah, sometimes. Do you like it? Oh yeah, I love it. Really? They're like, yeah, yeah. Why? And here's the point. Every day you have 10 activities you're supposed to be doing. At some point you draw a line at number five. There are activities you want to do for your job, but you don't have a good way or you don't have time. And so we've actually developed a system that people are taking jobs that they should be doing and we're giving them a way to do it 10 times faster so they're able to deliver for the customers because they can do the work for example we work with a economic development group in cleveland this person's job is to talk to startups and help them find investors and new leads and the way our system works she can do that in 15 minutes instead of five hours so now she does it and that's how you because she took the risk that's the experiment that you're getting.

15:11And that's the way you're improving your process and driving ROI, for example. I don't know if that answers you. You've worked with some pretty big brands, including Hershey's, Baylor University, Honest Company, and then of course, plenty of B2B. In a nutshell, if you were to give a two-minute summary, can you explain exactly what Graph IQ is and who it's for and like how it works within the company. Oh, within a couple of minutes. No, it's fine. I mean, it's like I said, we're a search engine to help you speed up business research in the order of 10 times. It's kind of a horizontal play because the ROI is based on helping you find information faster.

15:56Anyone can use it. And that's why we have a very wide array of companies that we're partnering with and working with. 2024 is a year of experimentation. 2025, we think that we're going to have a big impact in either sales prospecting, due diligence, or business research. And the way that the target's pretty random, but we're really starting to focus on sales teams, sales ops teams, consultants, private equity firms, where the analysts are in charge of, I need information quickly about an organization, organizations to keep up with it. We also work in supply chain. We also work with R &D people, but that's really the perfect target right now.

16:38And we're probably going to be working. One of the best companies, some of our best companies are the small to midsize manufacturers who we have a fairly low priced product. It's, you know, hundreds of dollars a month or about five or 6 ,000 per year per user. And they're able to get a lot out of it for a little bit of money. So that's another area we're focused on. That's what 2025 is going to be about. Really honing our market, really understanding the best use cases. But we're getting positive feedback across the board, actually, which is kind of unusual. Yeah. Okay. So what types of organizations, like, I just want to call out to our friend that's listening.

17:15Yep. Who should be reaching out, Malcolm, and what kinds of questions would you want to ask them to see if you, Graph IQ may be able to be a big help for them? Yes, exactly. So what I would say is anybody who's in B2B sales, who has a technology, it could be chemicals, it could be, you know, plastic parts, It could be a software company or service who you're really trying to figure out what new markets I can go after and you need to, or how can I find new customers to contact in any geography anywhere in the world? Those are the people we want to talk to. I want to talk to CROs. I want to talk to heads of sales ops.

17:57I want to talk to anybody who is a researcher. We also have a lot of business going on with chambers of commerce and economic development organizations because they have needs to. But that's really the target. And the kinds of questions we're asking, answering, like one of the unique things we do is because we have these capability fingerprints of a company. If you put a company in and click a button, it will take that fingerprint and find lookalikes to that company and allow you to filter down to really nail it. that's a great way to say, if I have found one company and I want to find a hundred more like it, we can help speed that process up 10 times.

18:31So all those place people I mentioned are all the kinds of people that are trying to figure that out, whether it's companies you want to buy, companies you want to sell to, even perhaps suppliers you want to bring into the fold to help you buy better. But it's really about how do I find better information, faster, deeper, and more companies that look like the ones I do. Hopefully that's direct enough. Yeah. Look, this world is moving quick. Malcolm, you're a good guy to have in your corner. I'll say that. Your website is graphiq.ai. When somebody goes there, what do they click on? What do they do?

19:08Yeah, there's at the bottom, you're going to see an info. You can do that. You can email me directly. My email is Malcolm at GraphIQ.ai. You can you can also there's also, I think, request a demo. We're just re putting our website up because we changed the name. But the best bet is go to the bottom and send an email to info at GraphIQ.ai. And one of the founders will get back to you very quickly. Yeah. Malcolm DeLeo, GraphIQ.ai. Malcolm, thank you so much for joining us. A pleasure to see you again, Josh. Take care.

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