00:00:00 · Mikk, David Flickinger
[00:00:00] S0: There are a lot of AI consultants and AI experts popping up these days. But before I recorded an episode about how AI can actually improve a traditional 1 to 10,000,000 of EBITDA business, I wanted to find someone who had truly been in the trenches, someone who has actually operated businesses, understands the realities of running companies and has been working with AI long before ChatGPT and other tools became fashionable. And I think I found exactly that person. Today, I'm joined by David Flickinger. David is the CEO of Vellm, managed AI infrastructure for businesses. He's also an operator who's run companies himself, held executive roles across variety of industries and has been deploying AI in the real world since 2017, long before it was popular. David, thank you for coming to the Buyers and Builders podcast today. [00:00:54] S1: Thanks for having me. Great to be here. [00:00:56] S0: Now I want a listener, whether they're a business owner, a CEO, a private equity professional, search fund operator or simply a serial acquirer. And once we finish this episode, I want them immediately forward this episode to their it's their CEO of their portfolio companies or their group CEO or simply their operating partner. So I want to make this episode so valuable for them. Let's get into this in a second. But first I want to talk about you talk about your background a bit because I think it's very unique and very special.
00:01:28 · David Flickinger
[00:01:28] S1: Well, that'd be great. And I do think my background is relevant here for the discussion in a couple instances. So right after I finished my undergrad, I commissioned as an officer in the Marine Corps here in The United States and, in particular, had the opportunity to be an infantry officer. It's a pretty funny thing to be immediately thrust from college life to being in charge of 50 infantry marines about to go on a combat deployment. But you quickly realize that as an officer, your your two best weapons are a notebook and a radio because you really become an orchestrator. You're always talking to your squad leaders. You're communicating back to your higher headquarters. You may be orchestrating fire support coverage from artillery or air support or snipers, and it's really you as the orchestrator, which I think is a relevant parallel to the AI orchestration we'll talk about in a little bit. But after about five years of active duty service, I transitioned into the private sector and had an opportunity to work for a Fortune 50 company called Medtronic, which is the largest medical device company in the world and got to do some really interesting things from corporate development. I had the opportunity to work on some m and a deals as well as pursue some business development initiatives there. They encouraged me to get my MBA, which I did, and I was very grateful for the opportunity to learn an industry I really didn't have knowledge of prior to my time in the Marine Corps. So I've spent quite a bit of time post military service in the medical device and health care sectors. I bounced around a few different companies. And one in particular you referenced in 2017, there was a really interesting technology called Metacrea. And the... That was the name of the business, but the technology was using AI machine learning algorithms to produce patient specific implants for spinal surgery, which if you think about is a pretty crazy concept to have an AI determine which type of implant a surgeon should put in a patient's spine. But it turns out that there's actually a very data driven algorithm where you take an X-ray scan of a patient that might have a spinal deformity, an adult or an adolescent that has scoliosis, and you determine according to the medical literature what is the appropriate curvature to return this spine to.
00:04:13 · David Flickinger
And then the AI algorithm can determine what that is and actually produce an implant specifically for that patient. That was the concept of this business, and it was tested over years of iteration against surgeons who were just using their own creativity. And surgery is a little bit of artistry. It still is, especially in spinal deformity surgery where the surgeon looks at a spine curvature and says, think it ought to be here. But it actually turns out that the data informs a better surgical outcome. In other words, if you have an AI produce a patient specific implant according to its parameters, the patients had better short term and long term outcomes as measured in follow-up studies over several years. So it was really fun project in business to be a part of. It was acquired in 2020 by... Incidentally by Medtronic, and it was cool to be a part of that exit. And since then, I've diversified the industries in which I'm focused. I've done some trade businesses. I've done other peripheral health care or med device startups and, invested a little bit myself. But I've continued to use AI based on that experience. And we really called it machine learning. The word AI has now become commonplace, especially with the launch of ChatGPT a few years ago. But I've continued to implement AI into portfolio companies as a consultant and into my own businesses to drive growth and extract efficiencies out of things that I've been doing. And then we transformed that into a business that's focused exclusively on providing managed AI services, helping businesses deploy AI in their own organizations. And I guess the last thing I'll say is we wanted to do that in a way that was sort of an operator first mentality. My own background having lived that experience both as an executive and as an owner operator, we wanted to do something that would not only improve efficiency, help a business grow, but ultimately foundationally make it more valuable. And so that's the approach we've taken with Vellm and what I'm doing today. So a long and winding road to what we're doing now, but each step along the way has informed the way that we think about this conversation, which is deploying AI into an operating business.
00:06:48 · Mikk
[00:06:48] S0: I knew that we have this episode coming up, so I did a bit of research and I called around... I had like 15 calls with traditional business owners here in Northern Europe, and 11 of them are actually using AI. But the way they're using it is a is a typical ChatGPT, like just putting all sorts of documents there and just asking to to summarize few things or just the numbers or or things like that. So I wanna go smoothly and ask from you here, like, can you maybe walk us through the difference between asking ChatGPT a question versus having an AI system that actually lives inside the business?
00:07:31 · David Flickinger
[00:07:31] S1: Yeah. It's a it's a great question. And I think at this point, we've all used ChatGPT or Claude or Gemini or some chatbot now. And I think what you find when you use those things is they, first and foremost, typically give a very confident answer. And so one can maybe maybe be persuaded by the confidence of the answer, but these answers, when you use them in the format most people do, they typically lack context. And so what you find yourself doing is adding a bunch of paragraphs. Maybe you're typing it in. Maybe you're even uploading a couple files so that the chatbot has some context about you, your business, your background. Hey. Answer this as if I'm a sophisticated finance professional. Answer this as if I'm a expert in x y z industry. And so you start to get some better context. But I think, ultimately, the difference is having context about your business from a prompt is very different from having context about your business as an infrastructure. In other words, the AI is connected into your CRM, into your ERP, into your databases, into your proposals folders, into your financial documents, and it has all the context about your business. It knows what your employees are doing. So it not only has context about what you're doing, but what your peers, your boss, your subordinates are doing in the business. All that is in this foundational memory layer of your business. And so when you ask a question of the AI then, you get a much different answer, one that's very relevant to your business and one that I think gives you the confidence then to take that answer and go apply it and use your own human judgment where I think a lot of folks who are using these chatbots at best are maybe maybe wasting a little time. Because if they are really the expert, they could often arrive at an answer faster than prompting with an insane amount of individual context every time. But at worst, they're getting an answer that may be different from the right one because it's devoid of context about their particular business and situation, but it's delivered in such a confident way that they might make a bad decision. And that that would be the worst case scenario.
00:10:06 · David Flickinger, Mikk
Ultimately, I think you're seeing a lot of people use AI and in many instances being a little discouraged or confused about how do I do this in an enterprise setting versus just me individually trying to supplement my own skills or work streams with AI. [00:10:24] S0: For me, a true eye opener was the example you gave me when we were doing those pre calls, and I've learned a lot already from you when it comes to AI. But one particular example, and it was the roofing estimator. And you told me the story where... I'll let you tell the story yourself, but this was really, like, where I I've read and studied quite a lot about AI, but this particular example you gave and shared was like, okay. For those who know how to do it, it's it's pretty dangerous in a good way. So please, could you please share the story?