Building an Autonomous Enterprise for Real-World Services with Netic Founder Melisa Tokmak

When your AC fails in a heatwave, you don’t want a busy signal; you need a solution. Netic founder and CEO Melisa Tokmak joins host Elad Gil to explain how Netic’s autonomous AI platform acts as an intermediary between companies and customers, deploying agents to instantly handle essential services, from emergency home repairs to hospitality to pet care. Melisa describes the complexity of these real-world workloads, which have traditionally relied on large human support teams, and how over 70% of Netic’s customers interact first with AI. She also talks about the reasoning behind building a scalable product company rather than an AI roll-up, why she believes robotics will not catch up in these industries in the near future, why she doesn’t view large frontier labs as competitive threats, and how private equity’s playbook has shifted toward measurable ROI in the AI-era. Plus, why Melisa is optimistic about the impact AI will have on education. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @netic_AI | @melisatokmak Chapters: 00:00 – Melisa Tokmak Introduction 00:32 – What Netic Builds 03:53 – Automating Workflows for Essential Services 06:26 – Building a Service vs. AI Roll-Up 10:38 – AI for the Real World Timeline 12:56 – Can Big Labs Compete? 15:35 – Modern Founder Mindset 19:09 – Screening for Agency 22:25 – Five Year Vision 23:53 – Selling to Slow Industries 27:23 – How Private Equity Approached AI 31:14 – What Excites Melisa About the Future of AI 34:27 – Conclusion

• 0:05Speaker 00

  Today on UpRires, we're joined by Melissa Talkmac. Melissa is the founder and CEO of Netic, a company that builds AI for different real-world services like HVAC, pet care, a variety of other things like that. Roofers, prior to Netic, Melissa was a director of engineering and worked on various aspects of go-to-market for scale.ai and also has experiences for Meta. Welcome to UpRires, Melissa. Melissa, thanks for joining us today on UpRires.

• 0:30Speaker 01

  Thank you for having me.

• 0:31Speaker 00

  Yeah, maybe we can start off by talking a little bit about your business and what you're building, because I think that you're doing something really interesting in the real world and you're kind of mirroring AI in the real world. So could you tell us more about your company and Netic and what you're focused on?

• 0:45Speaker 01

  Yeah, Netic builds AI to run millions of real-world businesses that keep the world running. That means basically we work with large enterprises in essential services. We started in essential services.

• 1:00Speaker 00

  What would be an example of essential service?

• 1:02Speaker 01

  Imagine a billion-dollar revenue home services companies in HVAC, plumbing, electric, or consumer wellness companies, like where you can become a member and really go do a lot of sports or different activities, hospitality, automotive, pet services across the board. So every single thing that you need to run your life or that you want to do are a good example. And a lot of these businesses are actually quite large businesses and they interact with millions of end users themselves, usually that are consumers or businesses themselves. So Netic exists between the company and its customers.

• 1:45Speaker 01

  So every single thing to understand the customer need or want and match that with how can we even help the customer with the operational rules of the business and even deploy the services or the labor, all happens on Netic.

• 2:02Speaker 00

  So basically, say a customer calls an HVAC provider, what happens or what is Netic doing for them?

• 2:09Speaker 01

  Yeah, so imagine that you are in the middle of nowhere, it's minus 20 degrees and your heat stops working. So you first find, right, a provider. And there are many providers, you want to pick the most trustworthy one and the one that you can get to because you're in a minus 20-degree weather. Maybe you have a kid or an elderly or something is not working. From there, once you find a business, and usually you can find these from aggregators or by search engines or in now LLMs, and you can reach out to the company from any medium you want. If they're using Netic, you can call them or text them or find, like go to their website to do an online scheduler. It's Netic agents that talk to the customer. What kind of home do you live in? Do we have any of your records?

• 2:51Speaker 00

  So this could be like a voice call and Netic is actually providing the voice.

• 2:54Speaker 01

  Completely.

• 2:54Speaker 00

  And then the reasoning around, hey, this person needs some help and we should deploy somebody out to fix their HVAC system.

• 3:00Speaker 01

  Exactly. And it's actually a lot of the businesses we work with, this is why we started with essential services, the operational needs are very complex. It's not as simple as, oh, Elon's heat broke and now Melissa goes. Is it that actually, what kind of even units do you have? What kind of needs do you have? Can we come to you? Is it something that we need to come to you today or tomorrow? What is your lifetime value as a customer? So should we be deploying the best person who can only work on, let's say, boilers or new age systems today or later? So it's actually quite complex to first and understand what is the need from the customer? Can this company service it? If so, who? When?

• 3:43Speaker 01

  And to ensure that it is all optimized to create customer delight to generate more revenue for the company, right?

• 3:51Speaker 00

  That makes sense. What is a sort of like an incumbent version of, you know, what you're doing or what are other players in the market or how should people think about, you know, what this replaces?

• 4:02Speaker 01

  So let's go about how do people do this today? Obviously, it's, we are a two-year-old company, so before us too, how were they doing that? So it's primarily with people. These companies are extremely large and if anything, actually, they can't grow because they have to keep investing in people to think of any kind of growth. And for them, they're EBITDA businesses. Many times they're actually owned by private equity. They need to care about their margins and what they make to be able to invest back into business. The most important labor in the business is actually the people who are going to deliver the job, right? You want to focus every single thing to make your end customer happy because a lot of these businesses are also commodities. If you do not answer me, I'm going to go to the next one, next search result on Google,

• 4:47Speaker 01

  next result on like now ChatGPT. So it's very important to be able to invest your money into your labor, the blue-collar labor. So until now, it was with hundreds and hundreds of people in these companies trying to figure out how to support customers at all times. The teams that support these workflows in the companies are unreliable as well. Let's look at a day in a life with this company that makes a billion-dollar revenue. You might show up, the business usually start at 4:00, 5:00 AM. You don't really have anybody in the company then, even maybe your technicians start at 6:00 AM. But before then, no one is in the company. You might come in as a manager, but there are at least three people that quit that

• 5:32Speaker 01

  way or that day, or five didn't show up. So all these customers are piling in, starting at 6:00 AM, because now it's a heat wave in the country. Actually, this past week, we have hit record waves last week in the country. What do you do as a business? So many of these businesses are cyclical businesses. It's very important in winter, summer, holiday season, season, people start working out, right? So you have to make sure that you're capturing a lot of your value in those months to be able to sustain yourself and your employees.

• 6:04Speaker 00

  Because you're providing like agents, they can overflow, so somebody's giving you a lot of phone calls, they can pick up the phone calls for you.

• 6:09Speaker 01

  Yeah. Over, that is many customers, how they started, but today, actually, over 70% of our customers are AI-first. We call it Netic-first. They go N1. And over 70%, actually, all of their customers' first interaction with the company is with Netic agents.

• 6:26Speaker 00

  So there's a few different approaches you can do for markets like this. And so obviously, I'm excited to be an investor in Netic. I've also invested in AI rollups where people will, you know, a company like Long Lake will go and buy a bunch of businesses and then optimize them with AI. And in some cases, these businesses overlap in their profile with your customer set. You mentioned many of them are owned by private equity already. How did you make the decision to build this service versus just doing a rollup or buying and running the assets or the trade-offs in terms of those approaches?

• 6:53Speaker 01

  I think three reasons. One, what I want to build in the world, skill set and scale. You know, before building this, I was at scale for about four years and I built a lot of their real-world businesses from government to large enterprises.

• 7:10Speaker 00

  And scaling AI, by the way, for folks who are watching or listening to this, was, started off as a data labeling company, ended up eventually having some sort of licensing or agreement with Meta, where Meta paid, I think it was $28 billion-ish.

• 7:27Speaker 01

  Yeah, a little 30.

• 7:28Speaker 00

  Around there, so real money. And so you were a very early and like important person, I think, at scale in terms of the variety of the different businesses you worked on. And then you decided to leave before that happened, actually, to start this business.

• 7:41Speaker 01

  Yeah, for me, there were two things really important. It's scale that showed me a lot more about the real-world businesses. So a lot of my business units, to give you a sense, I built at scale the government business unit and large enterprises in logistics, manufacturing, financial services, healthcare across the board. And I think the tangible impact you can make in the world is incredible. It is the fulfillment you actually get, you know, in tech, we keep talking about this fulfillment that doesn't usually come to many people. But I love doing that. My background, I grew up in a very small town in Turkey. I grew up with nothing and really came here only for college. When I got a full scholarship to Stanford, I didn't even own a computer before.

• 8:25Speaker 01

  And all of my town is actually in these type of industries. So to me, all of us come here and we talk about tech, we talk about creating impact, but majority of the companies that only really serve other startups or tech companies. So to me, that was very important, what are we building for the real world? And I combined that with a technical pursuit, which was a selfish pursuit, is that AI is good at assisting consumers or being a co-pilot. But the next most unsolved problem is that how are we using AI in mission-critical workflows? What does that look like to have a fully autonomous, executing, actually, systems? So Netic came out of really combining these two for me. And at the end, I loved being at scale.

• 9:08Speaker 01

  I was a very good culture fit, I think, and I loved my team. Some of my best friends actually are from there. Obviously, Alex was amazing person to work with directly as a founder. But to me, it was missing the product, right? What is the product? Because it is an operationally-heavy business to build the infrastructure for AI, even though people don't want to talk about it. And it was rewarding, but missing that product edge for me. So I knew I want to build a product that can scale and compound. And two, personal skill set. I think in a lot of those rollups, the main important thing is the M&A itself. I'm not an M&A person. I'm a builder, I am an engineer, I'm a product person.

• 9:51Speaker 01

  It just doesn't fit my skill set and I don't want to build a business where clearly what I can provide is not the most important thing. And I think third is the scale of the product too. What I have seen, there's a lot of successful rollups and tech-enabled rollups, but at the end, all the products you're building are for the company you just bought? It can't really be actually applied to any other company. So you are committing to buying these a few companies in whatever industries that you are interested in and serving those with your products. Whereas what I'm interested in is how every real world business can run on Netic, right? If we didn't have to limit them, if they could focus on what they are good at in that

• 10:32Speaker 01

  business, which is the labor, which is the differentiation, quality of the service, how could Netic run the rest?

• 10:38Speaker 00

  So when people talk about AI for the real world, they mean two or three things, right? So obviously there is what you're doing at Netic and serving these businesses that, you know, go and implement different services for people in their homes or their pets or, you know, different aspects of their life. There's people who talk about robotics, they're self-driving. Like, do you think all these things converge over time? Do you think the timeline on that is very far in the future and doesn't kind of matter in terms of these other types of things?

• 11:02Speaker 01

  Yeah, it's almost you're looking at the same book, maybe, but different chapters. We're talking about much more now chapters and for the next few decades. I do believe that there's a chapter in the future, it is all about robotics, but in some of the industries that I'm working with, that is quite far in the future. And I always say, you know, if you spend a few days with these businesses, which is very important for us, like, you know, I have to tell you about how I learned about these industries and every single engineer in our company do have to go visit customers on site to build the right product back home in San Francisco. And if you look around, if we look outside of a window, look at every single building.

• 11:45Speaker 01

  If robotics is going to do what we're doing with these companies today, every single of those buildings need to be either 3D printed or completely like standardized. I don't see that happening.

• 11:56Speaker 00

  And that's because you just think robotics will be able to navigate the different variation or variety in terms of?

• 12:03Speaker 01

  I think if you look at robotics capabilities today, it is quite far in terms of dexterity on how to be able to handle different types of screws even. What type of homes are this? How am I going up? How am I going into the tiny areas to be able to fix something? Many times it's not clear. You have to open up the whole walls to even see what do you need to fix? How? And on top of that, there is, in these industries, there's a lot of the human element too. Because when a lot of people are dealing with these industries, it is a worst day of their lives, right? It's either their home is flooded or they want to take the day and reduce stress and go play some tennis at the valet club, right?

• 12:47Speaker 01

  But whatever it is that they're actually going through something and there's a human element, I do think there's quite a bit of a while for robotics to be closer in our chapter.

• 12:56Speaker 00

  Yeah, I mean, I've kind of heard you talk about the big labs, so OpenAI, Anthropic, maybe Google, Meta, et cetera. How do you think the lipurs this industry or how do you think what you're doing is different from what they can do?

• 13:08Speaker 01

  Different way of asking that, maybe can labs do this? I think that's a fair question because there's a lot of startups in today's world that do, that build things functionally and visually very similar to the labs' key products, right? It's either a chatbot or a coding agent. I do chuckle at the question a little bit though, because I think 10 years ago, that same exact question was, can Google do this? And then now it became, can labs do this? Sure, some of the things, the core competencies, they can do it, but some of the other things, they're not investing in it. For Netic's case, I don't see them as a competitive risk. It's actually, I think the two, especially the leading labs, they are amazing businesses.

• 13:51Speaker 01

  They're also great partners to companies like us, so I really respect that. But in terms of looking at what we provide to these industries and companies, I actually think two things are very important. One, in focus in what you're building. And I will say, you know, it would be a funny question to these enterprises, right? OpenAI builds amazing products really fast, but also it kills them really fast. So I don't think enterprises are, at least enterprise in these industries, looking for that really fast. Or in Anthropic's case, you know, Silicon Valley converged in the idea that, you know, they pulled ahead in coding agents or like Claude because they had focus, but you see exactly the opposite in the enterprise case. There's about like 20 products, like what is really happening?

• 14:36Speaker 01

  And I don't really see that. And meta focus question, maybe about the labs and specifically researchers, they really care about solving the most generalizable way of the problem, right? So in this case, maybe looking at the problem we're solving, the answer would be, well, when we get the AGI, we'll ask how to solve that for essential services. And I think that is both operationally and intellectually a bit lazy thinking. And the finally is for, to solve these type of extremely difficult problems with millions in the country that have completely different worries, different accents, how do they want to engage, different contexts, and also even engage them again to make them multi-time

• 15:18Speaker 01

  customers, there's quite a bit of last mile that you really have to do that doesn't only come from models, that has to come from your harnesses and orchestration, the software and the product that you have to build on top. So if anything, actually, companies like us and Netic have to be good at all three layers.

• 15:34Speaker 00

  Yeah, that makes sense. One thing I've noticed, which is more sort of a side comment on what you're saying, is that one big shift I see from four years ago and now, you know, four years ago, I was funding things like Harvey and Perplexity and, you know, a little bit later, Decagon and Abridge and a lot of this sort of vertical applications, obviously Netic. And I feel like a lot of founders now are almost a little bit too worried about the labs are doing. And so they're not entering new verticals, they're sort of staying away from things that they think is in the roadmap of the lab, when I think in traditional times, people would have kind of fought it out a bit more. And so I think that's a little bit surprising.

• 16:06Speaker 01

  Yeah, I do think that's because there's a lot of building going on currently that's focused on how can I exit immediately?

• 16:13Speaker 00

  Oh, interesting.

• 16:14Speaker 01

  Instead of, I think being a founder, I actually think was a more honorable thing before. Like, you knew you're dedicating your life to it. Like, I'll give you an example. Before I built Netic, I actually really looked for a job. Is there something I want to build? I looked at the fourth thing I want to build and scale. Is there anything else I'm interested in? And afterwards, is there someone that I really want to help further the mission? I think being a founder is a very difficult thing, that you have to dedicate your whole life for decades. It is not something to be taken lightly, but people are worried about this too much because I think they're looking at it on like, oh, will I be able to exit that short timeframe exits?

• 16:57Speaker 01

  And then the second thing is, maybe this goes into hiring philosophy a little bit. People who are at Netic, who deeply care about what they are building themselves, customer obsessed for the long term, have the agency to start thing, urgency to solve problems, but at the same time to really rigor and patience to carry it forward, right? I see, especially Gen Z in these days, when I'm, you know, looking at hiring, obsessed with this permanent underclass mentality. If I don't make my money in the next 18 months, or if I don't learn everything in the world in the next six months, then I am forever poor or my intellectual.

• 17:35Speaker 00

  This is an AGI-pilled view of, you know, in 18 months, AI will subsume a lot of people and so your value decreases.

• 17:43Speaker 01

  Which I think is actually a very dangerous mindset. In fact, building really good things take a very long time. I have learned some of the most important lessons in my life from, you know, committing to things and keeping up with it with all the problems and with, especially at scale, for example, over really those four years and now with building a company. Because you have to see not just what's the first version of a thing? How are you thinking about what does it do in the world? What do you have to improve? How do you keep up with other research? How do you keep up with people? How do you need to improve that, right? I think especially we look for that, we really avoid shiny object seekers.

• 18:23Speaker 01

  And there's a, recently I was reading this, you know, quote attributed to Martin Luther, actually. It says, you know, the Christian shoemaker, you know, doesn't honor God by putting little crosses on the shoes, it does so by building the best shoe, right? The best shoes, because God cares about craftsmanship. And I think I really resonate with that when you think about as a founder, what are you building? Why are you doing this, right? It really is about building the best product that are solving the problems of the people you care about. If anything, you actually achieve more with less, with more focus and with a small group

• 19:03Speaker 01

  of people that are really, that came together to take down the whole world, right?

• 19:09Speaker 00

  You mentioned selecting for people with the agency. How do you screen for agency? Like, what do you look for? Is it an interview question? Is it experiences? Is it something else?

• 19:18Speaker 01

  Um, I think agency, what I look for is like not agency now. If you have agency, you care about agency, you have shown agency continuously in your life. So I will actually dig in, how, how was it like if you're a new grad, you don't have to have a job. Did you do something in college? Did you do something to be able to get into college? Do you have a project? Do you really care about? And not just that, like I did this for a weekend, but did you keep up with it? Right? So what are really those examples? And I think I do ask many times, it's just one question. I'd like to know about what people do, what has been the hardest thing they have ever done in life? And they can take it anywhere, but it's not just one question, but we'll really dig in to understand the why.

• 20:03Speaker 00

  Yeah.

• 20:03Speaker 01

  Or you pull that apart from someone's life story, right? But the most important thing I care about, not to have one agency example, is just however long you have been alive and conscious. Have you been showing agency in things that you did in life? And did you keep up with them? Did you stick through?

• 20:24Speaker 00

  You started something, you did something unique that most people don't do. And then you kept going on it. It's funny, I used to ask the same question of what's the hardest thing you've ever done? And I got such bad answers that I stopped asking it.

• 20:36Speaker 01

  Well, I mean, you know, I don't know why you asked that, but you know, if you get bad answers, you know, maybe that person is not really a good.

• 20:42Speaker 00

  Well, it's just consistently, I just mean like the hiring pool that I was at least looking after that.

• 20:46Speaker 01

  I do get really good answers. I think they're very different answers, right? Some will really open up and I, I'm not looking for a work, work answer. Like it can be anything in your life that truly the hardest thing. And sometimes you learn a lot about people's personal lives, that's something they had to go through. They didn't choose, but it was all about how they reacted, what they controlled. How did they take something they can control in their hands and actually change the future? Right? And sometimes it's about, uh, you know, it also doesn't have to be this grand, grandiose thing. I'll give you an example of someone we just hired, actually, he's starting at next week. And, you know, he gave this answer, this was the first time someone gave an answer like this. He said, I live a very simple life.

• 21:28Speaker 01

  I deeply care about my work and I have a crazy regimen about how I think about my health. And really outlined a little bit what they meant, right? Like outside of that, I don't really have a lot. But the hardest thing for me has been, I kept up with this for X amount of years. Every single day, like waking up this hour, doing these things every other hour at night. And showing up for my coworkers. And the hardest thing has been doing that for over 15 years and without getting bored, without really thinking about anything else and committing myself to what I care about. And I thought that was also a very creative answer, right?

• 22:05Speaker 01

  Like, I'm not really looking for, um, you know, maybe when I gave that answer, like my answer is a lot about building a company or about how I came from a very tiny town. When my parents didn't have anything to hear, but I'm not looking for that. Everybody's story is different. How did you make your own story? I thought that was a great answer and we're very happy to have him.

• 22:25Speaker 00

  That's amazing. How do you think about where you want to be with the company in five years? Or what's your longer term vision for what you folks have accomplished, what you're doing, what's your sort of North Star?

• 22:35Speaker 01

  In terms of our vision, we are building an autonomous enterprise. We want every single thing in these companies to be handled autonomously with Netic. Except the actual services and the labor itself, that human component, so that these companies can fully focus on that to deliver and create customer delight. And that is number one thing with the company, every single product, every single thing that we build on top of our intelligence layer. That compounds and connected to, to the other products is for that purpose. And second is, you know, building a company is very hard. And I'm also doing that for the vision, but also to work with remarkable people.

• 23:19Speaker 01

  I think for me, as the company grows, something I deeply care about, how do we keep working with only remarkable people? And there, there's no one answer. I think every single company that I know, that I respect, um, that even thought about these things for the long term, like imagine Palantir or SpaceX or Notion. Who really care about craftsmanship and really delivering for their audience for many, many years have struggled with this. So for me, um, deeply thinking about that and achieving that is very important, um, in the company.

• 23:53Speaker 00

  So you're serving a lot of industries that are perceived as very slow to adopt technology or not at the cutting edge, or, you know, things that take a long time to, you know, use new things. And you're selling AI solutions and agents to them. Has that been challenging? Has that been straightforward? Like, is that perception correct? Like, how do you think about your customer base in terms of just like the rate at which they'll adopt new things or try new things?

• 24:15Speaker 01

  I think it's a big misconception to think about these industries as old school. Um, actually, some of the most tech forward, business focused people, owners, founders I have met have been in these industries. So first of all, we, we work with large enterprises, so they're extremely value focused and they have to be tech forward, right? For example, uh, to give you a sense, you know, like just one of the businesses we closed, it can be like a half a million contract. Um, and it took from end to end 14 days. And it's not because, you know, there is, you know, they, I'm not a magic potion and the company is not, or just AI is not. They're very thoughtful about what they have to do and checking if the value is there, right?

• 25:00Speaker 01

  Even in their buying, uh, behavior. Uh, that being said, I think the way that I think about these industries is that they are extremely primal and tech forward at the same time. So if you think about a large roofing company, right? Is actually they have to have door knockers. So door knockers mean, you know, going neighborhood to neighborhood, thinking about the friend, you know, roofs and trying to talk to you about why you should think about a new way. Or like having solar on your roof, right? But at the same time, today in Netic, it's a compilation of product from handling, handling everything inbound, outbound analytics and even delivery of their labor.

• 25:39Speaker 01

  So we connect to satellite data to be able to think about in different neighborhoods, how the hurricanes affect different roofs. How should you think about different materials? Should that be autonomously fed into the context of our agents? So that not only you're better equipped to handle that conversation with the customer, but also you can spot who to go after. So these are not.

• 26:02Speaker 00

  Is this technology they were using before? Or is this, uh, you know, and then you adopted it for the Netic platform?

• 26:07Speaker 01

  Yeah, I think, so they were always interested in how do we serve our customers better? But they had to figure out how to do that, right? Do we get this data somewhere else or who looks at it? Do we look at it manually? So now imagine with one platform, okay? Not only I am actually assisting with the inbound that's coming from the ads we have to do. But at the same time, I'm building context about the neighborhoods that I have to serve and reaching out to bring net new revenue. So that is now they can do it very easily in one platform with Netic. But they were already thinking about these like additional data and sifting through that with different tools or humans, et cetera. And then send door knockers before. And that's just one industry, right? And then we talked a little bit about rollups and being private equity owned.

• 26:52Speaker 01

  Now imagine being a private equity and you own maybe 20, 30 of these, these businesses in different industries. So now if those are on Netic, what you can do is, well, if you're going to go after someone for a wellness offering, right? And I have a dog that I love. And if I'm going to be a member in a wellness offering, I would actually very much like to pick the one that has pet care, right? So if you know that about me and as the owner of the company, how would you think about talking to me about that? That is all about context and really understanding and doing that easily for your business.

• 27:25Speaker 00

  How well do you, or how do you view private equity firms as responding to this wave of AI? I think, um, they're, they're varying opinions in terms of everything from people are really leaning in and they're trying new things. And in some cases they're having to deploy companies, they're working with folks like, um, Brainco or other companies. In other cases, they're, uh, slower to, to move on it. What's your, what's your perception of like how private equity is interacting with AI?

• 27:49Speaker 01

  I think already the private equity playbook has changed. Before it used to be right, we're going to find a gem and that has an amazing multiple. And we are going to go change the team and create the value and then sell it again. But those gems don't really exist anymore, like undiscovered. So I think generally the playbook has changed to how do we create tangible value with these businesses that we're working? I think you are right that some are leaning in, maybe a bit too much, like without, um, you know, trying everything as if it's software. And you know that, that any product I use in AI, it's not like, you know, the first week, that shouldn't be how you look at the platform. It should be the beginning of the relationship.

• 28:30Speaker 01

  If anything, actually, you want to make sure those results exist throughout the year and keep getting better and not keep getting worse, right? Um, so I think that's important to change the shift on testing the AI, like AI and separating from vaporware to true ROI. And how do you do that? I think a lot of them at times can be more software oriented, you know, deterministic, but why can I not try that like in a week and tell? But many, I think, do understand with this new role that private equity companies hires, like different operating partners in AI. Or they'll have a few engineers that might be AI forward and they'll educate it as well. And in our job, you know, I always see in the company too, something is not hard.

• 29:15Speaker 01

  Is that like, what can we do better? So in a lot of these conversations, the conversation is all about the value they're going to get and what they can see tangibly now. It's not demos. We'll pull up and show, show a live deployment, right? Because like if it's working and I have it, why can't you just show you what this customer is making? That, you know, we have, you asked me about my North Star recently. We have made so far, I think over $600 million for our customers that have been really generated from AI handled interactions. Show that, how does it work? How is the real world customers interacting with this technology? So I think once you do that, they also get educated and they guide their companies.

• 29:57Speaker 01

  But still it doesn't, it is not taking away the notion of you have to have a relationship direct to the company. Because at the end, uh, private equity is more of a guidance for the companies they own. There's not many times, types of relationships where you can just shove it down the throats of the companies. But you can be a good counselor and you can be a good advisor to the companies and what to check for.

• 30:20Speaker 00

  Yeah, it seems like a lot of, um, private equity shops as well have kind of shifted from the eighties style, you know, come in, do big layoffs, take apart a conglomerate. And much more to your point, how do you optimize value or increase the value of something?

• 30:33Speaker 01

  I will say though, it's still, they are always the first conversations, very focused on cost cutting. Because I think they don't see a lot of products or platforms like ours. I'm not really there to cut your costs. Sure, that is happening in this way, but I'm really interested in this is how you're going to make net new revenue. So that is new. You have to actually start that conversation. You have to show them intangible examples because otherwise it's still focuses on how do we get to the bottom line and cut some costs, right? But they have to almost expand their horizon on thinking about what else is possible with AI, right? It would be pretty sad if we used AI only for cost cutting.

• 31:12Speaker 00

  Yeah, yeah, sure. What do you, outside of what Netic is doing, what are you most excited about in terms of the future in AI?

• 31:18Speaker 01

  I am really excited. So I told you a little bit about my personal story. So one of the, you know, when I didn't have access to anything, one of the, in my time, maybe the technology that helped is that I would find one or two people who graduated from my high school, like to read some of my essays or look at my work and give feedback or Facebook Messenger them. And it was, it was just being able to talk when they were in the US in colleges and they went from Turkey. It was pretty crazy. So like I will give the answer of education because I, I think it will change so many lives of people who otherwise would not even think about this world exists. So I'm personally really excited about that.

• 32:01Speaker 01

  And no one will be limited anymore that like everything you want to learn and everything you want to do is kind of in your pocket, right? So we made the world a lot more about agency, which I'm excited about. And I cannot wait to see that unfold.

• 32:21Speaker 00

  Yeah, it's very exciting. I think one big lesson for me is always you can just go do stuff. Like you don't need permission, you don't need to learn stuff, you can just go do things.

• 32:29Speaker 01

  But you know, that makes it also a little bit scary too. Then when you see people not doing stuff, then it's a little bit of a dystopian version of it because in, in any era or technology you live with, you can always do stuff. It ends up, it stays with the choice you have to make. We keep making it easy and easier, easier and easier to make that choice, but still I guarantee you majority of the world will not be making that choice. So it is something, something to think about, a little bit more negative. So, um, but I am happy that at least we're taking away the resourcing as a question, whether you have access to something or not.

• 33:10Speaker 01

  The second thing I am really excited about, a lot i- i- in America or in generally right now, more mainstream topic about AI is very negative. And what I'm excited about with use cases, like I'm working on, it's many times the people's worst day in their lives and they really need help and how do we make sure that you get help? Or in education or in about being able to look at your health records and really understand, you know, I was recently using the health feature and trying to understand how can I sleep better? And there's no answer. It's like, you gotta stop being a founder. But I think there are a lot more positive ways that we, we are going to start talking

• 33:51Speaker 01

  about AI and how people's first interaction with AI is not only about like why XYZ is going away or jobs are going away, but positive impact of AI. That's more in terms of the conversation in the world I'm most excited about.

• 34:05Speaker 00

  Amazing, yeah. Well, thank you so much for joining us today, NoPriors. It was a pleasure.

• 34:08Speaker 01

  Thank you for having me.

• 34:12Speaker 02

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