打造服务现实世界的自主企业:与 Netic 创始人 Melisa Tokmak 对谈
Netic 正在为基础服务运营商打造一家“自主企业”,把实体服务之外的所有环节自动化,同时将履约和人工劳动留给人来完成。 其代理处理语音、文字和网页交互,推断客户需求,执行运营规则,并调度合适的工作人员。其目标是让 AI “运营数百万家维持世界运转的现实企业”。
切入口早已不只是电话接待溢出;Tokmak 表示,如今超过70%的客户属于“Netic first”,所有客户的首次互动都由 AI 处理。 在 HVAC 领域,这意味着判断设备类型、紧急程度、是否能提供服务、客户终身价值,以及稀缺的锅炉专家今天该出工还是改到之后,而不只是接起电话。
Tokmak 选择可规模化的垂直软件,而不是通过 AI 赋能的服务业并购整合,因为 M&A 不是她的强项,而并购整合软件通常会被锁定在被收购资产之内。 她选择的替代方案是一层所有“现实世界企业都能运行其上”的通用智能基础设施,让运营商把精力集中在服务质量和差异化劳动上。
Tokmak 认为,Netic 的差异化来自垂直场景的执行能力,而不只是模型本身。 她不认为头部实验室构成竞争风险:这些公司解决的是可泛化问题,而任务关键型服务需要领域聚焦,并在3个层面同时具备“harness 和编排、软件与产品”。在她看来,等 AGI 来解决基础服务,是“在运营和认知上都有点懒惰的想法”。
采用数据正在挑战“基础服务企业是技术落后者”的假设。 Tokmak 提到,一笔50万美元的合同从头到尾在14天内完成,并估算 Netic 已通过 AI 处理的客户互动为客户创造了“超过6亿美元”。她的商业推介主要围绕新增收入展开,因为“如果我们只用 AI 降本,那就太可悲了”。
公司的经营哲学更看重经得起时间考验的匠心,而不是短期的 AI 投机机会。 Tokmak 会避开“追逐新奇事物的人”,招聘时考察一个人在一生中反复展现出的主动性,以及执行力、严谨性和耐心。她认为,创始人对实验室路线图的恐惧,反映出许多企业是为快速退出而设计的,而不是为了“把自己的一生都献给”一家能经营数十年的公司。
Tokmak 更广泛的 AI 乐观主义,核心是让教育触手可及,但她不会把获得知识与采取行动混为一谈。 把知识“放进口袋”会消除资源约束,让世界更多取决于人的主动性;但更阴暗的现实是,无论技术把行动变得多么容易,她仍敢保证,大多数人依然不会选择行动。
1. 基础服务需要编排,而不是又一个聊天机器人
Tokmak 将 Netic 定义为服务于大型企业的 AI,覆盖 HVAC、管道、电气、屋顶施工、汽车、酒店、宠物护理和消费健康等行业。“Netic 存在于企业与客户之间”,负责理解需求,并根据每家运营商的规则、服务能力和人力资源进行匹配。
在 Netic 出现之前,这些流程主要由人处理。许多运营商本质上是以 EBITDA 为核心的企业,且常由私募股权持有,若不持续投入人力就无法增长。它们的支持团队并不稳定:一家大型企业可能在早上6点前就开始营业,先后遇到数名员工离职或缺勤,随后又在热浪或其他季节性高峰期间迎来需求激增。由于许多服务本身同质化,没能接听电话就可能把客户推向下一个搜索结果,甚至下一个 AI 答案。
她举的关键案例发生在零下20度:有人家里的暖气坏了。Netic 可以通过语音、文字或网页接待客户,调取住户档案,了解设备情况和紧急程度,并判断企业是否能够提供帮助——尤其是在屋内可能有儿童或老人的情况下。
资源分配问题远不止于派出下一名空闲技师:需要判断安装的设备类型、客户是今天还是明天需要服务、客户终身价值,以及是否应该派出稀缺的锅炉或新型系统专家。目标既是让“客户满意”,也是创造更多收入。
Elad 最初将 Netic 定位为电话接待溢出,但 Tokmak 的修正很关键。电话溢出只是许多客户的起点,如今超过70%的客户已经是“Netic first”,即“N1”:他们与公司的首次互动对象是 Netic 代理,而不是人工团队。
2. 软件规模化胜过买下并运营底层资产
Tokmak 的动机既来自个人经历,也来自一个技术问题。她在土耳其一个小城长大,那里的人普遍从事这些行业;后来凭借斯坦福全额奖学金赴美读大学,此前甚至从未拥有过一台电脑。在 Scale AI 用4年时间搭建政府和企业业务后,她希望技术能够服务现实世界,并打造“一款可以规模化、持续复利的产品”。
Elad 的质疑值得保留:为什么不直接买下 HVAC 及类似服务商,再用 AI 优化它们?Tokmak 的回答有3层。第一,M&A 不是她的核心能力;第二,她是 builder,也是产品工程师;第三,并购整合软件仍会被锁在少数被收购公司内部,无法成为整个市场的基础设施。
机器人与此“属于同一本书,但处在不同章节”。Tokmak 预计未来会进入机器人章节,但认为许多服务业距离那一步仍很远:每栋建筑都得先进行3D打印或完全标准化,而现有工作要求在狭小空间内处理不同零部件,并具备高度灵巧性。技师甚至可能要先拆开墙壁,才能知道问题在哪里。
3. 垂直执行能力填补通用实验室留下的空白
当被问到 OpenAI、Anthropic、Google 或 Meta 是否能够打造同样的产品时,Tokmak 对这种翻版的“Google 能不能做这个?”笑了出来。她认为头部实验室是强大的企业和合作伙伴,但并不是 Netic 聚焦型企业工作流的竞争风险。
她关于聚焦的论点具有双重含义:OpenAI 推出产品很快,但也“淘汰得非常快”;Anthropic 备受推崇的 coding 聚焦,则反衬出她在企业端看到的现状——大约20款产品,而不是同样聚焦的一套方案。基础服务运营商需要稳定、长期的合作关系,而不只是快速推出更多产品。
Tokmak 表示,研究人员自然会去寻找最具普适性的解决方案,但把垂直问题推迟到 AGI 能够回答它时再处理,就等于回避了真正的工作。数百万客户会带来不同的口音、语境、担忧和再次沟通需求;要取得成功,必须让模型、编排层和工具链,以及为特定场景打造的软件协同工作。
Sarah 观察到,如今创始人会主动避开那些他们认为已经写在实验室路线图上的垂直领域。Tokmak 更尖锐的诊断是短期主义:太多创业都围绕“我怎么才能立刻退出”,而创建一家有影响力的公司,意味着要用“自己的一生”投入其中,并坚持数十年。
4. Netic 招聘的是持续的主动性与匠心
Tokmak 反对那种“永久底层心态”:认为一个人必须在18个月内赚到钱、在6个月内学会一切,否则就会永远贫穷。与之相伴的,还有一种被 AGI 叙事影响的恐惧——AI 会在18个月内吞噬大量技能,并降低人的价值。她的反驳来自经验:“把真正好的东西做出来需要非常长的时间”,而最深刻的教训来自持续经历一轮又一轮的版本迭代和问题解决。
她引用归于 Martin Luther 的一个文化隐喻:基督徒鞋匠荣耀上帝的方式,不是给鞋子加上十字架,而是“把鞋做成最好的鞋”。放在 Netic 身上,匠心意味着为团队真正关心的人解决问题,保持专注,并由一支能够“拿下整个世界”的小团队完成。
她考察一个人的主动性时,会追溯其完整经历:这个人主动发起过什么,为什么重要,以及是否坚持了下去。应届毕业生不需要正式工作经历,但一个周末项目远远不够;她要看到的是反复掌控局面、改变未来的证据。
Elad 在收到一些糟糕回答后,不再问“你做过最难的事情是什么”。Tokmak 则为这个问题的覆盖面辩护。一名新员工给出的答案,是连续超过15年、每天坚持一套高强度的健康与工作安排——并不光鲜,却证明了一个人能够长期投入,“而且不会感到厌倦”。
5. 收入验证正在改写企业和私募股权推介逻辑
Tokmak 认为,把基础服务称作“老派”是一种误解。大型运营商极度看重价值,也能够快速决策:她提到过一笔50万美元的合同,从端到端完成只用了14天,买方此前还认真验证了这项价值是否真实存在。
屋顶业务同时具备原始性和技术性。企业仍会派人挨家挨户敲门推销,而 Netic 可以把主动流入的需求与卫星数据结合起来,分析飓风对屋顶的影响、社区环境和屋顶材料,从而让代理与客户展开更好的对话,并识别应该主动触达哪些对象以创造新增收入。
私募股权过去的打法,是找到一颗尚未被发现的宝石,换掉团队、创造价值,再卖给下一家;但这一套正在改变,因为“这样的宝石已经不太存在了”。Tokmak 看到,市场上有更多运营合伙人和懂 AI 的工程师,但她警告,不要把每个 AI 产品都当作可以在1周后评判的软件:第1周应该是关系的起点,成果则应在全年持续、不断改善。确定性更高的产品,仍可能很快完成测试。
Tokmak 估算,Netic 已通过 AI 处理的客户互动为客户创造了“超过6亿美元”,她更愿意展示真实上线项目,而不是演示 Demo。私募股权买方仍会从降本开始,因此 Netic 必须扩大叙事框架:效率提升可能存在,但核心论据应是可量化的新增收入和更好的服务。
We're joined by Melisa Tokmak, the founder and CEO of Netic, a company that builds AI for real-world services like HVAC, pet care, and roofing. Prior to Netic, Melisa was a director of engineering and worked on various aspects of go-to-market at Scale AI, and she also has experience at Meta. Melisa, thanks for joining us today.
Thank you for having me.
Yeah, maybe we can start off by talking a little bit about your business and what you're building, because I think you're doing something really interesting in the real world and kind of mirroring AI in the real world. Could you tell us more about your company, Netic, and what you're focused on?
Netic builds AI to run millions of real-world businesses that keep the world running. That means we work with large enterprises in essential services. We started in essential services.
What would be an example of an essential service?
Imagine home-services companies with $1 billion in revenue in HVAC, plumbing, or electrical, or consumer-wellness companies where you can become a member and go do a lot of sports or different activities. Hospitality, automotive, and pet services are all examples across the board. Every single thing that you need to run your life or that you want to do is a good example, and a lot of these businesses are quite large and interact with millions of end users themselves, usually consumers or businesses.
Netic exists between the company and its customers. Every single thing to understand the customer's need or want and match that with how we can help the customer within the operational rules of the business—and even deploy the services or the labor—all happens on Netic.
So, basically, say a customer calls an HVAC provider. What happens, or what is Netic doing for them?
Imagine that you are in the middle of nowhere, it's 20 degrees below zero, and your heat stops working. You first find 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 20-degree-below-zero weather. Maybe you have a kid or an elderly person, or something isn't working.
From there, once you find a business—and usually you can find these from aggregators, search engines, or now LLMs—you can reach out to the company through any medium you want. If they're using Netic, you can call them or text them, or go to their website. It's Netic agents that talk to the customer: What kind of home do you live in? Do we have any of your records?
I see. So this could be a voice call, and Netic is actually providing the voice.
Completely.
And then the reasoning around, “Hey, this person needs some help, and we should deploy somebody to fix their HVAC.”
Exactly. A lot of the businesses we work with have complex operational needs, which is why we started with essential services. It's not as simple as, “Oh, Elad's heat broke, and now Melisa goes.” You have to ask: What kind of units do you have? What kind of needs do you have? Can we come to you? Is it something that we need to address today or tomorrow? What is your lifetime value as a customer?
Should we deploy the best person, who can only work on, let's say, boilers or new-age systems, today or later? It's quite complex to first understand what the need is from the customer, whether the company can service it, and, if so, who should do it and when. You want to ensure that it's all optimized to create customer delight and generate more revenue for the company.
That makes sense. What is the incumbent version of what you're doing? What are the other players in the market, or how should people think about what this replaces?
Let's go back. How do people do this today? We're a 2-year-old company, so before us, how were they doing it? It's primarily with people. These companies are extremely large, and they can't grow because they have to keep investing in people to achieve any kind of growth. They're EBITDA businesses, and many times they're owned by private equity. They need to care about their margins and what they make in order to invest back in the business.
The most important labor in the business is the people who are going to deliver the job. You want to focus every single thing on making your end customer happy, because a lot of these businesses are commodities. If you do not answer me, I'm going to go to the next one—the next search result on Google, the next result on an AI search.
It's very important to be able to invest your money into your labor, the blue-collar labor. Until now, that meant 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 the life of a company that makes $1 billion in revenue. The business usually starts at 4:00 or 5:00 a.m., and you don't really have anybody in the company. Maybe your technicians start at 6:00 a.m., but before then, no one is there. You might come in as a manager, but at least 3 people quit that day, or 5 didn't show up.
All these customers are piling in starting at 6:00 a.m. because now there's a heat wave in the country. Actually, this past week, we hit record heat waves in the country. What do you do as a business?
Many of these businesses are cyclical. It's very important in winter, summer, the holiday season, and the season when people start working out. 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.
Because you're providing agents to take overflow—if somebody's giving you a lot of phone calls, your agents can pick up the phone calls for them.
Yeah. That's how many of our customers started. But today, over 70% of our customers are AI-first. We call it Netic-first. They go N1. For over 70% of our customers, the first interaction with the company is with Netic agents.
There are a few different approaches you can take for markets like this. I'm excited to be an investor in Netic. I've also invested in AI roll-ups, where a company like Long Lake will buy a bunch of businesses and then optimize them with AI. In some cases, these businesses overlap with the profile of your customer set, and you mentioned that many of them are already owned by private equity.
How did you make the decision to build this service versus doing a roll-up or buying and running the assets? What are the trade-offs between those approaches?
I think there are 3 reasons: what I want to build in the world, my skill set, and scale. Before building this, I was at Scale for about 4 years, and I built a lot of their real-world businesses, from government to large enterprises.
And Scale, by the way, for folks who are watching or listening to this, started off as a data-labeling company. It eventually ended up having some sort of licensing or agreement with Meta, where Meta paid—I think it was $28 billion.
Yeah-ish, a little over $30 billion, around there. So, real money.
You were a very early and important person at Scale in terms of the variety of different businesses you worked on, and then you decided to leave before that happened, actually, to start this business.
For me, there were 2 things that were really important. Scale showed me a lot more about real-world businesses. To give you a sense, I built the government business unit at Scale, as well as large-enterprise businesses in logistics, manufacturing, financial services, and healthcare across the board.
I think the tangible impact you can make in the world is incredible. It is the fulfillment you actually get. In tech, we keep talking about this fulfillment that doesn't usually come to many people, but I love doing that.
My background is that 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. Everyone from my town is actually in these types of industries.
To me, all of us come here and talk about tech and creating impact, but the majority of companies only really serve other startups or tech companies. It was very important to me to ask: What are we building for the real world?
I combined that with a technical pursuit, which was a selfish pursuit. AI is good at assisting consumers or being a co-pilot, but the next most unsolved problem is: How are we using AI in mission-critical workflows? What does it look like to have fully autonomous, actually executing systems?
Netic came out of combining those 2 things for me. In the end, I loved being at Scale. I was a very good culture fit, I think, and I loved my team. Some of my best friends are from there. Obviously, Alex was an amazing person to work with directly as a founder.
But to me, what was missing was the product. What is the product? It is an operationally heavy business to build the infrastructure for AI, even though people don't want to talk about it. It was rewarding, but it was missing that product edge for me, so I knew I wanted to build a product that could scale and compound.
And, 2, personal skill set: I think in a lot of those roll-ups, 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 am a product person. 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. I think the third thing is the scale of the product, too.
What I have seen is that there's a lot of successful roll-ups and tech-enabled roll-ups, but at the end, all the products you're building are for the company you just bought. It can't really be applied to any other company. So you're committing to buying these few companies in whatever industries you're interested in and serving those with your products, versus what I'm interested in, which 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're good at in that business—which is the labor, the differentiation, and the quality of the service—how could Netic run the rest?
Sarah Guo
And so, when people talk about AI for the real world, they mean 2 or 3 things, right? Obviously, there's what you're doing at Netic and serving these businesses that go and implement different services for people in their homes, for their pets, or in different aspects of their lives. There are people who talk about robotics and self-driving. Do you think all these things converge over time? Do you think the timeline for that is very far in the future and doesn't matter in terms of these other types of things?
Yeah, it's almost like you're looking at the same book, maybe, but different chapters. We're talking about many more chapters over the next few decades. I do believe that there's a chapter in the future that is all about robotics, but in some of the industries that I'm working with, that is quite far in the future.
I always say, if you spend a few days with these businesses, which is very important for us—I have to tell you about how I learned about these industries—every single engineer in our company has to go visit customers on-site to build the right product back home in San Francisco. If you look around, if we look outside a window and look at every single building, if robotics is going to do what we're doing with these companies today, every single one of those buildings needs to be either 3D-printed or completely standardized. I don't see that happening.
Sarah Guo
And that's just because you think robotics will be able to navigate the different variations?
I think if you look at robotics capabilities today, they are quite far from what is needed in terms of dexterity and being able to handle different types of screws, or even different types of homes. 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 wall to even see what you need to fix.
On top of that, there is a lot of the human element in these industries, too, because when a lot of people are dealing with these industries, it is the worst day of their lives, right? Either their home is flooded, or they want to take the day to reduce stress and go play some tennis at Bay Club, right? Whatever it is, they're actually going through something, and there's a human element. I do think there's quite a bit of a while before robotics is closer in our chapter.
Sarah Guo
And then I've kind of heard you talk about the big labs—OpenAI, Anthropic, maybe Google, Meta, and so on. How do you think they'll approach this industry, or how do you think what you're doing is different from what they can do? A different way of asking that, maybe, is: can the labs do this?
I think that's a fair question because there's a lot of startups in today's world 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?” Now it has become, “Can the labs do this?” Sure, some of the things—their core competencies—they can do, but some of the other things, they're not investing in. In Netic's case, I don't see them as a competitive risk.
Actually, I think the 2 leading labs are amazing businesses. 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 think 2 things are very important.
One is focus on what you're building. It would be a funny question to ask these enterprises, right? OpenAI builds amazing products really fast, but it also kills them really fast. I don't think enterprises, or at least enterprises in these industries, are looking for that really fast pace. In Anthropic's case, Silicon Valley converged on the idea that they pulled ahead in coding agents, like Claude, because they had focus. But you see exactly the opposite in the enterprise case. There's about 20 products. What is really happening? I don't really see that.
A meta-focused question, maybe about the labs and specifically researchers, is that they really care about solving problems in the most generalizable way, right? So in this case, maybe looking at the problem we're solving, the answer would be, “Well, when we get to AGI, we'll ask how to solve it for essential services.” I think that is both operationally and intellectually a bit lazy thinking.
And finally, to solve these types of extremely difficult problems for millions in the country who have completely different worries, different accents, different contexts, and different ways they want to engage—and to engage them again to make them multi-time customers—there's quite a bit of last mile that you really have to do. That doesn't only come from models. It has to come from your harnesses and orchestration, the software, and the product that you have to build on top. So if anything, companies like us and Netic have to be good at all 3 layers.
Sarah Guo
Yeah, that makes sense. One thing I've noticed, which is more of a side comment on what you're saying, is that one big shift I see from 4 years ago to now is that, 4 years ago, I was funding things like Harvey and Perplexity and, a little bit later, Decagon and Abridge, and a lot of the sort of vertical applications—obviously, Netic.
I feel like a lot of founders now are almost a little bit too worried about the labs and what they're doing, so they're not entering new verticals or staying away from things that they think are in the roadmap of the labs. In traditional times, I think people would have fought it out a bit more, and so I think that's a little bit surprising.
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?”
Sarah Guo
Oh, interesting.
Instead, I think being a founder was a more honorable thing before. You knew you were dedicating your life to it. 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 to 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 like, “Oh, will I be able to exit?”—the short-time-frame exits.
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, are customer-obsessed for the long term. They have the agency to start things, urgency to solve problems, but at the same time, the rigor and patience to carry them forward.
I see, especially Gen Z these days, when I'm looking at hiring, an obsession 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 6 months, then I am forever poor. Or this is an AGI-pilled view: in 18 months, AI will subsume a lot of people's skill sets, and so your value decreases.
Sarah Guo
Which I think is actually a very dangerous mindset. In fact, building really good things takes a very long time.
I have learned some of the most important lessons in my life from committing to things and keeping up with them through all the problems, especially at Scale—for example, over those 4 years and now with building a company—because you have to see not just what's the first version of a thing.
Sarah Guo
How are you thinking about what it does in the world, what you have to improve, how you keep up with other research, how you keep up with people, and how you need to improve that?
I think we especially look for that. We really avoid shiny-object seekers. Recently, I was reading this quote attributed to Martin Luther. It says, “The Christian shoemaker doesn't honor God by putting little crosses on the shoes. He does so by building the best shoe.”
Sarah Guo
Right? The best shoes.
Because God cares about craftsmanship. I really resonate with that when you think about, as a founder, what are you building? Why are you doing this? It really is about building the best product that solves the problems of the people you care about.
If anything, you actually achieve more with less, with more focus, and with a small group of people that really came together to take down the whole world, right?
Sarah Guo
You mentioned selecting for people with agency. How do you screen for agency? What do you look for? Is it an interview question, experiences, or something else?
I think agency—what I look for is not agency.
Now, if you have agency, care about agency, and have shown agency continuously in your life, I will actually dig in. How was it? 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 you really care about? And not just, “I did this for a weekend,” but did you keep up with it? What are really those examples?
I think I do ask many times. It's just one question. I'd like to know what people do and what has been the hardest thing they have ever done in life. They can take it anywhere, but it's not just one question—we'll really dig in to understand the why, or pull that apart from someone's life story. The most important thing I care about is not having one agency example. It's this: however long you have been alive and conscious, have you been showing agency in the things that you did in life? Did you keep up with them? Did you stick through?
Sarah Guo
So, you care about the follow-through. You started something, did something unique that most people don't do, and then kept going on it. It's funny. I used to ask the same question: “What's the hardest thing you've ever done?” And I got such bad answers that I stopped asking it.
Maybe that person isn't really a good fit.
Sarah Guo
Well, it's just consistently bad. I just mean the hiring pool that I was at least looking at.
I do get really good answers. I think they're very different answers. Some people will really open up, and I'm not looking for a work answer. It can be anything in your life that was truly the hardest thing. Sometimes you learn a lot about people's personal lives—something they had to go through that they didn't choose—but it's all about how they reacted, what they controlled, and how they took something they could control into their own hands and actually changed the future.
Sometimes it's also about—you know, it doesn't have to be this grandiose thing. I'll give you an example of someone we just hired. He's starting next week, and he gave this answer. This was the first time someone gave an answer like this. He said, “I live a very simple life. I deeply care about my work, and I have a crazy regimen for how I think about my health,” and really outlined a little bit of what he meant.
“Outside of that, I don't really have a lot, but the hardest thing for me has been keeping up with this for X amount of years, every single day: waking up at this hour, doing these things every other hour at night, showing up for my coworkers. The hardest thing has been doing that for over 15 years without getting bored, without really thinking about anything else, and committing myself to what I care about.”
I thought that was also a very creative answer. Maybe when I gave that answer, mine would be a lot about building a company or about how I came from a very tiny town, where my parents didn't have anything, to here. 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.
Sarah Guo
That's amazing. How do you think about where you want to be with the company in 5 years, or what's your longer-term vision for what you folks have accomplished and what you're doing? What's your sort of north star?
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 delivering and creating customer delight. That is the number-one thing with the company. Every single product, every single thing that we build on top of our intelligence layer, which compounds and is connected to the other products, is for that purpose. Mhm.
Second, building a company is very hard, and I'm also doing that for the vision, but also to work with remarkable people. For me, as the company grows, something I deeply care about is: how do we keep working with only remarkable people? There's no one answer. I think every single company that I know and respect—even those that have thought about these things for the long term, like Palantir, SpaceX, or Notion, which really care about craftsmanship and delivering for their audience for many, many years—have struggled with this. So, for me, deeply thinking about that and achieving it is very important in the company.
Sarah Guo
You're serving a lot of industries that are perceived as very slow to adopt technology, not at the cutting edge, or just things that take a long time to use new things. You're selling AI solutions and agents to them. Has that been challenging? Has that been straightforward? Is that perception correct? How do you think about your customer base in terms of the rate at which they'll adopt new things or try new things?
I think it's a big misconception to think about these industries as old-school. Actually, some of the most tech-forward, business-focused people—owners and founders—I have met have been in these industries. First of all, we work with large enterprises, so they're extremely value-focused, and they have to be tech-forward. For example, to give you a sense, one of the businesses we closed had a $500,000 contract, and it took 14 days from end to end.
It's not because there's some magic potion. The company isn't one, and AI isn't one. They're very thoughtful about what they have to do and checking whether the value is there, even in their buying behavior.
That being said, I think the way to think about these industries is that they're extremely primal and tech-forward at the same time. If you think about a large roofing company, they actually have to have door knockers. Door knockers means going neighborhood to neighborhood, thinking about different roofs, and trying to talk to you about why you should think about a new roof or having solar on your roof.
At the same time, today in Netic, it's a compilation of products handling everything inbound, outbound, analytics, and even the delivery of their labor. We connect to satellite data to think about, in different neighborhoods, how hurricanes affect different roofs and how you should think about different materials. That should be autonomously fed into the context of our agents so that not only are you better equipped to handle that conversation with the customer, but you can also spot whom to go after.
Sarah Guo
Is this technology they were using before, or is this something you adopted for the Netic platform?
Yeah, I think so. They were always interested in how to serve their customers better, but they had to figure out how to do that. Do we get this data somewhere else? Who looks at it? Do we look at it manually?
Now imagine having one platform. Not only am I assisting with the inbound that's coming from the ads we have to run, but at the same time I'm building context about the neighborhoods that I have to serve and reaching out to bring in net-new revenue. So now they can do it very easily in one platform with Netic. They were already thinking about this additional data and sifting through it with different tools or humans, and then sending door knockers before. And that's just one industry.
We talked a little bit about rollups and being private-equity-owned. Now imagine being a private equity firm and owning maybe 20 or 30 of these businesses in different industries. If those are on Netic, what you can do is—well, if you're going to go after someone for a wellness offering, and I have a dog that I love, and if I'm going to be a member in a wellness offering, I would very much like to pick the one that has pet care.
If you know that about me, 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.
Sarah Guo
How well do you—or how do you—view private equity firms as responding to this wave of AI? I think there are varying opinions, everything from people who are really leaning in and trying new things, and in some cases having to deploy it in companies. They're working with folks like Brainco or other companies. In other cases, they're slower to move on it. What's your perception of how private equity is interacting with AI?
I think the private equity playbook has already changed. Before, it used to be, “We're going to find a gem that has an amazing multiple, and we're going to change the team, create the value, and then sell it again.” But those gems don't really exist anymore as undiscovered assets. So, generally, I think the playbook has changed to: how do we create tangible value with the businesses that we're working with?
I think you're right that some are leaning in maybe a bit too much, without trying everything as if it's software. Any product I use in AI—it's not like the first week should be how you look at the platform. It should be the beginning of the relationship. If anything, you want to make sure those results exist throughout the year and keep getting better, not getting worse.
So I think it's important to shift the focus when testing AI and separate vaporware from true ROI. How do you do that? I think a lot of them can be more software-oriented and deterministic at times, but why can I not try that in a week and tell?
Many, I think, do understand. With these new roles that private equity companies hire, there are different operating partners in AI, or they'll have a few engineers who might be AI-forward, and they'll educate themselves as well. In our job, I always see the same thing in the company: it's about what we can 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 a live deployment, right? If it’s working and I have it, why can’t I just show you what this customer is making? We’ve made, so far, I think over $600 million for our customers that has been generated from AI-handled interactions.
Show that. How does it work? How are real-world customers interacting with this technology? Once you do that, they also get educated and can guide their companies. Still, it doesn’t take away the notion that you have to have a direct relationship with the company, because private equity is more about guidance for the companies they own. There aren’t many times where you can just shove things down the throats of the companies, but you can be a good counselor and a good adviser on what to check for.
Sarah Guo
Yeah, it seems like a lot of private equity shops, as well, have shifted from the ’80s style—come in, do big layoffs, take apart a conglomerate—to much more of your point: How do you optimize value or increase the value of something?
I will say, though, that the first conversations are still always 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 how you’re going to make net-new revenue. That is new. You have to actually start that conversation. You have to show them tangible examples, because otherwise it still focuses on, “How do we get to the bottom line and cut some costs?” But they have to almost expand their horizon on thinking about what else is possible with AI. It would be pretty sad if we used AI only for cost-cutting.
Sarah Guo
Yeah. Yeah. Yeah. Sure. What, outside of what Netic is doing, are you most excited about in terms of the future of AI?
I’m really excited about my personal story. When I didn’t have access to anything, one of the technologies that helped me was finding 1 or 2 people who had graduated from my high school to read some of my essays or look at my work and give feedback. I would Facebook Messenger them, and it was just being able to talk when they were in the U.S. at colleges and I was in Turkey. It was pretty crazy.
I’ll give the answer of education, because I think it will change so many lives of people who otherwise would not even think this world exists. I’m personally really excited about that, and no one will be limited anymore. Everything you want to learn and everything you want to do is in your pocket, right? We made the world a lot more about agency, which I’m excited about, and I cannot wait to see that unfold.
Sarah Guo
Yeah, it’s very exciting. I think one big lesson for me is that you can just go do stuff. You don’t need permission, you don’t need to learn everything—you can just go do things.
But you know, that makes it also a little bit scary. When you see people not doing stuff, it’s a little bit of a dystopian version of it, because in any era or technology you live with, you can always do stuff. It stays with the choice you have to make. We keep making it easier and easier to make that choice, but still, I guarantee you the majority of the world will not be making that choice. It’s something to think about a little bit more negatively.
I’m happy that at least we’re taking away the resourcing as a question—whether you have access to something or not. The second thing I’m really excited about is that, in America and generally right now, the mainstream conversation about AI is very negative.
With the use cases I’m working on, it’s many times people’s worst day in their lives, and they really need help. How do we make sure that they get help? Or in education, or being able to look at your health records and really understand them? I was recently using the health feature and trying to understand how I could sleep better, and there’s no answer. It’s, “You’ve got to stop being a founder.”
But I think there are a lot more positive ways that we are going to start talking about AI. People’s first interaction with AI won’t only be about why X, Y, and Z is going away or jobs are going away, but about the positive impact of AI. That’s what I’m more excited about in terms of the conversation in the world.
Sarah Guo
Amazing. Thank you so much for joining us today, Melisa. It was a pleasure.
Thank you for having me.