The Achieve Podcast - Vishwa Karthik (Catenate)

Welcome to the Achieve Podcast, the show where we highlight the leaders, creators, and entrepreneurs who are building meaningful businesses and shaping their industries. My name is Jesse Warner and I'll be your host today. We're excited to have Vishwa Karthik, CEO of Katni, on the call with us today, the podcast. Vishwa, welcome! We're so glad to have you.

Thank you so much for having me, Jesse. Appreciate the opportunity to talk to you.

So our audience can get to know you a little bit better, give us a quick backstory of your business and what do you do, how to get started.

Yeah, I've been, uh, so my journey was pretty interesting. So I've been predominantly been in the data space for about, I want to say, 30 years or so. Been an entrepreneur for about 22 years. I sold my previous company, which is a health analytics company, providing care management and giving the ability for people to reduce the cost of care. So that company I sold in 2021. That was my entrepreneurial journey, which I started with two of my friends, Jeff and Jamie, in 2006. Then, um, interestingly, my biggest passion was about trying to solve the impending crisis of work and employability. So the impending crisis of work and employability has, uh, with the advent of AI— I've been in the data space for too long, right? And given that, I know that there is a lot of people who are going to lose jobs. There's about 100 million people who are going to lose jobs. That's the bad news. But the real good news is there's 146 million new jobs that are going to be created. Question was Can 100 million people who lose the jobs be able to get the 146 million new jobs? That answer is a no unless they skill themselves up to get to where they need to. So what we ended up doing in 2021, in the early years of AI, was we created a gamified platform which helps people understand themselves, know 84 different soft skills. And in the age of AI, it's not about whether you know how to do your programming or Python or whatever, people are going to be hired based on their soft skills and their ability to work on all of those, right? So given that, we give everybody a chance to understand themselves and every business a chance to understand the entire cohort of people and give everybody an upskill pathway to learn and get better so that they can find the best jobs of the future and not worry about what they had in the past. That's what we built. The product is called Maya Maya, and this is something that we built over the last 4 years. We got the patent already granted by the USPTO as of January 2025. So we are in market and now happy to be able to help a lot of people in education sector and in businesses today.

Well, congratulations first on the sale of your first company. I'm sure that's a whole other story and journey. Um, the— and then congratulations on kind of growing your business. What does your team look like today? How big is your company?

So today we are about like 17 people, give or take. Uh, but the way that we have organized ourselves, the data engineering and the data management team stays, uh, uh, uh, are offshore, but the entire data science, all of the key intellectual property of what we create is all based out of the US. That's kind of what we have done. So the team is about 17 strong across the globe.

Wonderful. Tell me how your business has changed as it's grown.

It's a great question. So we were trying to solve the problem from initially an education perspective rather than try to take this as a career perspective, right? We started seeing we wanted to just go and fix the problem upstream, as they call it, right? If you fix the problem upstream in education, automatically the river flows is kind of where we were going. The good news is we really solved the problem. The bad news is, hate to say it, nobody cares. Everybody cares about employability and earning more than they care about just what they are learning. Right? So earn matters a lot more than learn is something that we actually found it the hard way in 2004. So that's when we pivoted from the learn strategy to the earn strategy and give everybody a chance at career and changed what our product offers to market and brought that to life. That's kind of what we did significantly from a change standpoint.

Yeah, those can be painful lessons as well, right? You put a lot of energy and money and time into it to have to pivot. To what the market wants, right?

Correct. It does cost a lot of money. It does cost a lot of time, energy, and it makes you think, rethink, and it makes you wonder if you are in the right space or not. Question is, do you have the persistence to stay through this or do you want to just fold shop and leave? Right. We were— we just persisted and now we are all the better for it.

So obviously you've pivoted, uh, significantly from your original hypothesis, or maybe not significantly, but refined who your market was. Talk to me a little bit about your sales and marketing, your outreach. What's working for you? Where are you getting traction? And what's not working?

Great question. So I look at it as the drivers and the barriers, right? So the drivers that we are really seeing as to who needs to change and what are the barriers for change, right? It's kind of how we look at the market in its entirety. Who really needs to change are the knowledge workers, right? The companies that have knowledge workers and people who are seriously employing high-value talent. Now, that high-value talent with all of the AI and everything growing around it, The value of the high-value talent, because of what they used to do, say, in a consulting company and others, now those have become slightly less valuable than what it used to be in the past. The white collars, right? So this is a slightly different change in the— from the past. Usually it used to start from the bottom up from the pyramid. This time it's starting from the middle out. What I mean by that is The white-collar jobs is where it's starting from, right? So the idea behind what we wanted to do was go after the market, which is about knowledge workers. And we restricted ourselves to the kind of knowledge workers— knowledge workers are everywhere. But the idea behind is where is it that they would invest money in changing and where they need to change. Uh, we nailed down into 3 major sectors. Sector number 1 is, uh, technology, tech, IT consulting, and all of those specific ones where there is technology users who are getting paid a lot of money, and those many resources may not be required in the future. How are you going to get them to retrain into the new tools of the future and get them to go where they need to go? That's why. So that is one sector. Second sector is healthcare. Where a lot of data exists and they really don't know how best to put the right kind of people where the doctors are the ones, so their time is what actually makes them money, right? Where the value of the individual or their skill is what pays. So healthcare is the second sector that we are focusing on. The most interesting sector is actually education sector. The product that they actually deliver to market is actually knowledge workers. So for them, it was important for them to make sure that they are sending out people for a education sector in particular. Their job is to make sure that employability is higher of all of their students. That's what they focus on. So those are the 3 major sectors that we are going after, and there is a 4th that we do go after, which is staffing industry, industries where they are in a position to actually hire the right kind of people for the right value, for the right position at the right time. That's kind of what we want.

Obviously, we've talked about AI and the impact of AI in the market and in the world. There's a lot of buzz around it today— AI, automation, Gentic, you know, all the words that come out around that. When you look at your own company, how are you using AI in your business to help you grow?

It's actually— that's all we have used, right? Otherwise, we behave like a 60-people shop, but we are no more than like 10 to 12 people at any point in time, give or take, right? And for 17 people with like some part-time workers coming in and going out, if you look at what we have done In my past, I used to have a marketing department, a sales department, an operations department, an offering or a product department, and I used to have finance and accounting department with HR, right? These used to be the pillars of how we used to work. If you look at the slice of information that I am really not having to deal with, what used to be a 3-people department between marketing and a little bit of go-to-market for the top of the funnel sales is now 0.2 FTEs, right? And the middle and the lower end of the funnel, which is the sales department, where I used to hire people to be able to be the prospectors for us, are the people that I really don't need anymore because I'm getting qualified prospects, which is the pipeline fill-out that I'm already getting. So effectively between sales and marketing and the go-to-market strategy, what used to be, or traditionally been, a 4 to 5 FTE team is now a 1.5 to 2 FTE team, right? Automatically I've got that automation covered, which actually takes care of all of it. And all this can be done only if there is heavy automation possible. Second piece of it is product. Product strategy-wise, within the product, because we are an AI company, we drink our own Kool-Aid a little bit, right? So which means that we do end up using a lot of AI within the product, which actually makes it super easy. And our user experience and experience management within the product is also through AI. Third piece of the puzzle is around operations. We have made the entire Agentic framework so easy for us. Our operations team, which would have taken a lot of people for us to deliver— given, I agree to the fact that we are not a services company. As a product company, I don't need as deep in operations as it is for a services company. But still, we were able to trim down the operations. My operations team is not big at all. If any, 0.2 to 0.3 FTE. Is where that goes in. The key place where we have less than 1 FTE for even finance, it's just the product development piece is where we spend the most money so that we can build the data science to where we need to go. So we are able to take the money and use it efficiently. Let's put it that way.

Well, congratulations on using AI efficiently. You know, I totally agree with your idea, which is saying you get somebody experienced, knows what they're doing, You give them the right AI tools, half a person, you know, fractional person, or one person can do the work of a team of what used to take 4 or 5 people to do, right?

Correct. Correct.

So, you know, as you've tried to scale, what are some of the constraints that are showing up? Time, people, systems, capital, leadership, like where are you seeing the constraints?

The biggest constraint that I'm seeing right now is capital, because the speed at which we can grow and the speed at which we are growing can actually be managed. The good news is we did identify it about 2 months ago. The better news is now we are actively seeking capital from outside, right? Which means that we are probably like 2 months or 3 months away from getting capital, uh, infused into the organization. That's the biggest constraint, and that gives us an opportunity to address a market because we are a human capital market and we are not limited by the vertical. I used to own a healthcare company, which is a very verticalized segment, right? So because we are a horizontal, which is about human capital, we can go to many markets at the same time and see which market actually moves. So our idea is to use the capital to find what other adjacencies and markets are the ones that we need to go after with much better efficiency. That's kind of where we want to go.

As you look at the next stage of growth, what are you most excited about?

What am I excited about is the product-market fit having been established for our product already, the product maturity as to where we are right now. From the growth standpoint, what am I super excited about is the ability to acquire new customers, cost of customer acquisition, as we call that, right? Customer acquisition cost. I am excited about the fact that that— how that is expected to go down with the program that we are building right now, right? And how with the product maturity The lifetime value of our customers are also increasing or expected to increase and provide more sticky framework. It's kind of what we're doing.

So you're excited because it feels like you got some product-market fit, and it sounds like you're figuring out a go-to-market strategy that keeps those costs low. So now you're saying, hey, just give me some money, let me run at it. When you look back at your journey, the wins, the mistakes, what are some of the lessons that stand out to you?

The wins or the mistakes? I would—

both. Yeah, what are— talk to me about your journey and some of the things like, oh man, I learned a lesson with that.

Oh, I learned a lesson. I think I kind of called out one of them, right? I thought people cared about education. Nobody cares, right? Everybody cares about a job. They look at education as a stepping stone to a job more than education by itself, which is a very different way of looking at the world, right? So that's perfectly fine, right? And with the advent of AI, they just came and threw a whole bunch of catalysts into it, right? They just made it all about jobs. Microlearning is becoming more and for it, right? Then actually having to learn foundational, foundational learning in universities and 4-year degrees are going to be a tough sell. It's hard for me to think, and as a parent, you're thinking, what am I trying to do by spending $100,000 on a student's education or $200,000 in a student's education? What am I getting in return? What's my ROI here, right? So certainly that was the biggest mistake, which was about expecting people to spend money in advance with the promise of delivery 2 years later. We are in the world of Instagram where the dopamine hit matters, right? Certainly people want to fix the mistake today and try to see how I can get a job tomorrow. More. That's the big thing that we learned, right? And second thing which we realized was, uh, people say all the right things about emotional quotient and soft skills, which is what the key component of growth is going to be. But what are they willing to do about it? They all say the right things. Are they willing to invest in it to make it work? Until now, there were not enough studies given or provided to help them make that transition. So that's another thing that kind of recently helped. The third thing that really helped, right, was until 2024 or so, we were selling AI as a concept, right? Good for us that ChatGPT and all of this came, because suddenly it became a stream of life. Until then, we were just trying to climb uphill, and the education cost of every customer was on us, on the usage. Now, luckily, they have taken the cost of knowledge and education away from us, because people are not questioning asking whether AI is useful or not anymore. They're just saying, is this useful for this purpose? Much simpler for us to handle than otherwise. Those are the key things. Yeah.

Last question here: any final thoughts or advice that you give to other entrepreneurs who are on a similar journey to you?

Great question. Uh, I have a 20-year-old, uh, who's graduating sometime soon as well. So I would give the same advice to anybody. There is— this is going to be the biggest boom time for entrepreneurs. There will never be any company which is more than 500 people in another 3 years from now. The days of the large, big behemoth organizations are over. Every company will live and die within 10 years' time frame. And the size of the company will not exceed— even their best will not exceed— which means that continuous learning and continuous improvement is going to be the name of the game. Which means that consistently creative thinking and building that capability to build a newer and better and better things as you grow further is going to be the key. So don't make— what do I want to be 30 years from now? Make a plan for what do you want to be 5 years from now, and then 10 years from now, because that's all we have control over anymore.

The world is shifting fast beneath us, right?

Yeah, yeah, yeah. I mean, to be fair to the younger generation, they're having to deal with a lot more than we ever happy, or I am happy in my age. So the speed at which it changes is pretty substantial, and they don't have the time to correct their mistakes. We had.

Well, Vishal, I really appreciated the conversation. Your stories definitely resonates with me. I'm seeing similar shifts in the market. Uh, I think you've given us some great insights here. For those listening, if you wanna learn more about what Vishwa is doing, you can visit his website, catenate.io. And that'll wrap up today's episode of the Achieve Podcast. Uh, a big thanks to our sponsor Achieve Fractional, which provides fractional executives for growing businesses. And if you enjoyed today's conversation, follow the show, share with another entrepreneur who'd also find value in it. And again, thanks for listening. We'll see you on the next episode of the Achieve Podcast. Vishwa, thank you for joining me today.

Thank you so much, and please visit mayamayo.ai and find for yourself where you are at as well. So that's the product. You can see where you really sit and define a journey for yourself as an entrepreneur. Perfect, thank you.