Why Even With Great Products AI Startups Lose with 3x Founder Mahesh Ram, ex-Zoom AI

What does a founder learn from watching the CEO of a 32 billion dollar company make his biggest AI bets from the inside?

Mahesh Ram has built and sold three companies. Thomson Reuters acquired his first, GlobalEnglish went to Pearson after teaching English to more than ten million people at companies like IBM and HP, and Solvvy, one of the first conversational AI companies, was bought by Zoom in 2022. He then spent two and a half years heading AI products at Zoom, sitting beside founder Eric Yuan as the company raced Microsoft into the AI era.

In this conversation, Mahesh takes apart the three decisions that put Zoom ahead. Eric refused to charge for AI Companion because he believed everyone in the world should have AI, he publicly promised to never train models on customer data; and he built a model-agnostic layer instead of betting the company on any single lab. Zoom shipped weeks before Microsoft Copilot. Mahesh also shares the operating habits that made it possible, from the five-part rule Eric demands on every decision to the radical transparency that turned his own team into owners.

He is just as direct about the question every founder now asks: whether OpenAI or Anthropic will simply take their market. He answers that the model companies cannot see the hundreds of custom applications running quietly inside every enterprise, so the durable business is the one that owns the messy, multi-party workflows they will never touch. On the wider fear that AI will kill SaaS, he thinks the shift is real but that Silicon Valley badly overestimates how fast it arrives, which leaves a huge opening for founders willing to go out and become the educators their market trusts.

He closes on what he has learned selling three companies, why the best ones are bought and never sold, and the community of Indian origin founders he now runs that grew from three hundred people to more than two thousand in a single year.

If you are excited about building enduring AI and software companies, this episode is for you.

00:00 - Trailer
01:27 - The three time founder who keeps destroying complexity
03:08 - Two billion people learning English with no teacher
04:45 - Building conversational AI before anyone knew what AI was
07:21 - How Zoom came to acquire Solvvy
11:08 - Working with Eric Yuan, a true force of nature
13:43 - The three bold AI bets that beat Microsoft to market
15:09 - Why Eric made Zoom's AI free and refused to touch your data
17:29 - The five part rule Eric demands on every decision
21:25 - Radical transparency: share everything except one thing
23:32 - What Mahesh would build differently today
29:05 - The moat question: how do you survive OpenAI and Anthropic
35:33 - What Claude and OpenAI can never see inside a company
41:01 - Will AI kill SaaS? And why Silicon Valley is too early
42:25 - Become the educator: the biggest opening for founders
45:39 - The Indian founder community that 10x'd in a year
52:43 - Where the founder DNA actually came from
1:00:42 - Why he has no regrets building Solvvy too early
1:01:57 - What actually gets a startup acquired
1:05:14 - Why you keep the acquisition circle very tight
1:07:47 - The real job in enterprise sales: get your buyer promoted
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This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.

Transcript

SPEAKER_01 0:00

99.9% of the world does not know what AgenTic AI is. Recently came back from a trip, you know, internationally went to Vietnam and was talking to people that they're not thinking about Agentic AI. I don't even know what it is. You know, the third company solved that was a quite bad boom. We were one of the first conversational AI companies. You know, I think Zoom had already signaled its intention to get into the customer experience and contact center space. Tell us about working with Eric Young. I wish I had worked for him 15, 20 years ago. Eric is a true force of nature as a founder. You would not believe that the CEO of a $32 billion market cap company agonizes about whether it takes four clicks to get to a feature that he thinks you'd only need two. The one lesson that I want to leave with founders is power of radical transparency inside the business. And so what we've said was we will share everything with the employees except what somebody else makes.

SPEAKER_00 0:50

You said that technology, unless you're a foundation model, cannot be the mode. If you have to summarize modes for the founder listening, how do they build those modes then? So I think that. Hi, this is Siddhartha Alwaliya. Welcome to the Neon Show. I'm your host and managing partner for Neon Fund, a fund that has invested in some of the best enterprise AI companies that started from India and building globally, like Atomic Works, Spot Draft, CloudSec. Today I have with me Mahesh Ram. He's been a three times founder, sold all three companies to Fortune 500 companies. Mahesh, welcome to the Neon Show. Thank you.

SPEAKER_01 1:26

It's a real pleasure to be on the show. I've been watching episodes of the show, and I thought I have to join this party.

SPEAKER_00 1:32

It sounds like a good party to join. Thank you so much. And uh Mahesh, the special thing about you is uh right, you you have lived and breathed by ethos of you know that you want to give solve complexity for people uh and give them back their time. And you have done it across many different uh you know use cases, be it customer service, be it education, tax, legal, like across, you know. So where does this ethos come from that you have lived your entire entire life?

SPEAKER_01 2:03

I think it's um as as most things for as with most founders, I think comes from personal frustration. You know, in the in the legal and tax space, you know, the idea that uh before we built the expert systems, it used to take weeks for a company to incorporate itself and qualify to do business in all the 50 states in the US. And there was, and a lot of it was people having to go to the state offices, do filings, multiple forms, each of the states had their own forms, and it just seemed incomprehensible to me that that you would need dozens of people and weeks of time to do this, when in fact the information was highly repetitive. Of course, it varied by case to case. So that that frustration, I think, with seeing how things were done, and then when you actually dig in and understand why it's being done, there was actually no logical reason why that complexity existed, except that technology hadn't caught up to being a solution. So once you see the technology coming and you see the complexity inherent, I think you have a tremendous opportunity to do that. In other cases, the complexity is extraneous. And by let me give you an example. Today, as we speak, somewhere between one and a half to two billion people on the world are trying to learn or improve their English.

SPEAKER_02 3:17

Yeah.

SPEAKER_01 3:17

How many of them have access to a native English speaker, teacher? Well, when we when we did Global English to the company, the second company, um, we realized that we would never fix the problem that somebody's going to get a live teacher when they need it in China, Brazil. And we realized that global companies had hundreds of thousands, if not millions, of employees in that situation. And they were sending people to local language schools and so on. So there's an inherent problem there. And but language learning is difficult, it's complex, it takes a long time. So we thought, why don't we simplify this by having everything you know on you know on the internet, available, highly diagnosed, you know, prescriptive, diagnostic, and actually compress the time because most of the time was being spent saying I have to schedule a class next Friday, I have to travel. All of that could be reduced. People could study every day, 15 minutes, 20 minutes, 30 minutes. So I think when you see those opportunities, you see, but that is only possible because we had the internet, we had voice, we had the ability to do detection, we built ASR early on before Siri, um, you know, to understand language learning. So these the technology catches up. And then similarly with AI, you know, when we built one of the first conversational AI companies, it was because the technology caught up to the problem. So that's that's kind of what I think has been most exciting about about you know destroying complexity and simplifying and giving people back time.

SPEAKER_00 4:43

So in in your journey, you know, in your third company, Solvi, that was acquired by Zoom. So you started in 2015, the company got acquired in 2022. You were one of the first conversational AI companies, and you were used by large companies like Amazon and many other Fortune 500, uh, right? So, what was uh, if you can go deep, what was the ethos of starting this company?

SPEAKER_01 5:05

So I think I think the the genesis of the story is that I I was introduced by a common investor friend uh to the two PhD co-founders that I had at Salvi who had just finished their PhD at Carnegie Mellon in machine learning, robotics, AI. This is long before anybody was talking about AI, nobody knew what it was. And they had come up with uh an approach in the academic, uh in their academic careers that was doing question answering. So it could look at a huge corpus of unstructured text and you could ask a question, a natural language question, and it would actually extract the right answer as opposed to keyword search, which was all in vogue at the time with Google, it would actually extract the answer. So if you had a 15-page PDF about a lawnmower as an example, and you asked, How do I fix the back rotor of the lawnmower? It would actually find the exact answer to that question in the corpus automatically. So we so I when I saw the technology, I said, This is this is amazing, but we're probably not going to succeed against Google in the consumer space. But having been a CEO and realizing how many times our customers asked repetitive questions and customer support, I thought, why don't we just take all this available knowledge that companies have about their products and services and build something that can actually answer the L1, L2 type of questions very rapidly, instantaneously, using this technology that no one else had. And how do we put this in front of, you know, the brands can put this in front of between them and the consumer and have a great experience. And so a lot of it was about designing the experience, not the technology. We had the technology, but it was about designing that experience to make it successful for the brand and also for the user. Because if a user is unhappy, the brand gets a bad reputation. If the brand is not getting self-service rates that are valuable, they're not going to buy. So we really thought about design and how do we architect this. But that was the impetus is you know, using this new technology, AI and machine learning, which we had to build all of most of it ourselves, um, to be able to solve a problem that's been around for centuries, probably or decades at least, which is repetitive questions that slow a business down.

SPEAKER_00 7:18

And what is it for Zoom that acquired that they made the acquisition offer?

SPEAKER_01 7:23

So I think um, you know, I think Zoom had had already signaled its intention to get into the customer experience and contact center space. Um, some months before we were uh acquired, they had made a bid for 5.9 that that didn't happen, uh, public company. And so it was clear after that that that Eric, Yoan, and and the Zoom um leadership was committed to building their own native solution for Contact Center. Okay. And they saw that as a as a as a space that Zoom should be in. Naturally, Zoom has many assets that lend themselves perfectly to that space. And so I think we had earlier done a proof of concept with Zoom as a potential customer. And so they had dug in deep with us and asked us lots of questions, and we had done a POC, and I thought, but it then they went silent and we thought maybe we didn't do something right. We were quite sure we had done a good job. So some months later, when we were in the cusp of raising a Series B, we were looking, we asked Zoom and a couple of others potential strategic investors if they would like to participate in the round. And things happened very fast, as often happens, and we were not looking to be acquired. Uh, and Zoom said we would like you to join the company, we'd like to add you know this capability and really build out this contact center vision that we have. And one thing led to the other, and you know, we were resistant at first and then got more interesting because we thought the idea of bringing this at scale to the world was interesting. And today that product is now relabeled as Zoom Virtual Agent. It's part of the contact center business, which is one of the fastest growing lines of business at Zoom. Most people know meetings and Zoom phone, but contact center is actually growing very, very rapidly. Can you tell us more about that business, like that you helped build? Yeah, so uh so the the the my journey at Zoom has two different components. Um, the first component is you know, replatforming Solvi, our company, into Zoom Virtual Agent, becomes part of the contact center suite. The contact center suite has agent-facing solutions, the self-service solutions, which is Zoom Virtual Agent, it has workforce management, forecasting, scheduling agents, when does it be, and it has uh quality management. How do you manage proposals? They're selling to call centers. That's yes. And so well, they're selling to big brands. So a good example would be Major League Baseball, okay, you know, which uses Zoom Contact Center. And they also do replay with Zoom. If you see the video replay, it's powered by Zoom. So the actual contact center, all the ticketing, um, all of that, customer service is all powered by Zoom Contact Center. So that's one business that Zoom was building. So we were building that. When I joined, it hadn't yet launched. We were not GA. We had other, we joined other teams that were building other components and we released the product. But about eight months into uh post-tacquisition by Zoom, or six months after Chat GPT and OpenAI, OpenAI releases Chat GPT. And so we, Eric was very ahead of his time. And so he realized that he needed to um to be, I mean, he was already well aware of what is going on in AI and he knew something was happening. But he also knew that his biggest competitor, Microsoft, was deep in partnership with OpenAI. So he said, we have to be great at this in order to win. And so he asked me to essentially take over the head of AI product at Zoom, independent of the contact center, more focusing on the core business of meetings, phone, the collaboration side of it. So really two different journeys and continue to do that. And then I also managed the third business for at Zoom, which was the Gong competitor, so uh Zoom Revenue Accelerator, which was a smaller business. So, but the AI was for a lot of my time was my main focus, was building the AI product client.

SPEAKER_00 11:03

And uh tell us about working with Eric Yohan, right? He's an immigrant founder, built one of the most legendary companies of our era. Uh right, what was it like working with him for two and a half years?

SPEAKER_01 11:16

You know, the the thing I tell tell founders, uh tell everyone I know is that I wish I had worked for him 15, 20 years ago. Yeah I would have avoided some mistakes and done things differently. Uh Eric is uh is a true force of nature as a founder. Um he is uh able to, I think first and the most important thing that founders can learn from Eric is how incredibly focused he is on usability and user experience. To the extent that you would not believe that the CEO of a $32 billion market cap company agonizes about whether it takes four mouse clicks, four clicks to get to a feature that he thinks should only need two, or that the settings on the things are too difficult for someone to find. And if someone writes in with a legitimate complaint, Eric will not only read it, he'll make sure it gets acted on, that it gets fixed, and that it's communicated back. I'm talking about an everyday user. You could write in, and if you tagged Eric, he would ask someone to investigate and fix it. Yeah, he probably, you know, I don't know how he does it, but it's but it goes back to his more the core principle, which is his belief is and why he built Zoom. He built Zoom because he was a lead architect at WebEx and he believed that it was too complicated. And there were how many meeting platforms were there when Eric built Zoom? So many. Skype and GoToMeeting and WebEx. But he said, no, you know, this is all not good enough. You know, it's not easy to use. I can't just turn it on. And the famous phrase about Zoom is the three words, it just works. You open up your machine, you know that it's going to work. Whereas Google Meet, Microsoft Teams all had lots of challenges. When you opened the thing, it didn't always work the way you expected. So that all comes down to Eric. And so his intense focus on user experience and usability. And I it's very difficult for founders to maintain that focus. He's doing it all these years later, a $30 billion company. So it is possible. And I think if you don't do that, then you run the risk of thinking that your business is in the right place and losing the market. Um, so that's number one. Number two is his his ability to predict um the future, and we'll, I'm sure we'll talk about it more about the decisions he made with AI, is is remarkably good. He is very plugged in, he's reading all the what's going on, he has a good sense of what's coming next. And he's able to take very because he's a founder, yeah, and because he built this in his own vision, he's able to take bold decisions that would scare most public company CEOs because he has conviction. Can you share top three decisions that you know? Yeah. So I'll give you the best ones. I think, you know, at when we were building AI Companion, we were in a race. We wanted to beat Microsoft to market, and we did beat, we did beat Copilot to market by a couple of weeks. And about a month and a half before our launch, we we we had basically we were at that time most of the market that was adopting early AI solutions, this is 2023, was using customer data to train models. Um, they were using a single model like OpenAI or Anthropic or Lama. Um, and they were um they had very loose, I would say, security and governance. So one day, about a month and a half before our launch, we had built with the idea that we were gonna use customer data to train the model and that we were gonna charge for AI Companion. So imagine that we built everything for months and months at not sleeping, teams are awake all night building. And about a month before the launch, Eric called a few couple of us into the office and said, I've made some decisions. And said, What are the decisions? He said, number one, we're not gonna charge for AI companion. I said, What? You know, we're gonna monetize this, it's gonna cost us money. It we're gonna be underwater, margin-wise, you know. And he said, no. He said, all these things will commoditize, the model costs will commoditize. It's our job to make it affordable. Everybody in the world should have AI. We're gonna make it possible. That was a big, bold decision. Okay, number one. Number two, he said, I want to make a statement that we will never use customer data to train our AI models. Nobody was doing this in 2023, not even Microsoft. Microsoft was using chat data to train the model. And we said, Eric, please don't do that. You know, we'll slow down our ability to be accurate, you know, accuracy. And he said, Okay, I'll think about it. The next morning he posted on LinkedIn and said, we will never use customer data to trail the model. He made the decision. And it turned out to be one of the best decisions we ever made because when enterprises looked at us, they had that confidence of whenever they would say, How do we know that you won't? I said, our CEO has said it publicly on LinkedIn. He can't go back on it. Number two. And number three, he also came up with this idea, which was very unique at the time. He made a decision that he said, we will not be reliant on any single foundation model company. So he said, instead of just being building four open AI, we're going to build a federated AI later, which we talked a lot about, where we can be agnostic and we can actually build a lot of work to do this, build evaluation, judge, judge AI judges, to be able to use any of the best in-class models or our own models in some cases. So when we launched, we were using Lama, Anthropic, and OpenAI for different use cases. It's a lot of work. It's a lot of, it could have been much easier if we just picked one. Yeah. But he said, no, this is going to keep evolving. The world is going to change. And we don't want to be tethered to one player. Along the way, he also made another big brilliant decision. He invested in Anthropic, which of course has turned out to be a very fortuitous thing. So, but these three decisions, you know, the no use of customer data to train the model, um, they built not charging for AI companion, and then doing the federated approach were brilliant. They were far ahead of everybody else in the market. So I think, you know, that kind of bold decision making, I think, is, you know, at the time we many people were arguing with him inside the company. Why are you doing this? We need to monetize. He said, no, I see that this is where we're gonna be.

SPEAKER_00 17:21

So one layer of this decision making, I just want to understand why, so that our founders can know about it, right? One comes from uh caring deeply about customer experience that you already shared. What are some of the other principles that Eric or follows that lead to this kind of decision making?

SPEAKER_01 17:39

So I learned this lesson in the most difficult way. My one of my first presentation to Eric, I came in with a deck and a few slides, and I started to talk to him about a problem in building AI companion. And I went deep into the problem and I was talking about all this stuff, and he could I could feel his impatience. And I could feel that I wasn't it wasn't going well. So basically, and and he was getting frustrated. And nobody else, none of the other executives in the room were saying anything to me about it, and so I didn't understand. And at some point he at the end he just said, he said, Um, I I don't know what to do with this. And so I said, Eric, what do you mean? And he said, I would like you to tell me the problem, the root cause, and the solution. He said, Many people come with a problem. Some people come with a problem and a root cause, why? And and but then don't have a solution. He said, That doesn't that doesn't make good use of my time. He said, the best use of my time is when someone goes deep, truly understands the problem, truly understands the root cause, and actually has a solution to offer. When you have all those things, you come and present to me, you do it in this template, in this format, our meeting will go in 10 minutes we can have a decision. So I said, okay. So I went back and the next meeting, I thought I have it perfectly. And so I went back and I came with a beautiful problem root cause solution. And then I got to the thing is like uh, you know, and uh ownership and who's going to do it. And I had four names. I had owners, you know, for this, this, and this. And I had for dates, I said, you know, subject to scoping. You know, I put something in there, but because I wasn't sure. And he said, okay, you got the first part, right? Problem root cause solution, but you missed owner and date.

SPEAKER_02 19:25

Yeah.

SPEAKER_01 19:25

And he said, when I want ownership, I want a single owner. It doesn't mean the person should do all the work. This is the best lesson for founders. It doesn't mean the person should do all the work. The best employees you have have ownership.

SPEAKER_02 19:36

Yeah.

SPEAKER_01 19:36

Ownership means you are going to drive it to conclusion. And he says, I want your name on it. I don't want five names on it. You can sub, you can subassign and you can give them single ownership of a particular task, but I need you to be the owner. And then he said, dates. He said, I don't even mind if you have a date for a date. If you say in three weeks I will give you the launch date, that's okay. But in three weeks, I better have the date. But these five things, it's easy, the five, the five fingers of one hand, problem, root cause, solution, owner date.

SPEAKER_02 20:05

Yeah.

SPEAKER_01 20:06

And I think this sounds very formulaic. When you think about it, it sounds very formulaic. It sounds like something you read in the book. But when you actually watch it and apply it, and founders, if they use it with their employees, what you'll find is that the behavior becomes predictable and people are following a pattern that they can then use efficiently with each other, right? And so it's like the Amazon memo. It's a concept, right? It's there's nothing magical about the memo, but what the memo does is create a construct that all the employees of a startup, for example, can coalesce around and can get get their work done more efficiently. Stand-ups go better. Big decisions get done in a more methodical fashion. You know why. If you have to go back and you can look at the root, if something fails, you can go back and say, what was the problem, root cause solution? Oh, we got the root cause wrong. Why did we get the root cause wrong? We didn't do enough research. All of these artifacts get created and they actually are valuable if you go back and read them. So I think that is something that, you know, the founder in you thinks you just have to move fast, break things. You know, process is bad, but this isn't really process. This is this is a mental alignment. And so I think I strongly encourage all my all the founders I work with and advise and invest in to adopt principles similar to this. Does that help?

SPEAKER_00 21:25

Yeah, that helps. That helps definitely.

SPEAKER_01 21:27

The one lesson that I want to leave with founders is, and I had to learn this lesson was the power of radical transparency inside the business. I used to until uh maybe a year and a half into Salvi, until then, we used to like guard information. Didn't tell everybody everything. Oh, you know, I don't know, we'll you know, have enough cash, our runway of cash, or you know, when we expect to raise money, or what how we're doing against our milestones for the quarter, you know, all these kinds of numbers. And we kind of came to a a really An epiphany that I want every founder to think about deeply, which is radical transparency actually isn't a risk. It's actually an unburdening of your stress. And so what we said was we will share everything with the employees except what somebody else makes. We didn't go that far. Like there are companies that have even done that. I think that that has too many other risks because you then have to explain why somebody in Detroit is making less than some Bay Area and is doing the same job. You know, it's a waste of time. But that's that's going to very emotional level. Yeah, that's subject. Exactly. It's not objective. But but everything else we said our cash balance, you know, what did we have to do this quarter? Why did we fail? What were the mistakes I made? What were the mistakes our management team made, or what was things? Celebrating the wins, it suddenly became this beautiful experience of thinking that truly all of these people are owners. And so it's very difficult. And I particularly find it that with Indian origin founders and founders from India, that some of them are great at this, and some of them are like just really hoard information and try to keep it. And I tell them all, you will be better off if you adopt radical transparency. You might tune it a little differently for your business than somebody else. That's up to you. But you'll never be harmed. Don't worry that somebody's going to leave and go to your competitor and take that information. By the time information is useful to that competitor, you will have done something else. So I think that's that's one of the biggest stress relievers was adopting that principle.

SPEAKER_00 23:36

And if you were starting today, uh Solvey or any other problem, what would you have done differently?

SPEAKER_01 23:45

Well, obviously, I think the technology framework is completely different. I think the idea of you know automating everything and starting out with you know no manual process. I mean, that's a self-evident, obvious principle. I think you but it requires a radical shift in the way you think about building companies. So I think that is inherently different. Um so everything about that is different, right? Thinking that you need um somebody, I think generalists, uh the ability to hire generalists who can who can harness this technology to do things is better. In the old days, you would have to hire somebody very specific specialists. Today you a generalist can learn a lot of things. So that would be something I would do differently. Um second thing I would do differently is um go much, much I think data collection. I think the you know, it today the ability to capture data is greater than it ever was, but the data that you need to capture is actually quite different. There's been a lot of discussion about context graphs, yeah. And, you know, what is the actual meta workflow that you're intercepting? You know, you're not building up uh an agent to do credit scoring for the mortgage. You're thinking about why does somebody, what's the end-to-end process to get a mortgage? Yeah, right. And how would you reimagine that process? So I think reimagination today of a process is something that we didn't have the luxury of doing before. But in order to do that, you need to understand how mortgages are processed. What is the credit, how does credit figure into the equation? When do people make the decisions to prove somebody with limited credit? Are there regulatory restrictions that do that? These are all like knowledge that you have to ingest and learn. You can learn it much faster because the technology is available. But the best way to do it is actually to sit inside and somehow sit on the shoulder of somebody doing it or to talk to somebody who's an expert. So that's something I would do differently, is I would go much higher up in the meta layer. Why, why, why? The why questions today mean much more because then you can decide how to set up a flywheel to capture the data. As an example, in the mortgage process, years ago, it wouldn't have made any sense to understand why somebody, there are two people with similar credit scores, and one got approved and one didn't. Nobody thought to ask the question of the person making the decision, why did you they they checked a box in a CRM, approved because of you know salary history. But there's something else going on. You know, I met with the person, they're they built two businesses before, there's some context. You can capture that context, but in order to do that, you have to build a system that can capture that context. Maybe it's conversational, intelligence, something that has to feed in. So all those things I would reimagine completely. I would say, what's what's you know, the why? How do they make those decisions and capture that? Um, so those are things I would do. But all of that starts with a deep understanding. I think you've had Sri Sha Ramdas from Lumber on the on the show, and I think he did a brilliant job of this. He doesn't know anything, he didn't know anything about the construction industry when he started, but he he interviewed and talked to lots and lots of people and started to understand the second and third level problems that they were dealing with.

SPEAKER_00 26:53

I think that the problem that he's following is beautiful, that uh the same worker across two different counties will have two different payroll processes. Correct.

SPEAKER_01 27:05

And may have 15 1099s because they've done 15 jobs in the last six months. Yeah. And somebody's issuing us 1099s, he has he or she has to show up at the workplace. I mean, there's all these scheduling. So I think that's that's an example of something that's not a problem you could have solved in the old days of SaaS easily. It's an you know, it's lends itself beautifully to agentic.

SPEAKER_00 27:24

So so that lends itself uh to that the the best of the founders that will start in AIR or I have started, they they don't need to be the most technically savvy founders. They they need to understand the the human aspect very well, then because if if every process is going to get reimagined, yeah, then they need to do those conversations and look beyond the problems that are getting said.

SPEAKER_01 27:50

I think two things are equally true. I think if you don't have a strong technical founder on the team, it's very difficult to build these. Because as you know, pushing these agents into production is far different than building a POC. The non-technical person can build the POC and get it to look good and validate. But when it comes time to actually building something that performs reliably in production, we have all the other things, the harness, the you know, the the validation, the uh evals, everything else that goes governance, identity, uh data governance, etc. But but I think the non-technical founder um can um can do a brilliant job of deeply understanding the domain well enough to actually think about how it could be done differently.

SPEAKER_02 28:39

Yeah.

SPEAKER_01 28:40

Um I think and that's and that's always been true, by the way, right? I think, you know, when you think about Airbnb, or you think about even we work, despite all the controversy, you know, the idea that space is is actually modular and can be, you know, can be thought of differently as an asset. Yeah. And and so, and so what you would then think about is is in this modern context, um it gets harder for founders because it's so much easier to get to V1 of a product. So, how do you actually differentiate? What's the mode that you and I think you have to start with an expectation of how you will build a mode. That actually you didn't need to do that. In the old days, if you got the wedge right, you had enough time to build off the wedge and build something different. Today, I don't, I think even getting the wedge right is not a protection. You have to build the wedge in such a way that actually is a flywheel and it's sustainable, and you're operating in a world where other people don't have access to the same thing, proprietary. And so that is a much bigger challenge today for founders. Um and it's it's not easy to do. But again, that's where the non-technical founder can actually do well, is because they can actually start to understand what is the you know, they can actually think about modes that are not technical. Most of the mode is not going to be technical, unless you're a foundation model company or world model.

SPEAKER_00 30:03

It's not technical. I think where in this era, technical founders, what I'm seeing seeing in the portfolio and the couple of names that I discussed with you have an edge. Uh that technical founders with deep empathy are able to outscore non-technical founders because uh sometimes AI doesn't need to be sold. Where you required a strong business founder or GTM founder, things require to be sold.

unknown 30:31

Yeah.

SPEAKER_01 30:32

Well, it's what we talked about earlier. I think you said it is empathy, which I agree with, which goes back to some of my points about you know following up and doing other things, but it's the idea of the compounding founder. So uh it doesn't matter whether they're technical or not. Do they have the ability to go deep, understand, ask lots of questions, listen, synthesize, and come back with a better understanding of something they didn't know anything about? That's actually completely independent. Now, technical education can often be helpful for that, yeah. It can also be destructive for that. Some people don't cannot think in acceptance straight lines. The big picture they don't think that way. But the best founders can do that. And I don't think it's a barrier for a technical founder to do that. Um it's if anything, it's probably good that they're blind to some of this stuff, they're learning it.

SPEAKER_00 31:23

And and right now uh today, what what are the the best, some of the best founders that you have invested or met that you can name, who you think will build the next Zooms of tomorrow?

SPEAKER_01 31:39

Yeah, I mean I I'm and most of the companies I'm getting involved with a very early stage. So, you know, I think that there's some of the some of the really exciting ones. Um there's a a company uh founded by a founder Ashutosh who goes by MADI, a company called Axiorate. Um, and he he was at Eightfold working at Eightfold as a like a chief of staff type of role, and now he's building a company that's going deep into the CIO's world, the enterprise application layer, and has and he's done a remarkable job of helping CIOs truly understand their business application layer. And they have Fortune 10, Fortune 25 customers sheerly sheer, sheer hustle and and providing value. And I I very bullish on that company. I think I think just because of the way he thinks and the way the team is assembled, I think it's a great team. Um, Deccan AI is another company that's they're more in the in the data AI space, which is a crowded space, but and so you could easily say, you know, there's a lot of players, but yeah, but Rukesh Reddy, the founder there, is is you know, you're betting on the founder there because he truly understands the space, he's thinking all the time. And and and he's not the technical founder, but he's he understands the problem really well and what the pain is for the for the customers. Um there are uh Shamrock AI is another company that's doing uh thinking more deeply about the ERP transformation space, yeah. And has some you know incredibly strong initial traction where the customer is pulling the solution, literally pulling it out of them. And they can't even keep up because the customer is you know a very, very, very important company and they're pulling the problem uh the solution out of them. So these are some examples. Um there are others that are earlier in legal tech and other things that that I believe in, but we'll see.

SPEAKER_00 33:34

Coming back to moat, right? You said that technology, unless you're a foundation model, cannot be the mode. So then what's if you have to summarize modes for the founder listening, how do they build those modes then?

SPEAKER_01 33:48

So I think that any answer I give is likely to be wrong in a year.

SPEAKER_02 33:53

Yeah.

SPEAKER_01 33:54

And you know, you hear a lot of pontification about modes, and and if you go back and read what they said a year ago, they were saying, oh, you build small models, you know, capture the data. You focus on verticals. Focus on verticals, and and then you know, the next day, you know, cloud covert comes out and they have something that attacks that vertical, or they're gonna partner with with some SI and they're gonna build you know a services business around that vertical. So I think we should be careful in not over-generalizing about what a long-term mode is. But I think most founders, if they're smart, will focus on kind of an uh intermediate mode and then build off of that. And yeah, you're probably gonna have to construct a second mode and a third mode. So to me, the intermediate mode is I think three things. One is, you know, in multi-user environments where there's, you know, with these, when you're building these agents, if there's multi-users in a complex workflow, you then have to build an application that does it. The foundation models aren't built for that because they don't really understand persona, they don't have memory, you know, you think they don't have memory of multiple complex and the interdependencies between those. So I actually am seeing founders, some of the better founders I see as actually combining agentic behavior with deterministic behavior, because the interdependencies between eight, nine stakeholders who might be involved in a decision is actually something that most foundation models will do a poor job of repeatably getting right. So if you build some deterministic, some probabilistic, and you put these things together, so multi-party, a complexity where there's different decision junctures in the end-to-end process, and ideally where the data is not visible to the to the foundation model. So a good example would be these CIO applications, right? The uh AxieRate deals with an enterprise customer, they might have a thousand internal applications. Only a hundred of them are common off-the-shelf solutions. You know, there's SAP and Salesforce. The other 900 were custom built by somebody in-house. Nobody has Cloud doesn't see it, OpenAI doesn't see it, but their business runs on it. Could be invoicing, could be payroll, it could be compliance, it could be something else. So if you're and and by the way, those things involve multiple stakeholders, might involve AP and AR and other functions. So now if you build a solution around that, it's going to take a while before somebody's going to build a productized approach to this. Could could Accenture or somebody come in and build that for the one customer? Sure. But they're not productizing well. So your opportunity is to build that and then go to other customers. And now, of course, with services models, you have to open it up for the customer to do their own thing. But but by being first, multi-party, highly complex data that's that's hidden from the outside world, those are three pretty good criteria for a starting point.

SPEAKER_00 36:59

And would you advise the same? Because uh when founders get questions all the time, and I've talked to large funds, billion-dollar funds, even they don't have an answer. What if Claude comes in your portfolio or to a founder? What if Claude just, you know, your vertical or what you do is become the focus area?

SPEAKER_01 37:19

You know, I'll give you an example of a company that I think has durability, and I think uh is a company that I know uh well through the investor, is a company. Uh Cecilia Zaniti is the founder and CEO of a company called GC. GC stands for general counsel. And she comes from the world of legal general counsel, and she's selling software similar to what Harvey does with law firms, they're selling to general counsel. And I think when you get deep into what general counsel care about, the the governance, the identity management, all the privacy, security, the proprietary data, mixing and matching publicly available data with private data, it's gonna be all it's gonna be quite a while before Cloud Cowork solves that problem. Now, could one could could somebody at Uber General Council take all those tools and build something specific to this? Sure. But the one thing we forget in Silicon Valley, which we are too immersed in our own Kool-Aid. We're drinking our own Kool-Aid too. But you go out to the rest of the world, they're not even using AI. I recently came back from a trip, you know, internationally, went to Vietnam and was talking to people there. They're not thinking about agentic AI, they don't even know what it is. So we we realize that like vast proportions of the world are wide open to coming up with a solution that works. If you really understand the pain, you know, Cecilia understands because she comes from that space. So when she goes talks to a GC, she's speaking their language. Chances are somebody at Accenture going to speak to that person or somebody who's working for, you know, if Claude, if Anthropic comes up with an SI, or it's gonna take them a while before they can do that. So by that time, you could be at 100 million, 200 million, 300 million. Does that create an impermanent mode? Of course it doesn't. But you've built a great business. Chances are it's highly valuable.

SPEAKER_00 39:11

That's that's pretty good. And and coming to what you said, highly valuable, in in Silicon Valley today, a founder who has built a hundred million dollar business in 10 years or 200 million dollar revenue business in 10 years, they suddenly are getting questions from everywhere. Is this even valuable? Because the the ceilings have become so high. Uh, even even for that, founder will put and the team will put the investor put all to create that goal. The goalpost has moved by a lot.

SPEAKER_01 39:42

Yeah. I think I think the goalposts have moved, but not as much as sometimes people think. I think if you look at the compounded rate of growth of companies, as opposed to just the ARR number, and you see can are they actually growing, you know, is the compounding rate high? The companies that are doing that are getting funded. Sure, it might take seven meetings with investors before you get a term sheet or 12, but you're going to get a term sheet because momentum, tailwind and momentum, you know, they're not enough, let me say it differently, there are not enough good companies that fit into this category. If we take out all the coding and companies, which is I think a whole different category, and and even if I then also take out CX companies, customer care, which is kind of an easy category for labor displacement, if I look at all the others, there aren't that many companies that are growing at a compound rate, have a customer base of brands that you recognize, and are actually doing something that solves a real problem. There just aren't scarcity principle, and there's so much capital that they're going to get the funding. So then it's just execution. It's not that they're not getting hit by clawed cowork. The questions come from investors, but then but the customer doesn't even know they don't know, they're not gonna harness, they're not gonna take clawed cowork and build something, you know, in in the rest of the US. There's so much market.

SPEAKER_00 41:10

So I I I think it's overstated. And do you then also think that uh the entire re-imagination of software category is overstated because uh Silicon Valley has a narrative that um the software has to become headless now because the agents will start interacting with the software layer. So thereby it's also coming to the conclusion of SASO Clips that old SaaS will probably die.

SPEAKER_01 41:38

I I think we're I think that confuses two very different concepts. I I do think the way in which software is delivered and the value it can create is radically different. And I think anybody who doesn't start out with the premise of a clean sheet of paper and thinking about how the work should be done is probably at a disadvantage. And I think it's so let's start with that principle and say that that Silicon Valley is probably correct that this is the future. Silicon Valley overestimates how fast that future will arrive. So it's up to great founders to take advantage of this and to go out to the hinterlands of the US and Kansas and wherever else is a mid-fly over country as they call it, and and educate. See, this is this is the thing. We live in Silicon Valley, we think everybody's educated about this. The biggest opportunity for founders is to become an educator. Become the person who all the customers look to as the expert. They come to you, they ask questions. We were the experts at Salvi and how to use AI and customer care. People came to me in communities. I never publicized the company. I never I would participate actively in communities like CX support communities, and I would give advice and guidance that had nothing to do with what we were doing. But then, and so eventually customers, our customers were in there too. And so when someone asked a question, hey, you know any good self-service tools? I had 15 customers who would come in and say, actually, you should just use Salvi, it's the best. But it came because I gave freely by educating. And I educated people. I was like, What is what is AI? What does it matter? What is machine learning? How does it actually work? 99.9% of the world does not know what agentic AI is. Become the educator. Teach your market, whether it's a general counsel or a tax accountant or whatever, the small business accountant in Oklahoma does not know what agentic AI is. What an opportunity that is. Are they going to learn that from Claude? They're not going to learn that from Claude. They're going to learn that from you. You become an evangelist, you teach them how to use it and you give them practical examples that go, oh my God, I you telling me I can do this, you can win and win big. So you answered back to your question about SAS apocalypse. I think the challenge is that most companies weren't built with this new paradigm in mind. I'm on the board of a couple of companies. They have great customers, they have great product, but it wasn't built for this new paradigm. Making the shift is proving to be challenging. And it's not clear to me who will and won't make it. There are trillions of dollars of enterprise value locked up in those companies. So there's a lot of incentive to do that. Salesforce is taking the lead by doing the headless thing. Most other companies haven't figured that out and they don't know how they because Salesforce has hasn't figured out how they're going to monetize it. Most of the other companies are so scared of how they're going to monetize it that they don't want to make the announcement. And Salesforce also has a lot of proprietary data, more so than others. So it's not for everybody. So I think SaaS Apocalypse, yeah, I think it's possible. And I think the market's pricing that in. I've probably overstated to some extent because some of those companies will make it, but good luck figuring out which ones will. Do you want to be the one figuring out which ones will make it? No one wants to be the one. Yeah. Whereas I do see, what I do see is interesting is companies like Intercom, where the founder came back in and said, this old model is going to fail. We have a good business, but it's it's not going to be the business of the future, and created Fin AI and has completely reworked the model and has completely come out with a fully agenc approach. And that business is doing well. So it's like two businesses in one. Or in the case of Handshake, which reinvented itself, you know, from a SaaS company to now being an AI for data company, or you know, Turing, where I know you had touring uh Vijay from Turing on. Similar example, right? Started with one idea, but then have more. So I think what's the so if I asked you what's the common element of those companies, it's it's a founder-led thing where they're able to pivot, right? And they're able to see and pivot into something that's uncomfortable. Benny off as a founder. He doesn't care. His legacy is is is safe. He can take chances, he can steer into the problem. That's not easy.

SPEAKER_00 46:01

So you're the executive director for Funda, right? It's a very interesting name. It's a non-profit serving Indian founders in the US. Tell us more about the founding team. How did you build it? And who is it serving and what the purpose?

SPEAKER_01 46:16

So Funda has been one of the most pleasant surprises of my career and life. Uh, Funda is a completely not-for-profit community designed to help Indian origin founders. And that wording is important, Indian origin founders, because it's it's all embracing. Yeah. So it covers a generation of kids like my kids who've grown up here who are, you know, who are still Indian origin but maybe not have a connection to India per se, uh, as well as uh cross-border founders who are coming over to the US, as well as you know, veteran founders uh who are there. And it was started as a kind of an idea with a few serial founders of Indian origin, including Sri Sharamdas, who you know and a few others, and just getting together and thinking, okay, let's get something together and see if there's an interest. And the interest was overwhelming. So I took over as executive director last year after we had many events, and so it's clearly there was a lot of interest, but it has just exploded. I think today we have over 2,000 founders in the community. So I think founders have collectively raised over 3 billion. Um, I think at least a dozen exits in the last few months that I know of. And if I know a dozen, then there must be another 50 that I don't know about. Um, we do events, seven, uh, seven to eight big events a year. Um and we also do have a very, but the most interesting and exciting part of it is the private founder community that we have, where people are exchanging ideas, sharing best practices, learning from one another. There's an engineering subchannel where people are talking about what's working for them technically, questions about entity formation, commission, sales structures being asked and answered by people. So it's a give and take. Um, we also have created a CXO collective with the top CXOs in Silicon Valley. So 150 years uh came to our event at the consulate last year, Indian consulate in San Francisco, with several hundred more um in that community. These are very senior people at you know, companies from OpenAI to Nvidia to Apple and Adobe. Uh, and but it's all around the idea of helping founders win. So Indian origin founders, what will what can we do to help them with no obligations uh to anyone, uh, and a truly pay it forward model. And if if I had to say the most exciting part of it is that is just how um dedicated the community is 100% voluntary organization. I don't have any staff. We don't have, we just we do everything through volunteers. And we are um, but events happen, big events, you know, we're having an event on June 4th, and I I expect you know 450 to 500 people, you know, and we could easily have a thousand if we had room, uh, all free to everyone, thanks to a generous um sponsorship by by banks, ventures, firms, service providers, private equity, but they're but it's non-transactional. They're there to help the community and support us. And uh so it's been incredibly gratifying to see what we can do. Because for me, the you know, post-founding and post-being at large companies and so on, you know, I thought about what the next chapter is for me. And I kind of set an infinity goal for myself. Uh, the infinity goal that I set for myself is I want to be the single most helpful person in Silicon Valley.

unknown 49:43

Yeah.

SPEAKER_01 49:43

I thought, how do I go about being a single? It won't be by going one-on-one, how many, and I don't have enough bandwidth. So I thought if I can do something that's just bigger and expansive and helps um create a movement that can help everyone, it's a small start. Of course, it'll never, the goal will never be achieved, but the idea is that you you have to try to think of amplifying yourself. Yeah. And Funda is amplifying itself. And so we have, you know, people like Sriesha Sandesh Mawli, who I think you've had on the program, and and others uh who are involved, uh, Nupur Mehta, who is a young founder herself, and she's very involved, and um Anurad Nalapati, who's another founder, who's but they're all volunteering at time. These are busy people. Um, but the satisfaction they get is by seeing this community come together. So it's been incredibly gratifying, I think. Um it's the it's really my four, it's the fourth startup in a way. And I often joke that if Funda was uh was a startup, we would be raising a massively oversubscribed Series B. Because we went from 300 founders a year ago to 2,000 in a year. And um and so that's that's something. So clearly we're delivering value. You know, you know the PMF is there. So uh now we have to amplify with zero marketing spend. Yeah, yeah, with zero marketing spend and no staff. You know, I think we're the one-person startup, I think, or the zero person startup, I think, that everybody keeps talking about. How many events do you have in a year? So we typically are doing seven to eight face-to-face events. Uh, we do two very big events, the one in June and then one in December. We do another big event, which is a CXO collective event, private only to CXOs, what we did last year at the at the consulate. Um, then we do smaller events. We did one on engineering in the age of AI with three great founders last month in May. Um, then we'll do a first gen founder event, which is the the kids who've grown up here, some of them. Um uh, you know, last last year we had uh uh Kashish Gupta from um Hightouch, Arnav Mishra from Das. Um, you know, is and before the other big funding events. Um and so that's an event that we typically do in the fall, September. Um, and then we do smaller events. We did a cybersecurity event with the Indian and Israeli consulates in February, um, where we had um uh the uh Jay Choudhury, the CEO of Z Scalar spoke. So, you know, we end up doing seven, eight events that uh are either topic-based or very large. And all events are in Bay Area? Um, we have a uh a chapter in Texas that they do events, smaller events naturally. Um we have members in Bangalore, and I think we'll end up doing an event in Bangalore this year, I'm sure. Um, but you know, given it's all volunteering, um Bay Area is kind of where the epicenter is. The good news is a lot of people come from India and from other places to come to these events. So it becomes an excuse to come to Bay Area. Yeah, yeah, exactly. Combine it with other things and do it. So we're very pleased um to have that, and the community has been great.

SPEAKER_00 52:46

So peer towards you know the conclusion of the podcast, you can think of last 10-15 minutes. Uh, but would love to learn where did the founder DNA come in you? Like at what point of time you shifted from India to the US, what you did before becoming a founder, and your first, you know, you spoke about the the Solvi journey. What about the other two journeys?

SPEAKER_01 53:06

Yeah, so I'm I'm an unusual case in that I'm a I I'm what I call a 1.5 generation. You know, my parents moved here. My father came here for higher education, and so we moved here when I was still in um in you know, pre-even before high school. So I I you know New York City, grew up in New York, you know, went to high school and public high schools, and and uh but but I'm also the nobody in my family has had been an entrepreneur. Everybody's the expectation was engineer, doctor, lawyer, you know, the the EDL, um, you know, was the LED or whatever. And and that was what I assumed as well. Um I thought, oh, I'll be a doctor, I'll be a lawyer, and and and and I think that the entrepreneurial bug only bit me when I started to build something to you know, like automate the complexity. And so that was for me the the real realization that with software you could actually automate complexity captivated me. Um it actually came before the idea of becoming an entrepreneur. It was more like, oh, this is this is really valuable. You know, you can build something and have produce value. Oh, by the way, you can build a company on this. That's all that came secondarily. So I think that's the genesis of it is just getting excited about things. And one thing I realized early on for myself, and I think most founders would gravitate towards this, is that working for someone else is constraining. That you you don't have that expansiveness uh being able to do what you think. You have that freedom. And so a lot of it is the constraints that that large companies impose on you. Um, you know, when I was a CTO at Thompson Reuters, um you had a lot of other stakeholders and you're worrying about big numbers of employees, a lot of bureaucracy, administration. I hated that. I love zero to one. And so, where do you get opportunity to do zero to one? Rarely do you get that in bigger companies. Zero to one is best when you're actually building. And so, and you're working with people who you get to know and work shoulder to shoulder with. So that has been the attraction, and and so you know being the first in the family to be an entrepreneur was a was a great thing. But um, you know, I had inspiration. You know, I had a grandfather who had a second career after he was 75 and wrote three books after the age of between 75 and 93, and became a well-known um music critic and you know, writing in the Indian Express. So, you know, like I had inspiration, so it just wasn't entrepreneurial inspiration. At what age you started your first company? Um, 20 uh uh 28, 29. Wow. Yeah. It wasn't 20. These days it's 18. So you know, it's like drop out of college.

SPEAKER_00 55:50

I don't think that would have been and that was acquired by Thomson Writers. Yeah. After how many years? Uh that was a fast one, it was like 18 months. Okay. And then you worked at Thomson Writers for how many years? For about a year and a half. Okay. And then you started the second one.

SPEAKER_01 56:05

Yeah, then moved out here to the Bay Area and Global English. They were all built in New York. Yeah, yeah, I was in the East Coast, yes. And then Thompson moved me to Florida. Okay. Um, they did a roll-up, and I was the CTO of the roll-up.

SPEAKER_00 56:17

Understood.

SPEAKER_01 56:18

So yeah. And then moved out here, and then um Global English was the second company. And you picked for five years, Global English? No, no, Global English was a long journey. So my joke is that you know, I I thought it was going to be easy, and you know, it took 11 years.

SPEAKER_00 56:33

Wow.

SPEAKER_01 56:33

Because we were so far ahead of the market. I mean, you started that in 2001 and got acquired in 2012. Yeah, exactly. So it took 11 years. And the company actually was incorporated even earlier than that, where we're doing consumer. And so, you know, the idea was when I joined and to kind of re-redo it around corporate educ English learning.

SPEAKER_00 56:52

And so that was and if you can share what scale do you took each company at and roughly how much funding do we had raised in each company?

SPEAKER_01 57:00

Well, the first one was no, it was all friends and family, and it was you know single-digit million, but we had all of our destiny around hand. With global English, when we exited, we were uh somewhere around 65 million. We had a we had 450 of the global 2000 as customers. So companies like IBM, HP, GSK.

SPEAKER_00 57:16

You're teaching their employees English. Yeah, exactly.

SPEAKER_01 57:18

And focus. I think IBM at one time had 220,000 IBMers using Global English platform. I think we ended up with the last year, we had probably, I think we ended up with well over 10 million people who used our platform to learn English. So it was a pretty powerful concept. Um, and but we also had customers all around the world. So most of what was interesting about global English was the customers, the buyers were often in the US or in Europe, but the users were almost always in developing markets. So we had offices in 22 countries, China, Brazil, India, where the users were actually distributed. So IBM headquarters would make the purchase, but all the users were abroad. So um, and then once we're in Pearson, part of a much larger billion-dollar business unit focused on English language education. I was part of the executive team there, stayed for two years, and then started Solvi. Solvi, we got to, we were very lean. We were we got to eight-digit ARR. Um, we launched a product in 17. We exited obviously early 22. Um, we were, I think, 67 or 68 people when we exited the company. We were super lean. I didn't even have a VP of finance, I didn't have a CFO, didn't have a general counsel. We did all of that through uh the team we had. So built a very strong leadership team that could do many things at once.

SPEAKER_02 58:37

Yes.

SPEAKER_01 58:37

You know, my COO handled legal finance, some marketing board deck strategy. So give I like people who are polymaths and can do, yeah, who can handle multiple things at once. And that's what allowed us to stay lean. And and I think our biggest competitor raised seven times as much as us. We were venture backed with scale, scale ventures. Rory O Drisco was on my board, true ventures had led the earlier round, pair I mentioned earlier. Yeah. So we had great investors, but we but we didn't, but our competitors raised seven, eight times as much. Wow.

SPEAKER_00 59:11

And you were still able to make our dent.

SPEAKER_01 59:13

Yeah, yeah. I mean, and we were we had you know we were equal to them in in revenue and and you know, we were beating them on deals. So that's how you control. I always say this to founders is like, don't think that funding is funding events are not high high signal unless you turn them into high signal. And you control your own destiny a lot better when you are able to do it um without a lot of funding because you don't have as many people to answer to.

SPEAKER_00 59:42

And uh in in the SOLV journey, it was uh uh exceptional that you had more than a billion conversations across all these customers, yeah, like Amazon.

SPEAKER_01 59:54

Yeah. Again, because we did we learned early on that the focus should be on customers that had a lot of volume, which meant they had a lot of agents, which meant they had a lot of repetitive issues, AI is perfect. I mean, I look at what Decagon and Sierra and all these other guys are doing now, and I think uh we saw this coming. We just didn't have the technology foundation of what the foundation models have built. We didn't have Anthropic and OpenAI and others building, but the problem statement hasn't changed.

SPEAKER_00 1:00:23

I imagine that if Zoom wouldn't have given you the offer today, Solvi would have been a nine-digit ARR company.

SPEAKER_01 1:00:30

I think so. I but I think we would have had to replatform. Yeah. Which would not have been easy, but we would have done it because we would have realized we saw what was coming. Um so we would have required a pivot and a redoing. I think what Intercom did, as I said, with with Finn is exactly what we would have had to do, and we would have done it. Yeah. Uh and maybe we would have gone more to the agent side earlier, um, as soon as we saw that, so which we did Zoom did, and we did at Zoom. But you know, I don't hindsight's always 2020. I think I think I don't look at I don't look back. It's like what I love love is that you know we understood the space really well. And it just so happened that the technology wasn't ready. But I think if you deeply understand the problem space and you build a great solution and it has a good outcome, probably you made the customers ready for an uh completely autonomous agent. Yeah, but I don't regret that. You build the right thing for the right time, you know, you can only build what's available. Yes. You know, mobile mobile came along and made you know app economy possible. Yeah. So you know, had you built a great product and that could have been a great app before mobile became ubiquitous, doesn't mean that you weren't a great founder. It just meant your timing wasn't right.

SPEAKER_00 1:01:50

Yeah. And uh, you know, founders usually struggle when during the process of acquisition, many LOIs get dropped. What are some of your learnings? Because now you have done it three times back to back. How to take an LOI to a successful conclusion, which is win-win for everyone. And first is how to even get an LOI.

SPEAKER_01 1:02:08

Yeah, I I think I think first of all, anytime I meet a founder, she says, Yeah, you know, we starts talking in a early conversation about potential acquirers. I tune out.

SPEAKER_02 1:02:16

Yeah.

SPEAKER_01 1:02:17

I I think you know, the old thing is so true. The single biggest thing is companies are bought, not sold. Yeah. And if you start out with the idea that you're going to get acquired, it's a bad idea.

SPEAKER_02 1:02:30

Yeah.

SPEAKER_01 1:02:31

You just can't build for that. First of all, you'll end up building a bad company that nobody wants to acquire. Uh so I think the biggest thing is be known in your ecosystem, know who else is in your ecosystem, build relationships and partnerships so that at the time, if you are in a process or something, you know who to call. But some of them are your competitors too. You want to beat them. You know, just because somebody is in your space and you can have cordial relationships with them, but you want to build a company that's that can beat them. That's what's going to attract them most. If you're actually, you know, I always say if you're actually hurting a company that's or you're filling a gap that they're not filling with their customers, it's the best time because then they know they need you. So I think that, you know, between an LOI and an acquisition, I think it varies dramatically with company to company. The one thing I would say to founders is look out for your employees. Because chances are, especially for a lot of young founders, they're going to work with these people again. And so treat them really well, treat them better than you treat yourself. Advocate for them. Make sure that the um acquirer treats them well, um, that things are done. Even more so than your investors. Your investors are gonna be fine, but your employees are gonna be with you for a lifetime.

SPEAKER_02 1:03:47

Yeah.

SPEAKER_01 1:03:48

Um, hopefully, you know, hopefully you can build something else with them. Um, and I think most founders know that, but they don't know what the specifics of that mean. So, what does that mean? Retention period, investing, how they get paid out, all these things, you should agonize about it, more so than yourself. Fight for it, negotiate, you know. Because you only get the one chance when you're negotiating.

SPEAKER_00 1:04:15

So did in in third case of Solvy, uh, did Zoom hear about uh because you were trying to sell it to them, or was it it it's a huge No, I I I you know I don't know that we ever actually I never actually asked the question, but I but they did.

SPEAKER_01 1:04:29

The chief customer officer at Zoom, we had pitched to him. Yeah, so he knew uh Nick Chung, and uh they had obviously done a scan of the CX AI space, so I think you know the corp dev people knew about us. So I think it's all of those things together. I think the best thing in the company is in most acquirers is that multiple people know you. But the one thing I would say is that it's it's not enough if corp dev knows you. Unless there's a burning fire, the the line of business has to know you.

SPEAKER_00 1:04:56

Yeah, because uh the process of acquisitions can be very distracting for a founder and their team.

SPEAKER_01 1:05:01

Yeah. Um, in all the cases, I don't think the very small number of people knew. Okay. Uh, because you you don't want I mean, this is one of the few cases where radical transparency doesn't work. It's because it's distracting and people start to wonder what it means for me. And you don't actually know the answer, so there's no point in giving them radical transparency when you don't actually know. So, my advice to founders is keep the circle very tight until you absolutely have to tell people. If you have a signed LOI and it's actually going to now you're gonna do diligence and people have to be involved, you you need to tell your employees. But even then, you have to be very careful in what you tell them. Is it the likelihood that it may not happen? It may not close, things can happen. We have to execute our business. Customers come first. So I think I think most founders know that. I think you know the tendency is to not to tell everybody in the world um don't get too excited. Sometimes it doesn't happen. Right? I've not had that environment situation, but I've Happens all the time where a deal collapses for different reasons. Particularly with public companies, if they're acquires and if they're using stock, you know, the stock, the market could dictate, something else could come along, you know, gyrations that are independent agnostic of the company. So I think when we were going through the Solvi process with Zoom, I think another wave of COVID hit. So there was also existential risk of that, like third, you know, extraneous risk. But fortunately it all went through smoothly.

SPEAKER_00 1:06:34

And at that point of time, like Zoom was doing remarkably well on the stock market at in 2020.

SPEAKER_01 1:06:40

Actually, I think at that by that time, I think it had slowed down. I think by 22. So actually the the market had had priced zoomed um differently. Yeah. So no, this was post the mega run-ups. So and I think now it's gone back up because of you know various factors that you probably know. Um market stock has done remarkably well in the last six months. Um, but I think we we yeah, we didn't see that huge run-up that they had between 2020 and 2022, because we were after that.

SPEAKER_00 1:07:16

Mid-2022, it had already price uh come by the market. Yeah. So so Mahesh, in in your journey of let's say you you you shared various lessons during your journey. You shared radical transparency, built with the team, you know, you shared uh, you know, going openly with customers, not selling them prior to educating. Educate as much as you can. Your job as a founder is to be the chief education officer rather than the chief sales officer. Exactly. Right? Uh and and ask, don't, don't be fixated on a problem. Uh ask customers what are the problems that are that are dear to them that they are trying to solve. That's what you did at Solvi. Right? That's how you observe that cloud fill is not the right way to go, whereas solving for the end consumers for a company is.

SPEAKER_01 1:08:10

We actually did a commercial at Global English about this. We said, and the whole premise of the product, it was a product pitch, it was like an animation, but it was the whole idea was we kind of made it that our persona buyer, what would it take to get them into the corner office? To become C customer office of the company. And so we kind of built that. And so we built it around the idea that the person we're selling to, our job is to get them promoted.

SPEAKER_02 1:08:34

Yeah.

SPEAKER_01 1:08:35

And if you think about it from that per second, it's actually a very uh liberating way to think about it. If my job, you're the customer, my job is to ensure that you are celebrated, promoted, made to look like a hero or a heroine, I have done something, right? It's actually a great way to think about it. And it never fails. So in the case of, you know, we're going to HelloFresh, thinking about, okay, if they can go instead of going from 1,000 agents to 2,500, and they can, and but they have the budget for 2,000, but we can save them that, they're gonna look great. CFO is gonna love them. So I think that's the that's the other thing, is just keep thinking about put yourself in the shoes of the customer. Why they're taking a risk on you, how are you gonna reward their risk? What's their reward risk, and how can you maximize that? And then when you get a few of those, celebrate those wins and have them be your advocates to the others. Because then they're in a position of saying, I adopted Saovi, it did these things, I'm it's great. This team will make you successful. That's what buyers want to hear. Right? They don't want to hear about the tech and all that. They'll learn about those things. But if they know that it works and that it's gonna get them promoted or make them look good, you got a you you got a meeting.

SPEAKER_00 1:10:01

Yeah, yeah. That's what is said in enterprise software, even the CXO that you are setting to, yeah, uh uh you only become successful if they get promoted for implementing you. Correct.

SPEAKER_01 1:10:12

Yeah, and so people talk about champions and you know all these other things. It's like, yes, people have self-interest. And it it's okay to lean into the self-interest.

SPEAKER_00 1:10:21

Yeah. Thank you so much, Mah. I had a wonderful discussion. I learned so much during the conversation. Grateful to you for doing this.

SPEAKER_01 1:10:29

I appreciate the time and I hope that uh anytime we can help founders, you know, that's like I said, I want to be as helpful to as many people as I can. And so this is a great forum. I think what you guys are doing with the podcast is uh fun. I've listened to a number of the episodes and learned a lot myself.

SPEAKER_00 1:10:46

So which ones have been your favorite? We'll try to reach that kind of a bar with every episode.

SPEAKER_01 1:10:51

Yeah, I think um, you know, I I've I listened to Sri Sha's one, of course. One of my favorites. And then I uh listened to the the gentleman who is at Cloud Cloudflare and Manish Fair Manish, yeah. And uh I love that one. I thought he had some incisive points more from the go-to-market side. I thought that was some really good ones. So those are two that I liked. Um, but I'll go back and listen to more. Thank you. Thank you so much. Yeah.

SPEAKER_00 1:11:15

Such a pleasure. Thank you.

SPEAKER_02 1:11:16

Thank you.