We used to have about 20 big deals in a given quarter. So imagine discussing 20 big deals in about 60 minutes. That's 3 minutes to a deal. And in those 3 minutes, I'm also trying to gather the news, right? What's really going on? And then maybe I have a few seconds left to decide how to change the news, right? So think about how compressed that timeline is.
Correct me if I'm wrong. Mohit, both Nutanix and Cohesity, they are doing billion dollars in revenue each. Correct.
That's correct. They're both north of a billion dollars in ARR. If I was to see a thread through the three companies including my current one, I would say they're all about convergence in some way or the other, right? Nutanix converged infrastructure, Cohesity converged data. Siphon is more about converging go-to-market context. One CFO told me that we are connecting AI to some 50 different tools and MCP connectors and yet at the beginning of the quarter the pipeline looked healthy. We entered the quarter with $500 million in pipeline. Within two weeks we had people who looked at the pipeline closely and the pipeline fell by more than $100 million. That's an example of a lot of tool sprawl and b, despite the fact that we are using all kinds of tools including AI and whatnot, we still don't have enough context. New company, Siphon, now our AI is going to watch over the deals, our AI agents are going to be updating that information and so the companion would basically be watching out for, you know, be looking at your thoughts that hey, some customer is going south or the sentiment doesn't look good. Informed self-driving cars, right? The car is kind of like your companion now. It's doing the heavy lifting basically for the most part. It's an autopilot doing things for you and then it'll involve you where you really need it. So now you literally have two beings, like one artificial being and one human being looking at the context and making sure that it's accurate.
He built Nutanix, then Cohesity, both crossed a billion dollars in ARR. Most people would stop here. He didn't. He saw firsthand as CEO how broken go-to-market was: 20 deals, 60 minutes, 3 minutes per deal, and realized the whole world was reporting the news instead of changing it. So he started again. This time he's building Siphon to fix the one problem every revenue team has but nobody has solved. This is Mohit Aron and this is his third act. Now I bring you Mohit. All right, Mohit, excited to have you on the 1947 Rise podcast.
Shiva, thank you so much for having me here. Exciting to be here again.
Look, I want to start by asking you, Mohit, what drives you? Is it the thrill of winning or fear of failure?
You know, interestingly, it's neither. I mean, obviously, everyone wants to win. I'm not saying that's not a thrill. And by the way, I think if it was the fear of failure, then I would never do it the third time, right? Who wants to live in fear all the time? It's actually the journey that drives me, right? The journey of building something phenomenal. The journey where I'm surrounded by smart people. I'm seeing young people thrive and become a much better version of themselves. A journey where we are constantly on our feet thinking about new challenges and how do we basically win, right? Despite the fact that, you know, nobody wants you to win easily. They want to win, right? Whatever might be an incumbent that we are fighting, they don't want new guys to win. And if there are new guys, they want to be the ones who win. They don't want other new guys to win. So, and sometimes it gets busy and there's a lot of noise and so navigating through all that is its own reward as you figure out those solutions. So that's what excites me. It's more the journey.
Understood. We'll talk about your new journey, Siphon, in a bit. You know, you went to IIT Delhi, moved to the US, went to Rice, did your PhD, got into Google, and I want to pick the thread from Aster, the company you worked at before you started your entrepreneurial journey. Mohit, before, you know, we started recording, we were talking about this, that, you know, when you had come to the US, starting a startup was not a thing at all. It was more about finding a job. So talk about Aster. Why did you join Aster and what did you kind of learn there which gave you confidence to go and start your first company?
Yeah, let's start. You know, I came to the US in 1995 and at the time doing startups was not a thing at all. I think people came here to basically work in some well-known company and, you know, make good money and do good work. That's why they came here, right? But I mean, just think about it, right? I mean, normally when people take a risk, they want to move out of their comfort zone. Maybe they want to move one or two degrees of freedom outside their comfort zone. They don't want to move like 10, 15 degrees out of their comfort zone. But as they see others who are taking the lead, then what looks like 15 degrees apart is like, no, no, that's just two or three degrees apart. Maybe I can also do this. So slowly, right, when I graduated with a PhD in 2000, I of course joined, you know, some other company. But then I saw people who were, you know, maybe my batchmates or maybe a few years ahead of me, they were now, some of them started doing companies and some of them even became modestly successful. And so that puts the seed in your mind that, hey, maybe I can also do it, right? Maybe it's not that far-fetched. If that guy can do it, then maybe I can also do it. And then once you progress in industry, you gain confidence. Then like, okay, maybe I should do it. You know, what's the fun in doing more of the same? Let's try somewhat of a risky stuff. And at this time it's no longer 15 degrees apart. It's maybe two or three degrees apart. And so you just got to cover that distance and you put yourself outside your comfort zone, learn that stuff and go do it. And then when you become successful, your success drives others, right? And slowly that seed goes to, I mean, first it was, you know, it caught up in the US and then people in India started doing it. And now these days we hear about so many startups in India. That's kind of how it happens, right? And so big change from when I came back in 1995. I think there are so many companies being built not just in the US but also in India. And what was your second question?
So, you know, you ended up joining Aster and what kind of, you know, prompted you or what got you to start your first company while you were at Aster?
Yeah, I think I'll start by saying this. I did a PhD in computer science. Every person in my mind who does a PhD has to eventually make a decision whether to stay back in research or whether to join industry. And so I went through the same thing. It was a painful decision. I loved research, but for a variety of reasons I chose industry. But I knew that, you know, my mind was in research, which means that I wanted to invent things. And the way to invent things is to eventually start a company. You know, hard to do it in some other company where there are already like a thousand people and most of the innovation is already done and you're just there to further incrementally add stuff. But to do companies, you have to learn how to do companies, right? So Aster was a little bit like that. I was happily at Google. Google, when I started at Google, it was, you know, 600 people back in 2003. When I left Google, it was some 35,000 people. And now these days, I don't know, it's probably more than or closer to 200,000 people. But the point is, I left Google to learn the ropes of doing a company. And so I joined a small company as data systems and the focus was to learn, right? So again, going back to the fact that I wanted to innovate, I wanted to build something from scratch, but I wanted to learn how to do a company. And so I kind of got that experience. And, you know, when people start levitating around you, when they depend on you, well, anytime there's a big architectural thing, they come to you. Even people outside R&D are depending on you and you kind of know that you can now lead a team independently and lead a company. And so that was basically, it was always that plan that I was in data systems only to learn the ropes of doing a company. And when I got that confidence, we, you know, we started Nutanix, which was my first company and today it's a public company and that's how it came.
Understood. Mohit, maybe give us highlights of your first two companies, Nutanix and Cohesity. What were they about? What is the, you know, what you are most proud of? What have they become?
Yeah. So a lot of things to be proud of, but I'll start by what are they about. I think if I was to, you know, see a thread through the three companies including my current one, I would say they're all about convergence in some way or the other, right? Nutanix was about converging infrastructure. So let me explain that. Before Nutanix, if you wanted to sort of run your production applications, especially in a virtualized environment, you would go buy compute from one vendor, then you will go buy storage from a different vendor and then some expensive networking from a third vendor. And then you'll connect all these three to get a platform on which you can run virtualization as well as your applications in a virtualized environment.
And you can imagine that going to three different vendors, buying three different solutions, then cobbling it together, all of that was not just expensive, it was hard to manage. And so what we came up with was a concept called hyperconvergence which sort of in the same platform did all three, right? So that's why I said it was converging of infrastructure, right? You're converging the compute infrastructure, the storage infrastructure and the networking infrastructure, bringing it together. So that was basically Nutanix. So I mean one example that I would bring up on how simple it made things was at the time this Iraq war was going on. And, you know, the people, the US army needed to carry, you know, virtualized platforms that would take care of their email and stuff. And in that environment they had these Humvees, right? These vehicles and the platform needed to fit in those Humvees. Now the traditional three-tier architecture was extremely complex and large and would have a hard time fitting in these Humvees whereas Nutanix's product would very easily fit there. So that's just an example of the simplicity that we brought to the table.
And I think the, was it the Iraq war or was it some other war? It was some war. Basically the US army became a big consumer of our products. So, but the idea I'm trying to give to the audience here is that it was the convergence of the infrastructure that made it simple.
My second company was, and if you think of Nutanix as managing your production data, right? So think of it as the tip of the iceberg. If you map the world of data into an iceberg, the tip of the iceberg is your production data. And that's where Nutanix sits and that's where it converges stuff. Then there is a large part of the iceberg that's below the surface of water. Think of that as everything that is so-called secondary, right? Think of it as the second touch of data, right? Backups, archival, test and development. A lot of what you do in analytics, all of that is really the second touch of data, if you may. And so my second company, Cohesity, was all about converging that. So said another way, while Nutanix converged infrastructure, Cohesity converged data, right? Or secondary data. So that was the second company I did. So we brought, we ushered in simplicity in that environment. Normally people would go buy backups from one vendor, even within that, the backup pieces were very complicated. You were cobbling it together using three or four different pieces. Then they would go buy archival from somebody else, you know, file servers from somebody else and so on and so forth. So we kind of converged all that together and eventually resulted in security or ransomware detection being converged and then finally AI getting converged onto the same platform. My third company, Siphon, is more about converging go-to-market context. You know, it's the data that you need to make efficient decisions while running your go-to-market operations. So in a way that's also seeing a thread through this convergence thread. So the problem is that our go-to-market data is sitting across multiple systems and so it's very fragmented, hard to get hold of in any one place. And second, this data, this context doesn't reflect reality.
So it's either just flat-out missing or it's stale or it's just garbage. So the concept behind context convergence is that you're not only trying to bring the data in one place but you're also converging it closer to reality. So you're making it reflect what the reality is, right? So that's context convergence and that's my third company that I'm now doing.
Understood. And correct me if I'm wrong, Mohit, both Cohesity and Nutanix, they are doing billion dollars in revenue each, correct?
That's correct. They're both north of a billion dollars in ARR. So yeah, both of them are big companies. Nutanix is a public company and Cohesity hopefully will go public one day.
Let's see. Yeah, if you were to, you know, pick one reason, you know, things were going great at Cohesity, it was growing, what was the urge to start the third company?
Yeah, a couple. I think one was just my, I saw firsthand running it as the CEO how bad the go-to-market, how hard and bad the way go-to-market execution was. I mean, it's more an art than a science. Everything is like, involves a meeting because I already said the context is kind of all over the place and it's hard to get at it. And anyway, you don't trust it. God knows whether it's right or wrong. So you call a meeting, everything is a meeting, right? It's so inefficient. And most of the time that's spent in these meetings is kind of extracting the news or reporting the news and not changing the news, right? So I personally used to run a big deal review meeting, right? So we used to have about 20 big deals in a given quarter. So imagine discussing 20 big deals in about 60 minutes. That's three minutes to a deal. And in those three minutes I'm also trying to gather the news, right? What's really going on? And then maybe I have a few seconds left to decide how to change the news, right? So think about how compressed that timeline is. And what I'm also indicating is that you only have time to discuss the short term. What about the deals that are not quite deals this quarter but they might become important deals, you know, next quarter or the quarter after that? And I don't have any time for that. In fact, by the time I do have time for that, which might be, you know, when the deal is in quarter, when the next quarter comes, it might be too late. If for some reason the customer is, let's say, not happy, the time to do something about it is right now, not when, you know, it's closed for the customer to make a decision.
