Every argument clarity score on this site is built from rows on this page. Each
question and answer was assessed with names hidden, the host's own answers included, on
four things from 1 to 5:
directness (does it answer the question asked), coherence (do the ideas follow),
precision (concrete details and clear references), compression (says a lot per word). The weighted
mix (30/30/25/15) is the exchange score. A person's published score averages their exchange
scores on raw tape only, at least 8 of them, shrunk toward the cohort mean.
Full method →
Answered raw tape
D 5 · C 5 · P 4 · Cm 4 4.60
Q Got it. And what kept you going in the first five years? Because as you said, right, there was a struggle for product market fit, getting the right set of customers, figuring out what could scale globally. It must not, not have been easy, right? Those five years, there was no SaaS ecosystem in India.
A I think that's the fun part of the whole thing. Like it's the reason it's called venture, you know, you are figuring out stuff. So We very well understood we are on the first of many, many things, and that was the exciting part of it. We also very well understood that, look, you know, there's one thing which is critical about a startup that you got to dream big, that you have to have a big idea and spending a lifetime chasing a big idea is far better than, you know, getting an overnight success on a small idea, right? So we really wanted to find a product market fit where the market is large, the TAM is large, data protection and backup and recovery, disaster recovery, long-term retention is The entire market, even though, unless you understand the market close enough, it looks like a, a very infrastructure market, a thirty billion dollar market, right? It's a very, very big time. We were the first one to actually think and pioneer the whole SaaS-based approach to, you know, change the game. This market was known to have multiple vendors to be deployed to sound a very, very highly complex problem. The joke was it's a seven vendor problem and you have to deploy multiple parties and the seventh vendor is a God. Ultimately pray to God it actually works. So to really, really make it work to actually Turn the market upside down and have a subscription option for enterprise to deploy…
AI assessment note: “I think that's the fun part of the whole thing. Like it's the reason it's called venture”
Answered raw tape
D 5 · C 5 · P 4 · Cm 4 4.60
Q And which year was this that you got your, the one million dollar ACV customer?
A We started selling the cloud version in, it was in 13th, it said, I think I would say March, March of 13th, if my memory serves me right. And I think by December in seven to eight months, like we had, we had a first million dollar ACV customer. Now getting one customer doesn't mean the business model is viable, scalable, or repeatable, right? Like the, each of these Three things, viability, repeatability, and scalability, like you have to spend multiple years to actually get right. So often time in the product market fit is good. You get lucky with one or two really, really good early adopters, but getting to the mid-stage customers and then the mature customers and late-stage market takes multiple years of refining your product and go to market engine.
AI assessment note: “I think by December in seven to eight months, like we had, we had a first”
Answered raw tape
D 5 · C 5 · P 4 · Cm 4 4.60
Q So if you could remember till 2013, before you got your first large customer on cloud, what was the growth revenue till then?
A Even though like if my memory serves me right on the software model, we had hit seven to eight million dollars already, but as I said, it was a complete redo of the entire company. We have to burn that eight to nine million dollars down on the ground and build it all over again, because these are two fundamentally very different companies. We had a tough choice to make that do we build a software business by replicating software across the board? Because cloud is not a technology charging by itself, right? Cloud is also a business model shift, operational shift in the company. Right. So we had to almost burn that revenue, which we had built and softened in the ground to build the company again. So pretty much starting with ground zero on the cloud platform.
AI assessment note: “if my memory serves me right on the software model, we had hit seven to eight million dollars”
Answered raw tape
D 5 · C 4 · P 4 · Cm 4 4.30
Q Got it. You, you know, let go of eight million dollars in revenue. How hard was this decision to take at that point in time?
A It was pretty hard. Initially, we felt like, hey, we could do both. And that's an easy answer for any entrepreneur in any company saying, you know what, how different could SaaS be from building software, just a hosted software. As we got deeper into it, we spoke to customers, we realized, you know what, they're actually a different set of customers who are facing different set of challenges. The company's DNA to actually sell subscription, which is sell software, which is downloadable, is very, very different. Right. And you know, if the market is so large that just do one thing in one thing, right. Even a 30% market comes our way and believes in us that we'd rather be number one in the world doing the 30% of market versus be a software, which could, you know, which could certainly be good, but we felt it could be over time, like not a big, big advantage compared to the market. So given the time was so big, like even the decision was very, very hard. Like it initially, it confused us, confused the board. We have been thankful to our investors and board and they let us Experiment and, and think big. It was very, very hardcore, but in hindsight, one of the best decisions we ever made.
AI assessment note: “It was pretty hard. Initially, we felt like, hey, we could do both.”
Redirected raw tape
D 2 · C 3 · P 2 · Cm 2 2.30
Q So let me ask you, what are the mistakes that you avoided in this journey?
A That's a difficult question for me. The reason I say so is like, I know a lot of mistakes which I made. I probably wouldn't even know the mistakes I avoided. Somebody probably watching me outside in could see that Better. A lot of mistakes are made along the way. I'm not sure which one I avoided. No, I think the, the learning curve is how do you hire the right person for the job is always a big learning curve. The learning curve on how do you build a repeatable process. As an engineer, you get trained to sort of work on more, you know, creative means sort of, but process is not a thing, but I learned that US may not be the best country. Like it is besides being a very innovative country. It's also the country to scale innovation. The scale part, the process part is also critical, which as an engineer is not very natural.
AI assessment note: “I probably wouldn't even know the mistakes I avoided.”
Not addressed raw tape
D 1 · C 3 · P 3 · Cm 2 2.25
Q How much time it took to hit, you know, the first one billion in ARR?
A We initially got immediate traction in software, really selling software between 2010 and 13 and 13. We actually found like a hundred plus customers rapidly deploying. We had to almost lead to the entire business because the customer deploying the software, but not the same one deploying our cloud, right? So when we were actually focused on deploying cloud, we actually got immediate traction almost immediately. We saw, I think one of the very large pharmaceutical companies deploys globally and spend like a million dollars plus, like almost within the first year, right? So that's how we came to the realization that this product market fit is actually a sucking sound in the market for what we have to offer. And then we have to double down, triple down to actually solve the problem. So once you build something good and once you hit product market fit, like There's an incredible hole in the market to actually absorb your product and deploy.
AI assessment note: “We initially got immediate traction in software, really selling software between 2010 and 13”
