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Ushering In White Revolution 2.0 | Ranjith Mukundan @ Stellapps Technologies
207 Plays3 years ago
‘Milk is the largest crop on this planet and there is a strong need for technological interventions.’
Convinced by this, a group of ex-Wipro employees perceived digitizing the Agri-Dairy supply chain as an opportunity.
In this episode of Founder Thesis, Akshay Datt speaks with Ranjith Mukundan, Co-founder and CEO, Stellapps Technologies Private Limited - an IIT-Madras incubated start-up which provides end-to-end dairy technology solutions.
Ranjith is an alumnus of Illinois Institute of Technology, Chicago and has worked with Wipro for more than a decade. In 2011, he along with a group of IIT graduates started Stellapps to address the major problems in the milk production process and help dairy farmers and cooperatives to maximize profits with minimum effort.
Tune in to this episode to hear Ranjith speak about how Stellapps is leveraging AI/ML to revolutionize the dairy supply chain in India.
What you must not miss!
- Ranjith’s interest in M2M space.
- The business model of Stellapps.
- Finding product-market fit.
- Tech ensures supply chain integrity.
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Transcript
Introduction to Zencastr and Podcast Support
00:00:00
Speaker
Before we start today's episode, I want to give a quick shout out to Zencaster, which is a podcaster's best friend. Trust me when I tell you this, Zencaster is like a Shopify for podcasters. It's all you need to get up and running as a podcaster. And the best thing about Zencaster is that you get so much stuff for free. If you are planning to check out the platform, then please show your support for the founder thesis podcast by using this link, zen.ai slash founder thesis.
00:00:27
Speaker
That's zen.ai slash founder thesis.
Ranjan Mukundan and Stellapps Overview
00:00:31
Speaker
Good afternoon. I'm Ranjan Mukundan, CEO, co-founder at Stellapse.
Indian Dairy Industry and Stellapps Innovation
00:00:46
Speaker
The best innovations happen at the intersection of two different spheres. The Indian dairy industry is already the envy of the world thanks to the pioneering work done by companies like Amol, which brought about a white revolution in India. On the other hand, Wipro is the envy of the software world being among the top three IT companies in India.
00:01:10
Speaker
This is the story of how a bunch of ex-vibro guys are bringing about a white revolution 2.0 by making use of cutting edge hardware and software.
00:01:21
Speaker
Stellaps is one of India's largest dairy companies and you can probably guess from the name Stellaps that our guest today Ranjit did not really set out to build a dairy company. He had something else in mind and this conversation is a fascinating peek into how by using first principle thinking Ranjit made Stellaps the most technologically advanced dairy company in India.
Ranjit's Career and the Birth of Stellapps
00:01:47
Speaker
Here's Ranjit talking about the journey from working at Wipro to becoming an entrepreneur.
00:01:53
Speaker
I had a good client at the Vipro carrier ladder. In those 15 years, when I moved out, I was globally heading Vipro's telecom value-added services and service delivery platform practice, which was a practice under the telecom division. And this practice was all about how do I let AT&T launch its own app store and take on Apple, right? Kind of a practice.
00:02:21
Speaker
How do I let how do I let hangama work on top of a natural network? How do I launch more? How do I let this million model monkey, right? I mean, that that's that model is all about on the internet. It's difficult to bet on the chapel thrive, right?
00:02:41
Speaker
Just need to let the million monkeys throw things out of the internet and one of them will become a killer app. The whole notion is that if you give a million monkeys a typewriter, you get Shakespearean in time. Difficult to predict. So the notion of killer app didn't exist because we worked on messaging platforms for a long time. In 2011, we were so dismissive about a WhatsApp-like stuff.
00:03:08
Speaker
If someone would have come to us and said, no way it's going to succeed. So you don't know until it succeeds that it succeeded. So we were very deep into that. So I was heading a practice called value added services. It's all about putting out platforms.
00:03:25
Speaker
And then app stores and things like that can come up. And then one of them will become an ecosystem of developers. And a platform, right? A platform and ecosystem of developers. So that is what I was driving that practice. And that's where the name Stellapp also comes from, because we knew whatever we do, it's going to be an application realm, right? So we knew there has been an app in the name of the company.
00:03:51
Speaker
So we said Stellar applications, the domain exists, right? So we said App Store, we looked at Appsery, and all of that, right? A nursery that nurtures apps. Okay, absolutely. So finally, we figured that, okay, a Stell app sounds quite hip.
00:04:09
Speaker
We know that our company has to be revolved around applications, but obviously what we're doing right now is about cows and milk, which is nothing to do with applications. So the name App came into picture and we decided no matter what we do, applications and not the network will drive the business momentum.
00:04:27
Speaker
And it has to be something horizontal where if you are in healthcare, if you're in education, anyone have to use that application. It has to be like an IoT app store. We have to become the Google of IoT.
Stellapps' Technological Evolution
00:04:40
Speaker
That's where the original thought process collapsed and all that was the genesis of the whole part.
00:04:48
Speaker
What do you mean by it has to be horizontal? What is that? What we do with applications on the platform should not be something that's daily specific, agri-specific, healthcare-specific, or education-specific, or automotive-specific. It has to be cross-industry, right? That's what we got started in 2010. I have to build an IoT platform, an app store for IoT, that
00:05:14
Speaker
telematics industry could use, and healthcare or a telemedicine industry could use, agri-tech industry could use. So that's where we started. Automotive could use. Automotive could use. So we started to trust the horizontal platform because we were so enthralled by this million monkey model. And we thought that we just need to unleash this model in an IoT framework, right? Because we have seen this model work in the content and outside.
00:05:37
Speaker
Your original idea was to this exactly this, like build an app store for IoT. Exactly, exactly. But was IoT even a thing back then? No, it was not even a jargon those days. So when we started, an M2M was made popular by one of the consulting companies. So it was called machine to machine, wireless machine to machine. So we said we are an M2M. We want to actually call it an M2M app store.
00:06:03
Speaker
We said, we'll build an M2M app store. And then later, IoT became popular. Then they said, yes, M2M is IoT. It's an IoT app store. And of course, there's a lot of journey in between. And finally, we are a dairy supply chain company today. That journey is exactly what I am looking for. That journey is the most interesting thing in terms of finding a fit. Finding your market is very important for a founder to do.
00:06:29
Speaker
What made you choose the M2M space? Because it was so tiny at that time, no? It was very tiny, but it was an in thing. So as a techie, you also want to pick the most in thing at that time. And the unfortunate thing about a techie is that you're trying to pick the most glamorous tech piece irrespective of whether it has a business connotation to it or not. Because none of us come from a business world. We're all techies and we think,
00:06:59
Speaker
Because as you know, we're all very famous about the Google story. They went to sell the Google search engine to Yahoo for a million dollars and Yahoo refused to buy it. They didn't know what they built. So we thought even we will also find one such mojo where we build something and eventually it becomes a few billion dollars. We thought let's build something very tech. Let's build an app store.
00:07:23
Speaker
And we will then figure out the business model later. We will figure out the monetization later, build something very tech and geekish. And the reason why we picked M2M was that one of the last projects that we did when I was at Pro was, as I said, trying to build an app store for AT&T.
00:07:42
Speaker
And AT&T was, the network took a big beating because of the relationship AT&T had with iPhone, with Apple. But Apple made all the money with all the apps and all that. And AT&T just became a dumb pipe, right? They give the network. Then AT&T decided, look, if we have to monetize, we have to develop our own app store, right? But you can imagine what a telco trying to develop an app store. Yeah, yeah, yeah, yeah. And then the story went there today.
00:08:09
Speaker
And it was a giant project between Pro and Microsoft. We were all spending a lot of time in Seattle those days.
00:08:18
Speaker
to see how to help AT&T, see how to build an app store. And the team of M2M came up. M2M is in, people are, world is going wireless, right? All the parts and wired phones are going to go away. So wireless M2M is very critical. And the communication is not just going to be between humans. Medical devices are going to communicate, vehicles are going to communicate, which Tesla has done a tremendous job on that front.
00:08:45
Speaker
So, M2M is going to be an important piece of that platform. And when we dug deeper, we said, yes, this is where the world is going to be. There's a lot of IoT going to be. It's not just going to be the 6 billion humans who are going to communicate. It's going to be those several more billion devices that are going to communicate.
00:09:02
Speaker
And hence, let's build something around that team. So when we stepped out in 2011, we figured that let's pick M2M as a team. Because we figured it tickled the geekish part of our brain. It tickled the tech glamour part of our brain. So let's pick something there. And that's why we decided, yeah, let's build a new app store well. We said, let's build an IoT app store and a horizontal IoT app store. So that's what triggered for us.
00:09:27
Speaker
And then the six of you were like, were you all in India, in the US? Yeah, by that time, we had all come back and we had left Vipro, we had worked with many of the companies. At that point, we were all at Vipro. They were all part of my team. So I was heading the team and my co-founder was all part of my team. And we decided, yes, time to take a plunge, 2011.
00:09:53
Speaker
And we decided, yes, let's build out this platform. And let's see
Applying IoT in Dairy and Agriculture
00:09:58
Speaker
which industry to apply it to. So we spoke to folks in medical industry. We spoke to a lot of physicians. We spoke to a lot of surgeons.
00:10:10
Speaker
We spoke to telematics folks like Volvo. I decided, would you like your buses to be... What is telematics? Telematics is about monitoring vehicles, your car. How do I know that? You're a better driver than I am. And hence, you deserve a better insurance premium than I do because you drive your car better. So there are communication interfaces in these vehicles called OBD2 and those interfaces where you could put it off and I know how many times are you braking?
00:10:39
Speaker
doing a harsh braking or accelerating too fast and all of that. And if Volvo were to partner with us, all the buses would be equipped with this cloud-based technology powered by our IoT platform and they would be able to tell a Volvo bus buyer saying that I can tell you which driver drives better.
00:10:58
Speaker
He actually go to sleep at the wheel, right? You know, kind of stuff. So we spoke to a whole bunch of cross-industry guys. And at the same time, one of my Viprok colleague's uncle, he was also, he was starting an organic dairy, right?
00:11:18
Speaker
So he said, you guys are very tech geekish and all that. You're trying to fit things onto cars, trying to fit things onto buses, trying to fit things into an operating theater. Why don't you help me use some of those technologies for my organic milk?
00:11:33
Speaker
It was an interesting idea. Agri and dairy was not on our radar. We actually visited some of the farms, and that's probably one of the first times you're actually visiting rural India. And the last years we probably visited a lot more of it quite a bit, but that was the first time. And it became extremely interesting because we felt that, unlike an urban use case,
00:11:59
Speaker
A rural use case actually needs a remote monitoring much, much more compared to urban use case. And it's much more compelling because it's to do with livelihood. It's not about the ability to switch on and switch off your air conditioner when you're getting home. It's not as compelling. You wouldn't pay for it. But here, there are people saying, if I can actually monitor my cow sitting in Bangalore, I'll pay you XRP right now. So people are willing to leave money on the table. And we figured that from a problem-solving perspective,
00:12:28
Speaker
It helped solve two things from an IoT perspective. One, the only way to ever monitor a thing's agricultural component sitting in Bangalore is over an IoT. There's no way you'll have people running each and every cow and monitor the cow. Probably, you park your car in office, you park your car at home, it's well monitored already. You wouldn't spend $1,000 a month to get that monitored.
00:12:54
Speaker
It's a needless luxury. Exactly. It's quite compulsive. There's no other way to monitor it. That's number one. And number two, we also figured that in these rural villages, there is no sufficient expertise available on the ground to act on those monitored data.
00:13:13
Speaker
Because all the good vets, all the good agriculturists are all relocated to urban centers, running pet clinics, or are in Australia or the US doing some farm work there. So we figured that the analytics on the cloud can be a reasonable substitute for lack of expertise and premise.
00:13:35
Speaker
Whereas in urban scenario, we didn't find it that compelling. Your surgeon was just a phone call away. Your 108 emergency service is just a phone call away. And then you get access to best of expertise in Bangalore-like cities. Whereas in the villages,
00:13:54
Speaker
expertise has to be rendered differently. So it was called analytics, though just machine learning was still not jargon of those days. We said, yeah, let's make use of a lot of analytics engines and solve for lack of expertise in premise.
00:14:13
Speaker
And the only way the data is going to come to the cloud is through IoT. So these two things fell in place. The lack of expertise in premise and analytics, which is now we call AI, ML, and all of that. The Redwoods evolved, became an in thing. And then IoT is the only way to monitor. So we spent a lot of times on those farms, literally living on some of those farms. It's the first time you're actually seeing how animals smell. Many of us, it's the first time we could actually tell a cow from a bull.
00:14:41
Speaker
No. Now I can talk about, hopefully someone wants us about milk and cows and all of that. The first time we actually figured that milk actually doesn't come from a slot machine in Bangalore, it actually comes from the animals. In fact, they're actually one of my friend's brother who actually thought milk comes from slot machines because some of us want milk.
00:15:04
Speaker
So we went deeper, spent about a year or two in 2011-12, then we didn't realize that you need capital. It can't just be our problem-solving part of the brain. How do I build a business model around it?
00:15:21
Speaker
And that's yet another journey, right? So we figured that we started a journey by thinking, let me start selling this tech to the farmers, right? So we're very farm focused. We were trying to automate
00:15:39
Speaker
If you like to hear stories of founders, then we have tons of great stories from entrepreneurs who have built billion dollar businesses. Just search for the founder thesis podcast on any audio streaming app like Spotify, Ghana, Apple podcasts, and subscribe to the show.
00:15:59
Speaker
What was the problem you were solving to a farmer? Because you'll have to explain to him in very, very simple language that what is your pain? Once we had figured out the tech piece, you were exactly trying to figure out what you just asked. What do we now sell? Someone has to pay for it. It's an interesting problem. Monitoring cows looks interesting. Fitbit for cows looks interesting. But then someone has to pay for it. And then we decided, can I then take it
00:16:29
Speaker
to a dairy company, like an organic dairy company, like the company that I mentioned, Akshay Kalpa, who are one of our first customers. Can I try two models? One, I'll sell it to a dairy, saying, look, if your farmers have to shift the orbit and produce good milk, you need automation at these farms. You need monitoring at these farms.
00:16:51
Speaker
and you need untouched milking of the animal so that the milk can be sold as premium milk. So why don't you buy the tech and become a channel to sell to your farmer? Because you see the farmer every day. We don't. We are a tech company.
00:17:08
Speaker
That was one model we tried. Second, we also started approaching farmers directly to some rural channels, saying, hey, farmer, look, you seem to be interested in dairy. And I have this tech. This is my pricing. What do you want to buy? Then we figured that... Using the tech, the cows will give more milk.
00:17:32
Speaker
Exactly. So the tech would help you do at that point, now it's a little more different. At that point, the key pitch was helping improve productivity and quality. By monitoring the cows, I will tell you, I will help you do preventive health care.
00:17:55
Speaker
so that instead of sickness management, I will ensure that all your issues are fixed at a subclinical level so that you can save money on veterinary costs. You can improve your productivity because if your cows fall sick, they don't give milk too. Then quality, I can help you milk the cow without touching the other because when you touch the other, we used to make automated milking machines.
00:18:21
Speaker
It can just attach itself to the ardor and it's a human milking. All over the world, except in India, cows are milking machines. Human hand milking happens probably only in India. In fact, there are tourists who come abroad to see how animals are hand milking. But for us, that's the daily side for us. So we said, we can help you milk the cows without touching the ardor. And by the way, you don't need labor. Even if you have 10 animals,
00:18:47
Speaker
You just need one machine. You don't need to hire a laborer because a laborer was a problem in Indian rural scenario because they were all either migrate and all that. They'd come to cities and do other labor work. The value prop was well understood, but not everyone was willing to pay based on the value. I want to go a little deeper into the value prop.
00:19:10
Speaker
How would you exactly know that this car is going to fall sick, for example? Like you said, you will increase the uptime, like you will remove downtime due to sickness. How would you know that? So a couple of ways. One is we had this wearable platform which you could fit
00:19:30
Speaker
It's like a fitbit for the cows, right? You could fit on the cows and you could actually measure the step count, right? A step count is typically indicative, basically the software will keep a measure of the base step count.
00:19:46
Speaker
If the step count keeps trending downwards, you know that something lethargic is hitting the cow. So we may not know what exactly is the disease, but you know what, something. So you would send them alert. Early warning signals. Early warning, right? Saying that this cow is slowly less active.
00:20:05
Speaker
And hence, it might have. So then it sends an alert to the neighboring vet or a para vet. They would go examine, oh, you're right. This has a hoof infection. Lucky, I caught it now. Otherwise, it would have become a clinical infection. That is one. And second, we could also measure things like sitting and standing ratio. Typically, cows ruminate when they stand, when they sit, not when they stand. So if you measure the sitting standing ratio, you know that this animal could have a nutrition issue.
00:20:35
Speaker
And then we also had an Android-based application which works in conjunction with this wearable called as a herd management application, which a village-level technician could use to enter parameters like when was the animal vaccinated, when is the next vaccination viewed.
00:20:55
Speaker
When should you do the next deworming? What kind of a nutritionist? But these are entered data, not automated because you can't automate all of them, but you have an app and then the cloud intelligence then takes over and tells you, okay, if this cow is vaccinated now, next vaccination comes, this so and so. And then it could give you nutritional alerts, it could give you healthcare alerts, it could give you general upkeep alerts.
00:21:20
Speaker
So, all of them in totality tells you how to improve productivity, how to reduce downtime, and most importantly, how do I inseminate the animals at the right time? Because one of the biggest problems for the farmers is that
00:21:37
Speaker
If you don't inseminate the cows at the right time, it won't get pregnant at the right time. And hence, if you don't get pregnant at the right time, it can't give enough milk in that particular year. And hence, it's sort of dry for most of the year, which means it's a cost center for you. But it's not producing milk, which is the revenue part. So cows give milk only if they get pregnant.
00:22:03
Speaker
Just like in human beings, right? So it's a higher order ruminant, right? So the biggest problem is how do I detect peak ovulation and inseminate it at the right time? Otherwise... And how do you know that? Like through that, how does it fit with it? Yeah, again, more closer to the 21st day.
00:22:25
Speaker
the activity levels of a cow in peak coalition would peak, right? If you're able to detect this peak, you know that within a four hour window, you know this is the peak coalition and hence if you disseminate it in the four hour window, the probability of pregnancy is the highest.
00:22:41
Speaker
So in India, people don't use tech. They use telltale science. And what if it's happening between 10 PM and 4 AM when no one is in seeing? Then you miss some of the speak window. Where tech you monitor, you measure. So these are all the key ways in which you can improve productivity by reducing downtime, by decreasing what we call as an intercarving period of the drive time in the curve.
00:23:05
Speaker
and ensuring that all the general upkeep sort of happens. So 2011, you put your jobs. By when did you have this product, like a prototype that you were ready to sell? Yeah, so by 2013, we had the prototypes ready to be sold for the farm side intervention. It included things like automated milking machines,
00:23:31
Speaker
where you could just... Which you probably procured from some vendors. Yeah, we designed the entire thing grounds up because until then... Okay, you designed it, okay. Yeah, so I mean, that's a good part about what we did. It was like, not just, you know, calculating our software engineering part of a brain, right? It sort of also stretched our mechanical engineering concepts, civil engineering concepts, the electronic engineering concepts,
00:23:59
Speaker
all of that came to the fore. And then the fundamental sciences of veterinary science and all of that. So it was like almost redoing three or four times what would pick up during an engineering course. You do grounds up, you go look what's happening, you read, you design. And a lot of us had given up our engineering drawing skills 20 years ago, you retrigger those.
00:24:27
Speaker
And then finally, we designed something that is fit for the Indian market. It's not something that fit for a large farm in the US or Europe. Of course, we borrowed a lot of those principles. So when you look at a lot of PhD thesis available on these matters, we borrowed a lot of it, distilled it down to a very a farm in a box offering.
00:24:47
Speaker
for a smallholder Indian farmer. It included automated milking machines. It included things like milk meter that can measure the characteristics of milk as the animal is getting milk. It included early prototypes of a Fitbit for the cows and a handheld platform where you could actually enter all this data.
00:25:06
Speaker
Like an Android app. So it's company-based, like a Android app, right? So this is something that we took to market, took to Akshay Kalpa. You were like self-funded so far, like Bootstrap. You were using your savings. Yeah, correct. In 2012, we got funded by IT Madras because my co-founders at that time were either from IT Madras or IT Karatpur.
00:25:28
Speaker
So, Professor Ashok Junjanwala played an extremely supporting role. So, we would meet him whenever he's in Bangalore. He used to be on the board of several Bangalore companies like Saskia and State Bank of India and all of them.
00:25:45
Speaker
So whenever he used to be in Tobago, we should ride along with him from the airport to the city, and good that the airport shifted, you could use that time to get some good meetings. So then he said, look, you guys are trying to do something fundamental that is needed in the Indian agriculture. I think he used to be part of the Prime Minister's Advisory Council for Agriculture at that time, I think.
00:26:06
Speaker
So he said, why don't you guys get incubated or itemized? We have something called as an incubation cell. And we can also give you some money because you need a few more people to help you. We'll give you some. So they enabled some equity, soft debt altogether, maybe about 50 lakhs.
00:26:22
Speaker
they know kind of money that plus our own bootstrap savings each of us you know put in about 25 lakh each to that extent plus that 50 lakh plus we also raised some money from friends and family we went back to our colleagues and said we're trying something exotic and interesting.
00:26:40
Speaker
And given our track record and the people willing to bet their money on us, so we are eternally thankful for people who bet on us. So 50 lakh from IIT Madras, about one crore from sweat, and our own savings contribution.
00:26:59
Speaker
another crore from the friends and family, including IIT Madras, Alaminas, and our ex-Vipro colleagues. So we got access to a couple of crores of capital, which kept us going to 2013. So we were sort of IIT Madras-funded, friends and family-funded, self-funded till 2013.
00:27:22
Speaker
In 2013 is when I ran into Mark Khan of Omnivore, which was probably the only ag tech fund at that time. I ran into him at one of the conferences in Delhi and he got quite interested saying that we are ag focused and dairy is ag. I want to look at how we are early prototypes are working.
00:27:51
Speaker
What do guys do? So he flew down to Bangalore. He went along with us to some of the dairy farms where we were trialing some of our solutions. And he said, yeah, this seems to have a lot of legs. Is there something like a business plan that you have on how this can scale and all that? And that's when we did a few night outs.
00:28:14
Speaker
did all the work on the Excel sheets on, this is the total noticeable market, this is the promise. And finally, they did their first institutional fund in us in July 2013. So from 2011 to 2013, we ran with our own bootstrap capital, IIT Madras Money, and the friends and family money. In 2013, July, Omnivore gave us a check of about 7 crore at that time.
00:28:40
Speaker
which was the dollar was about 40, 45 those days. It was about a half million dollars, which felt like a lot of money those days. We said, yeah, we said, yeah, with this money, we should break even. But now I realize how wrong we were. We said, it's a lot of money. We should go IPO with that money. But then once we started getting into the market and solving the problem and our business models continuously shifting,
00:29:08
Speaker
right? Several mini micro pivots happen. Tell me about that evolution, that whole journey of finding the product market fit. Yeah. So very soon we realized farm-only approach is not working. Either the farmers felt that
00:29:25
Speaker
They all felt that right for several generations, they understand cows and make the best. Why should they buy for the tech? So we couldn't get the value-based pricing out of the way. And number one, in selling things in a retail fashion to these dairy farmers, we found it's not a scalable approach.
00:29:45
Speaker
Because the customer acquisition cost would be too high. Customer acquisition cost is very high. So much traveling. So much traveling, channel costs. And if it's an urban scenario, at least the ARPU, the average revenue per user is high. But the village scenario, how much can you ask a farmer to buy? And these are smallholder farmers.
00:30:04
Speaker
80 million smallholder farmer dairy farming families. That's roughly the size of the US population. But then how much can they pay? So we decided that value-based tech pricing in a retail fashion to an agri farmer is not going to work. And what pricing did you have at that time? Yeah, so we tried a per cow pricing. We said 200 rupees per cow per month. We tried a monthly rental at a herd level pricing.
00:30:32
Speaker
Okay. And you had to pay some telecom costs. I'm assuming because you have to pay for the telecom costs. These devices would have some SIM in it. Right. Correct. The food would actually send data to a central device, the solar based device so that you could multiplex multiple. So we used an unlicensed spectrum, you know, for that called a six low pan. All right. It's a power efficient, uh, uh,
00:30:58
Speaker
power efficient wireless mechanism called Sixclopan that was actually made popular by Google when they acquired Nest. That's very power efficient. This was like a Wi-Fi mechanism. Yeah, the Mac layer is actually 802.11. That's the Mac layer. It's just that the layer on top was more evolved for battery efficient working.
00:31:21
Speaker
and low power Bluetooth wasn't very commercial those days. In retrospect, if I do it today, I could have probably used BLE because low power Bluetooth is quite commercial and quite affordable.
00:31:37
Speaker
Those days, Sixflow Pan seems to be the choice that was the right choice to make. So it would send to a central part and that SIM cost would also kick in. And then how do I charge it to the farmers? I need to charge the hardware part, the cloud part, the communication part. So we tried various models, some CapEx, some ApEx, some cloud, some hardware, because there's a hardware element also involved.
00:32:01
Speaker
But we couldn't find the right model that would give us a flywheel effect and where we can scale rapidly. We knew the market is huge. There is 80 million smallholder farmers. 7.6% of our GDP was dairy.
00:32:21
Speaker
300 million cattle producing 560 million liters of milk per day. Milk is, if you consider milk as a crop, we knew it was the single largest crop on the planet. But how do you monetize this was a difficult thing because all of us were looking at it from a tech only angle. We were not looking at it from a business and commercial and a monetizability angle.
00:32:46
Speaker
Then once we figured that we're not able to get that flywheel effect going because of all the friction points.
00:32:53
Speaker
We stepped back and then started taking a supply chain deal. We said, look, I can't just solve the problem only at the farm. I need to sort of solve the problem of milk from the other to the consumer. Because finally, you and I, finally the guys who pay.
Supply Chain Transformation and Product Development
00:33:11
Speaker
If I give you an antibiotic free milk, you probably pay 10 bucks extra because you can very comfortably give it your kid at home or give it your pet.
00:33:22
Speaker
since you are the ones who are paying, I need to tap into your valid share. And then we figured out how to tap into your valid share. It's a farmer's valid share. Farmers should probably benefit from what you pay. And so then we figured that
00:33:39
Speaker
I need to take a supply chain view. I need to solve for this supply chain. And we figured that there are two components to supply chain. One is the market linkage part. How do I take milk as an output? And when the milk comes to you, I need to make a buck or two when Akshay pays extra for the milk. How do I get to that? How do I tap that loop?
00:34:03
Speaker
The second loop is farmers do buy cattle nutrition, soil inputs, feed, seeds, and a lot of things. They need capital to grow their own herd size. They need financial capital. They need insurance and all of that. So this is another part. And the agri-input results in that output, which is milk.
00:34:21
Speaker
So we said, these are the two points, two ends of the barbell where I can actually make money. And tech should power this. Tech should enable this. So we shifted from the mindset of trying to license tech and make money out of tech. Tech actually powering the supply chain and we monetizing the supply chain in a company, which is agri inputs and the market linkage. So that's when we stepped back and said, yes, I need to sort of build out my stack.
00:34:46
Speaker
which is a farm-only stack to make it a supply chain stack. And hence, from 2013 to 2014, we took one year to launch a product for the supply chain part, which is the collection center where you do trading and pricing. So we launched a product which could help you do grading and pricing and payment for milk. So when a farmer comes to sell the milk at a collection center, you could grade the milk, you could price it,
00:35:16
Speaker
And you would actually do a payment, a direct form of payment to the farmer's hands. So you're literally converting milk into currency, right? Then you figure that milk is perishable. The next part of this opportunity is cold chain. I need to optimize cold chain. Otherwise, if you're trying to make Kanazawa, great cheese.
00:35:32
Speaker
Your raw milk is not great, right? You would only get pizza-grade cheese. I'm not sure. You can't make another cheese. We said culture is important, right? And then we figured that till the time it reaches the plant, I need to maintain supply chain integrity because it's a very rural phenomenon. People can take good milk, pour water and all that, right?
00:35:49
Speaker
So we started launching between, once we figured that it's a supply chain play in 2013, we started launching products for all parts of the supply chain, the collection center chaining. So it took about till end of 2014 for us to have different pieces of enablers that take data from those parts of the supply chain, put it onto the cloud, and on the cloud, we start cross-correlating data.
00:36:17
Speaker
across the path, including the farm. And then the notion of traceability kicked in. So when we started, it was only a productivity and quality proposition. Then we said, now we have three pillars of value problem. It is P, Q, and T, productivity, quality, and traceability. Earlier traceability, and I'm using the term traceability very loosely here, right? It's traceability. How do I give you antibiotic free milk?
00:36:46
Speaker
How do I know that if you scan the QR code on the yogurt that you eat, how do you know that has undergone tests all throughout? It's just not an audit-based assurance. It's actually a test-based assurance. So that if you want to give pesticide-free milk, adult-trend-free milk, if you want to do cheese that has undergone certain tests along the way,
00:37:08
Speaker
How do I give the assurance so that when you scan the QR code on that pack of yogurt, on the pack of ice cream, you know that the ice cream, the milk's journey has been, right? You should virtually be able to trace it back to its roots, which is the farm or a cluster of farms and say, yeah, something goes wrong. I know these are the group of farms that contributed to that good thing or the bad thing, right? So traceability became a very big thing. And that we found was very nicely monetizable.
00:37:36
Speaker
So, were you making these products to become a supply chain player or to sell to supply chain companies like this dairy? To sell to supply chain companies. That was another mini-pivot, right? So first we started with, once we figured that supply chain is the way to crack it, initial part of the journey in 14, 15, even right up to 17, 2017,
00:38:03
Speaker
was about trying to sell the supply chain components to the dairy process and say, look, we will give you tech that can help solve for PQNT. You could then use it to launch antibiotic-free milk. You could then use it to launch dynamically traceable milk. So right up until 2018, well into, in fact, right up to
00:38:29
Speaker
just before COVID kicked in, it was all about trying to sell the supply chain for five years we spent in selling these tech so that someone else can use it, right? And that's when we figured that it still had friction. The friction point was that majority of the dairy processors in India look at milk as commodity.
00:38:49
Speaker
They don't look at milk as nutrition. Their margins are very wafer thin. Commodity margins are very wafer thin. If they try to sell something that is premium, it would cannibalize their commodity business because high volume low margin business.
00:39:11
Speaker
They still didn't have the mindset, not the business model, to sell differentiated products. It's like, basically, if you've been running a no-frills aircraft for a lifetime, you just can't think of a Vistara. You just can't think of the Vistara model. And the people who are willing to see value in it are very niche, like an organic milk company.
00:39:35
Speaker
That could be let us scale, organic built is a very small sliver, right? Yeah, maybe single digit percentage. Single digit percentage or even lower. So we figured that
00:39:46
Speaker
until we launch our own business operations, right? And demonstrate how this tech stack can be used to power a brand like an ITC or a Coke or a Britannia who have the brand to sell nutrition into the market, branded nutrition into the market, not just commodity milk, right? We need to do that because someone like an Amazon fresh or a sweet here as a matter.
00:40:11
Speaker
They wouldn't want to sit in Begusarai, Samastifur, Mungir and run operations and procurement. They want to take great quality milk into the market in the form of cheese or butter or whatever. And then they would use the BB Royal brand if you have a big basket. They would use a fresh-to-home brand or a delicious brand to sell that branded product, branded dairy category into a consumer.
00:40:31
Speaker
So then in 2009, before we come to this pivot, I'm slightly going back a bit. So these individual devices that you made for the supply chain, can you go into detail on those? Say you made a device for grading of milk, how did that work? I want to understand how you went about building each of these.
00:40:54
Speaker
Absolutely. So for grading the milk, typically the milk is graded using an ultrasonic IOT device called a milk analyzer. The milk analyzer would take a sample of milk and take the sample of milk, it would give out electronically.
00:41:15
Speaker
It could tell you what's the percentage of fat content, what's the percentage of SNF, is there any other transities, is there any somatic cell content in it. It would give you all those data. So we get the data out into our IoT router and the router sends it to the cloud.
00:41:30
Speaker
And in the cloud read-run analytics, how is the farmer's milk quality trending? And how do I cross-correlated with the data coming from the farm? At the farm, if there's an antibiotic intervention, this particular farmer's milk would be collected separately in a separate can.
00:41:47
Speaker
So we would maintain a mapping of cow ID to farmer ID mapping and farmer ID to sample ID mapping and the sample ID would tell you what the sample readings were. And then the dairy process would decide, okay, if the sample quality is X and the quantity is Y, I can pay him this much money.
00:42:06
Speaker
This is like a UV scanner? You would actually need to take a sample from the incoming farmer's milk. It's a small sampler. I need to fit the sampler into a milk analyzer. And then the milk analyzer would suck a portion of this milk in.
00:42:26
Speaker
And using ultrasonic technology, you should come back and tell you what the quantity is. Today, of course, things are more done. We're trying to see if we can move to a spectral analyzer, which is more powerful. Those days, ultrasonic itself, IOT, IOTifying and ultrasonic sensor is itself a big thing. But today, the analysis has moved to, can I do this using spectral analysis?
00:42:50
Speaker
at a very affordable village level. So that village level analysis can be done at affordable spectrum. So we're still exploring. So spectral analysis will give you more data as compared to UV? More data more quickly, can give you more data more quickly. And you can measure a lot more. The spectral signatures can detect a lot more things far more quickly because ultrasonic can at the
00:43:16
Speaker
at the, at the, at most tell you one or two or three things, fat, protein and all that. Whereas spectral fingerprints can give you a lot more things, how much of urea was added. Okay. Okay. Let's give you like a complete chemical composition. It's like a blood test result in fact, how much of vanaspati was added to beef up the fat content.
00:43:38
Speaker
It could catch because ultrasonic sensors had a limitation in that it could only give you primarily the composition of milk. It couldn't give you the complete adulterant and contaminants of the milk. Whereas spectral analysis can do a lot more quickly. But even today, the commercialization of this is still taking a while because it's still expensive. I need to make this work at a village level, not at a lab level.
00:44:05
Speaker
Why is it convenient for a blood test? Because it's a lab level function. And I can amortize the cost across thousands and lakhs of people walking in. There's a village where only 100 farmers walking in, right? So the costs have to sort of working at it. So that we're trying to see, can we now use those innovations sort of here? So that's basically how that piece of the technology works. What other components did you develop?
00:44:34
Speaker
Yeah, so that was one. And the second was that there are several peripherals at a collection set. For example, there is a simple, old-fashioned bank scale. The bank scale data has to come wirelessly to us so that the quantity can be measured through a bank scale.
00:44:52
Speaker
And then we put a disparate device at the correction center so that all the farmers standing in the queue as a transparent view of how much the other farmers, how the other farmers are performing so that there becomes a healthy competition among the farmers. If that farmer is getting 10 rupees because milk is where, I should probably do that. And then we introduce the notion of an ID card for the farmers. And if the farmer walks in, you scan his ID card.
00:45:16
Speaker
So that uniquely, you could identify that farmer and you set a unique ID card. So it became a unique farmer ID. Internally, we could actually map it to another system. We could map it to a mobile number and all that. But externally, it's a simple ID card. So the farmer's loyalty to the dairy improves and all of that. Milk quality assessment, weight assessment, transparent display of whatever is being performed there.
00:45:42
Speaker
And finally, on the cloud side, integration with the back-end payment systems. Because the farmer would have some bank account. How do I do a DBT, direct benefit transfer to the farmer's account? So that's where our fintech part of our business took off. We then realized that in India, we disbursed about $25 billion worth of payments to the dairy farmers every single year. So there is money made to be made on payments. Money can be paid and made on lending to the farmers.
00:46:12
Speaker
So, it opened a whole new vertical, which today we call as Moopay. We never had an idea that it could result into that. But when we started to identify payment data, it can result in payment.
00:46:29
Speaker
And then we started seeing payment data. We said, yeah, payment data is helping us get into the lending space. And hence, we could start. So it gave rise to a whole new vertical internally, which today will drive us a separate vertical, separate subsidiary internally. So that was one measurement that we did at the collection center. At the chilling center, which is the next part of the supply chain, we started measuring
00:46:56
Speaker
using a volume sensor, we started measuring the volume of milk. How much milk is there in the bulk milk cooler? In the middle of the night are people pulling out good milk and adding not so good milk into it. So there's a sudden fluctuation volume that some hankie-pankies happening in that milk.
00:47:11
Speaker
is the milk getting under chilled or over chilled, so we integrated and integrated a temperature sensor into it. We integrated a mechanism to measure the energy consumed because in India, we still spend about half a billion liters of diesel every single year to chill milk, right? Because not all of these villages are electrified. You don't run it on, we probably consume about 2 billion kilowatt hours of energy in chilling milk.
00:47:36
Speaker
How do you optimize it? Though our primary focus is on quality, there are other practical benefits like can I chill more in an energy efficient manner? Can I contribute to the carbon footprint emission reduction? I burn less diesel to chill more milk. We integrated about five, six sensors to ensure that the cold chain protocols efficiently in a monitor.
00:47:59
Speaker
Since we are also measuring the quality and quantity at the collection center on a performer level, when that milk comes in into the chilling center, if at an aggregate level, it doesn't add up to the performer level measurement, we know that along the route, some issue has happened, someone has removed. You could actually in real time catch the issue.
00:48:21
Speaker
penalize the right person, saying that your can is supposed to have so much, but when it came, it doesn't have so much. So I'm not going to accept the scanner. I'm only going to pay you so much. So since you're catching these things in real time, people's compliance goes up quite a bit.
00:48:35
Speaker
We call it supply chain integrity. So we started measuring some of those. And then once finally that milk goes out from the bulk milk cooler where milk is actually chilled into a milk tanker, you again maintain the mapping. Which bulk milk cooler's milk has gone into which tanker and which tankers, which compartment so that finally when the milk reaches the plant,
00:49:00
Speaker
you know for sure that what you're accepting is what the farmer actually poured several hours ago in a remote village. So all of these measurements started coming to our cloud, which could help us finally tell how do you improve productivity, quality and traceability.
00:49:16
Speaker
As I was saying, right up until 2019, again, before we come to that pivot, you must have been co-building these components with dairy customers. You must have got some paying customers with whom you were co-building these components.
00:49:34
Speaker
Absolutely. So the supply chain business was quite a compelling business. It still is selling tech to people who run supply chains. We have deployed our systems in about 35,000 points of presence in India. These are 35,000 villages, right? And these are real remote villages. We have about 300 people in the company whose focus is to provide support and maintenance for these deployed hardware.
00:50:03
Speaker
Right. And these are deployed in almost all the dairy companies in India, right? We pick the large cooperatives, Amul deploys it, Nandini and Karnataka deploys it, Sudan will be hard deploys it, Britannia deploys parts of it, ITC deploys part of it.
00:50:21
Speaker
hadson deploys it several large and small derivatives so we have about 250 dairy process in india who deploy our systems right this was this was a result of these deployment that happened between 14 2014 and uh 19 and and but our whole point was this index this was this was not growing fast enough or like you know it was it was still growing but we always knew that
00:50:48
Speaker
given our telecom and app and app store background, we still knew that this digital access network is still the platform piece. The flywheel million monkey please impact is still not taking over. So we're always looking at ways in which this digital access network that we've built across the dairy supply chain, which is deployed across
00:51:15
Speaker
35,000 villages, how do I get the flywheel effect to sort of begin? And who will pay for those value-added services? If the dairy processor for whom is applying technology, if they themselves are making, let's say, 30 paise per liter, how much will they pay for the tech part?
00:51:36
Speaker
If I want to make a lot of high-value margins, I need value-added services to kick in, and the value-added services payment has to be taken care by you and I paying more for it.
00:51:53
Speaker
So that's when we figured that in 2018-19, there's sufficient growth happening, but I couldn't shift the margins significantly higher. So we shifted from a horizontal land grab business model, which is keep adding more and more farmers, keep adding more and more milk flow. We were at that point digitizing about 13 million liters of milk flow per day.
00:52:18
Speaker
By virtue of which we were probably the second largest in the country after our milk, the amount of milk flow that we get to touch on a daily basis. But it's just that they get to touch it physically, we get to touch it digitally. But this was not your milk flow. This was like your customer's milk flow. Exactly. It's customer milk flow. But just that we grade and price that milk flow. We ensured the supply chain integrity for the milk flow, but it was not our milk. It's someone else's supply chain.
00:52:47
Speaker
And all the 13 million liters of milk flow that we were touching at that point were predominantly being sold as commodity milk. So I couldn't get the flywheel effect kick in. I couldn't get the margins kick in. And we knew that we had enough volumes so that when we can sit back and say, OK, I'm the second largest in the country today after a month.
00:53:10
Speaker
That's when we started getting towards the next part. I wouldn't call it a pivot, but we figured that the only way to get the operating margin part to kick in is to get more and more vertically integrated so that I have to get more vertically integrated.
00:53:31
Speaker
I have to become the Uber. I just can't be the guy who's giving the taxi to the Uber. I have to become that Uber, where Uber gets paid for every hail, or Ola gets paid for every hail.
Vertical Integration and Farmer Support
00:53:46
Speaker
I need to get for every liter. The only way to do it is getting more vertically integrated, where I need to run the business operations. And then go back to this dairy and say, hey, look, why are you actually running your operations?
00:53:57
Speaker
I exactly run it for you. You have built a brand. Why aren't you better off leveraging the brand and then selling it? And by the way, I'll help you launch multiple brands now. One can be antibiotic free. And by the way, if you're Britannia, your brand is well recognized in India, right? And you might actually want to do it. So we would actually be your backward integrated player. I would be your Intel inside. You become the Dell, right?
00:54:22
Speaker
I would become your tetra pack, you become the Tropicana. That became the pitch, which was really well accepted by the market because almost every FMCG player, almost every D2C direct-to-consumer player wants to launch dairy as a category.
00:54:39
Speaker
But there's no clue in how to launch a differentiated product that you and I will need to pay for more. And even if they're new, for them sitting in Begusarai, Samastipur, Mungir, Sharanpur, Chanyat, Sandoli, and procure that milk in the remote villages which is next to a forest in a tribal area and bring it to your Mumbai city or Delhi or Bangladesh, virtually unthinkable, right? But we have sort of done that for the last 10 years, right? And we have visited
00:55:08
Speaker
thousands of these villages now. We have 800 people today who eat and breathe milk in these villages. So it becomes like a very good offering on the plotter for an FMCG brand who is now trying to launch these differentiated products to this aspirational India. So we have about 25 to 30 million households in India that contribute to 65% of the FMCG value.
00:55:36
Speaker
We are the guys who are willing to pay a shift from maybe Maruti to Toyota or a Civic or a Civic to something else. We are the guys who are willing to pay a click and buy something that is antibiotic free because we think our kids
00:55:56
Speaker
We are the kind of people who would buy tetra pack milk. At least the guys might pay 10 bucks more per liter. In this industry, 10 rupees per liter is a huge amount of money because you operate to millions of liters. Because the good part about India is almost the entire 1.3 billion people consume milk, in some form or the other. So on one end, you have 80 million farmers producing this milk. Other end, you have 1.3 billion consumers who consume this.
00:56:26
Speaker
We sort of said, we'll become the digital proxy to enable connect the two. 80 million farmers on one end. You'll build the pipe, basically. We'll build the pipe and it becomes a, we'll build that multi-service supply chain. That is, I'll build a supply chain on top of which you could run a Deccan Airways or you could run a Vistara. Obviously, our preference is to run a Vistara.
00:56:48
Speaker
everyone will buy. Not everyone offers first-class passengers. You'll have economy class, you'll have economy plus. So we will build that pipe wherein you could take an economy class trajectory, extra legroom trajectory, first-class trajectory, and a business class trajectory.
00:57:05
Speaker
You decided you want to build the pipes. So this would mean that you would then start paying the farmer from your pocket and then you would sell it directly to a Britannia, take the money from them. That whole money would flow through you. Exactly. I mean, this is when we figured that one, since I built the pipe,
00:57:28
Speaker
I'm building the highway myself. I'm building the infrastructure. I better enable people to sell differentiated products. And these are people who either to had the muscle bar to sell differentiated products, but didn't have access to the raw material. I enabled them with the raw material. And second, this also gave rise to an option where to make sure that the pipes are efficient. I need to make sure that the small holder farmers can't remain small holder.
00:57:57
Speaker
They need to ship from a 5 liter orbit to a 200 liter orbit.
00:58:02
Speaker
For that, they need all the inputs to do that. And these are farmers who didn't have access to all the inputs. But why did this matter to you? Because the supply chain efficiency goes. Yeah, that's when our unit economics will look better, because I would rather collect more amount of good milk from fewer number of farmers than large set of farmers. So my supply chain efficiency improves. But you have the second place. It doesn't matter much.
00:58:29
Speaker
It's taking place, but since I'm also taking on the operations now, because I'm building the pipe, I'm running the operations, I would rather, on a per head basis, I would rather make sure that every personnel is able to handle 1,000 liters of milk, 100 liters of milk, so that I'm able to better leverage my fixed and variable costs. My unit economics will start working better.
00:58:55
Speaker
For these farmers to make the unit economics work better, number one, they need access to capital. Because otherwise, they don't get loans from a state bank of India or an ICICF. To buy cows. To buy cows.
00:59:12
Speaker
How do you underwrite risk? They don't have a credit history. So we started using the data to develop things like a moose score. We came up with something called a moose score that helps you assess the farmer's credit worthiness better. Because 60% of the farmers have never taken any form of loan, any form of formal loan.
00:59:33
Speaker
We are actually trying to patent it. We have actually six or seven patents. How do you score a farmer on creditworthiness? Is it on consistency of output? Right now, what we do is we get an assessment of the milk quality. We also get an assessment of the farmer's cash flow because we know how much you pay the farmer.
01:00:00
Speaker
So the cash flow becomes pretty important to decide, do I give you a 10,000 rupee load or a 30,000 rupee load? I get an indication of your loyalty. I get an indication of your churn. And then I also get an access to the asset data. What is a farmer's biggest asset? It's its cows. I get the asset data. And then I also get a field for a psychometric because I know if the farmer, how compliant is he to the vaccination protocol?
01:00:29
Speaker
how compliant is he to where he's at. So he's a little more progressive from a company. So I use a combination of this data to decide, one, what kind of a loan product can he absorb? When is the right time to give him a loan? And what kind of a risk I'm taking? So that's broadly how this Musco works. And today, I have partnered with a whole bunch of banks where I actually do almost end-to-end risk underwriting. But I'm sort of a business correspondent of that particular bank.
01:00:58
Speaker
And farmers get access to more formal credit. And banks get access to these new set of borrowers who they never had access to. Which would help banks meet their priority lending quotas. Priority lending goals and all of that. And these are not SAG loans. These are not microfinance loans. We get to see the farmer every single day, twice a day.
01:01:20
Speaker
Because milk is a daily velocity product. It's not a seasonal product like potato or tomato, right? If a farmer doesn't turn up into a collection on a particular day, someone gives him a call saying, hey, what happened to you, right? So it's not like I get to know that the end of the month he has not repaid and hence there is some issue.
01:01:36
Speaker
Right, so we are able to help underwrite, it's sort of a lend and monitor type of an approach. Yes. Not a lend and forget kind of approach. Yes, yes, yes. I'm also able to monitor the deals. And probably you are able to do the collection from what you're paying him, like some percentage. Yeah, exactly. So it's almost like you're having access to the farmer's salary account.
01:01:55
Speaker
I'm able to detect things from the source. So this is how this entire scenario works. Initially, when we started, we had no clue. But then we realized we have all this data. We have the moose core kicking in with the payment data and all that. So that gave rise to four new billion dollar vertical types internally, which we're trying to nurture, which is like a FinTech
01:02:16
Speaker
vertical. And then the market linkage is another vertical where we go to the Britannias, I teases the world or Amazon's person, they call the cokes of the word and say, I cannot be launched by the milk, but a cheese, but a paneer or whatever. And then you had the agri input in a part of the business where I figured that these farmers also need nutrition, animal nutrition, right? If the farmers, so I started partnering with a lot of this agri input providers with cattle nutrition being the first one.
01:02:43
Speaker
where we said we make some commission from selling agri inputs in the farm. So now I have three revenue generating streams, which we had no visibility to when we started. One is, of course, the tech block, which continues to power our own capital supply chain and third party supply chain. Then you had the FinTech block for payments and credit.
01:03:10
Speaker
Then you have the market linkage block, where I take milk to a Britannia or an ITC or a Parley or a Coke or a Swiggy. And then at the agri-input part, where I'm partnering with folks like Nutrico, which is, for example, our Dutch nutrition provider, who used to make very high-end cattle nutrition products, which our Indian smallholder farmer never had access to.
01:03:34
Speaker
Now suddenly, the Indians followed a farmer to have access to a Western European cattle nutrition product. And some like a nutrico, who actually came on board as an investor recently, suddenly have access to all of these farmers. And they don't have to worry about how to collect the money back because they can collect the money. So these are the four towers that currently we have given a rise to. And they are very interrelated.
01:04:03
Speaker
Because at the end of the day, it's market linkage. But to ensure that my differentiated premium market linkages work, I also need to provide agri inputs, including financial services. Otherwise, my supply chain is inefficient. And then tech has to power all of this. Otherwise, it's going to look very brick and mortar.
01:04:24
Speaker
Milk is an incidental outcome of a well-designed digital supply chain. It's not a dairy product. It's an outcome of it. And since it's a digital highway that we have built, now we cannot think of what else can I do? Can I bundle insurance with credit?
01:04:41
Speaker
Why not give other soil inputs like fertilizers and other things to the same dairy farmer because the same dairy farmer also is growing other cash crops. So now that we have this digital pipe built in and we have the model built in for agri inputs and this output, I'm trying to get more and more vertically integrated and this is where my flywheel has started ticking off. I'm now seeing that
01:05:04
Speaker
my revenues have started spiraling up because it's just not the tech licensing SaaS revenue. That's just one component of it. I have the commerce revenue kicking in. I also have the unit economics kicking in, the contribution margins kicking in, mainly because I'm able to leverage my fixed cost and the variable cost much better because India being India,
01:05:28
Speaker
Different regions behave differently. Eastern UP behaves differently from Kohler. Unless I perfect this cluster model and make sure that each cluster is thinking demand backwards, the demand backward thinking becomes extremely important. What is demand backward thinking?
01:05:48
Speaker
Do you know what backward thinking is? If I know that Coke wants to launch antibiotic-free milk in Bangalore, I need to have a modular cluster that supports that customers in Bangalore because Bangalore can pay for it, but maybe e-road may not be able to pay for it. Typically, in India, the traditional dairy supply chains have been built with the supply-forward thinking.
01:06:13
Speaker
to solve for the availability problem and the quantitative sufficiency problem. I still remember standing in queues to buy milk. Because availability problem itself was a big deal, but now that the availability problem is solved by building the supply forward supply chains,
01:06:33
Speaker
time has come to think, demand backwards, what type of milk, what product, and who are the consumers who pay 10 rupees extra for that product, right? There could be cheese lovers in Delhi who swear by buffalo cheese, milk cheese, right? And they are willing to pay, why 10 bucks, even 50 bucks more, you know, for that cheese. How do I build backwards from there?
01:06:58
Speaker
Hence, an Ashirvat brand is well known in all the cities. But why isn't ITC Ashirvat having dairy as a category in every city they operate in? Why is it they only have auto? Why is it that they only have pulses?
01:07:12
Speaker
It is just that they don't have access to these modular supply chains, we can help them pan India. And if you're an Amazon fresh or a sweetie or a bb daily, you would rather want to launch a product in 20 cities because all the 20 cities are pockets of backdoor like customers. And hence, I am able to tap into that in one row. So that's what I mean by demand backward thinking.
01:07:32
Speaker
wherein I have a very modular cluster build out because of the tech I'm able to build out these modular clusters, right? And then help these brands power a differentiated milk sale to those consumers.
01:07:43
Speaker
So who was your first customer to whom you started selling milk? And how many liters was it when you first started selling? How many liters do you sell now? Where the whole pipe is through you? Yeah. So right now, when we started, it was virtually unheard of customers. We used to, as you build it, we used to take it to a local Horeca segment.
01:08:09
Speaker
And this is not by what I come in a hotel restaurants and catering, right. And these are not even large what I can change like coffee does Starbucks, this would be some local guy because we had to get some basic volumes right but the whole point is, if
01:08:25
Speaker
It was raw milk. It was just raw milk. So we would run the logistics. We would take it in tankers. Tankers should go and hand it over at a tanker level or at a can level, right? You'd have these data A's like vehicles taking these in cans and handing out the can levels. And the whole point of this Horeka segment is important for us when we started was that
01:08:49
Speaker
If Coke were to be a customer, the day one requirement would be 30,000 litres, right? How would you sell 30,000? But day one, I would only get 5,000 litres, right? So I could sort of dispose of this 5,000 litres to a local, you know, Horeca, because they make 5,000 glass of tea and coffee or 10,000 glass of tea and coffee. Until my supply side scales, I just can't get. So my first set of customers were highly fragmented sort of Horeca.
01:09:14
Speaker
And what was the value prop for them? Like better quality or better pricing? Yeah, better quality. You could actually make more cups of tea and coffee with our milk. Because there's a rich in fat, better yield and all of that. And they would pay us more because they have seen.
01:09:32
Speaker
Yeah, it could be a sweet maker who makes koa. And he would tell, yes, koa is the base for most sweets in India. So they'd say, yes, I'm actually getting more koa out of your milk. So I don't mind paying you extra, kind of stuff. And then we started latching on to several big ones. So ITC became one of our big customers. So today, as we speak, we are doing about 40,000, 45,000 liters of milk flow per day.
01:10:01
Speaker
When we started to reach a total sales of 1 million liters, which we started in July 2020 at the peak of COVID, we took about 250 days to touch a total of million liters of milk. Today, we are probably doing a million liters every month. Every month, yeah. Every month. By the end of this financial year, by March, we'll probably do anywhere between a million liters every 7 to 10 days.
01:10:31
Speaker
and our aspiration is to save a day every three to four months, which means in about 21 to 28 months, I should get to a million liters every day, right? And then, and we are, you know, if a supplier ramps up at the speed at which it should, it could then, we are in advances or discussion with several FMCG companies, including D2C companies like Zometo, HyperPR,
01:10:55
Speaker
Swiggy Super Daily, Amazon Fresh and all these guys. All of them who want to launch this differentiated product. Are you still selling through like tankers or do you also do packaging?
01:11:09
Speaker
Packaging. So we have started doing some bit of packaging. Our whole idea is you want to do this fairly end-to-end. Because Big Basket would want packages branded, ready to sell. Exactly. Because Big Basket would pick a product, let's say, from a dark store in Jeppi Nagar or Kormagalai in Bangalore. They wouldn't want to do anything until we reached that point. So we have to manage this entire cycle right up to that point. And then they would sell it maybe as a BB Royal Cheese or whatever.
01:11:39
Speaker
Are you processing also? Are you making cheese also? Cheese, we have still not started. We have started doing a little bit of paneer. We have started doing a little bit of yogurt. We will start doing a little bit of flavored milk shortly. Cheese is still not on the cards yet. We will probably start doing a little bit of ice cream. You are setting up your own processing unit or is it like third party?
01:12:06
Speaker
Fundamentally, we are taking third-party plants on lease, so that it's sort of an asset-like model. So you're not investing in the land machinery, but you're operating it. Correct. We will take them and run it on a per-month model, a rental model, or a per-liter model, and then start. We think we will start doing more and more value-added products, because finally, India is actually moving from a drink milk society to an eat milk society.
01:12:35
Speaker
compared to Europe where 90% of the population eats milk by way of cheese and other things. Only 10% drinks milk. In India, it's almost the other way. About 75% of the population still drinks milk.
01:12:51
Speaker
25% sort of eats. We think it's going that way because as the GDP of the country improves, people can pay more and more for, paneer is a very good protein. As a protein consumption improves, over time, we think it'll shift more and more. So we think we have to get into more value-added products because these FMCG companies, with the good part about fresh milk, it's a daily velocity product.
01:13:17
Speaker
They land up and you get to see Amazon Fresh in front of your doorstep every single day, which is good for Amazon Fresh because they're in your face every single day. That's a daily. But then you also would occasionally buy paneer, you also would occasionally buy cheese, and you don't mind paying more because it is almond flavored or whatever.
01:13:38
Speaker
So that's where you make your margin. So we are working on the entire portfolio. It's almost like a portfolio management, which consumer needs what kind of portfolio at what point in time, where milk is at daily velocity, but then you also have all these weekly, monthly, quarterly buyouts as well.
01:14:02
Speaker
ITC doesn't sell milk, they sell ghee. No, they do sell ghee in up north. They do sell a lot of milk as well. They sell it in the Swasti brand.
01:14:12
Speaker
They sell fresh pouch milk. It's called pouch milk. They do it in East today. Right now, I think they have their fancy, the chances of becoming the Amul of the East. They do that. Parle wants to launch its flavored milk. We would want Power there in a brand as well.
01:14:39
Speaker
Zamata has a two-pronged strategy. They would like to first supply milk and value added products to their restaurants and cloud kitchens, to the hyper PR access, and then eventually also selling direct to consumer as well. And all of us know that folks like Coke and Pepsi do want to get away from the sugary drinks to more nutritional drink.
01:15:04
Speaker
talking to them. So for us, demand has not been a problem. And I think we are now trying to ratchet up our supply, because at 45,000 liters, we have maxed out. We can't give more. I need to now deploy these pipes, the cold chain components great to price and variables and all of them.
01:15:33
Speaker
across the chain. That's the reason we've just raised a total $20 million type of a round right now. That's powering it. This is the next raise after you did that raise in 2014. This is the next one or between 2014 to now? In 2013, we did the raise from Omnivore. That money we used to... The 7 crore raise. That's the 7 crore
Global Expansion and Industry Dynamics
01:16:00
Speaker
raise.
01:16:00
Speaker
And then subsequently, of course, they did an add-on raise of another 10 crore and all of that. But all of it was done by Omer. They also probably felt that they gave us too little of money. So they gave us some more. In 2015, they gave us some more. In 2016, they raised a bunch of capital, about 14, 15 crores from
01:16:24
Speaker
a combination of Bini Bansal. He used to be the CEO of Flipkart. He put in some money in 2016. Bloom came in. They normally do early stage companies. They were one of the earliest investors, a runner that got acquired by Zomato. Taxi, for sure, got acquired by all of them. They came in there. Then we had a 500 startup who came in. It's a very prolific investor.
01:16:53
Speaker
Then we had a couple of Japanese investors who came in like PNEXT and RMSEED. And then we had another interesting company investor called Venture Highway, who came in. Venture Highway used to be run by Samyushruth and Neeraj Arora from Google and WhatsApp respectively. So these guys together, all put together, gave us about 14, 15 crores that helped us get our business to supply tech to the supply chain companies.
01:17:20
Speaker
In 2018, we had a couple of more interesting guys come in. We had Indesage, which today is called Celesta, come in. Again, a valley-based fund, but have an Indian presence. Gates Foundation came in. We were the BMG of the Gates Foundation's first ever equity investment in India.
01:17:40
Speaker
Of course, of course, they've invested in people like 1MG, which got acquired by Tata. I, in fact, met Bill in 2016, Bill Gates in 2016. We were one of the four companies which presented him. So I had a minute exclusive slot with him. Amazing. Which was a good experience. Full circle, like way back in... Yeah, exactly. In 1997, he inspired you to become an entrepreneur. That's correct.
01:18:04
Speaker
Exactly. He liked what we did and then their investment team invested in us after all the due diligence and all of that. Then we had ABB technology ventures who came in at that time and then Qualcomm because there's a whole bunch of telecommunication and the IoT involved. They came in as an investor as well. These are the investors who came in then.
01:18:29
Speaker
Right now, we just closed around, this was in 2018, a few couple of months ago, we rose around the NutriCo, as I mentioned, because the commerce part kicking in. And we are just about to also get someone like an IDH farm fit to close this round for us that it makes like a total $20 million in a type of round.
01:18:49
Speaker
They're like, the ideas form for it is like the Gates Foundation of Netherlands. Because no matter what, so we get a lot of undeserved attention for changing lives, right? That was not our focus, but we landed up solving the problem.
01:19:07
Speaker
I call it undeserved because I wish that was where we started, but we landed up in that sector. But so we get a lot of impact. Because we changed lives, 80% of the dairy farmers are women. We are improving farmers' income.
01:19:26
Speaker
we are reducing carbon emissions because if animals produce more, carbon emission goes down because with fewer number of animals, you're able to produce more amount of milk. So you're reducing methane gas emissions because animals produce methane gas by way of regurgitation, flatulence and other things, so you're able to reduce that, right? Almost 60% reduction we're able to show. But all of those impact metrics were purely coincidental. I mean, it was not taught. It's a byproduct of
01:19:56
Speaker
IoT journey that eventually started up becoming an FMCG journey. So we're able to attract a lot of the impact investment because we're able to show income increase of an order of magnitude for the dairy farmers who come on our supply chain. Because you pay 100 bucks for high-end milk, it eventually has to flow back to those farms. And my fintech is
01:20:23
Speaker
taking it to the next level by making a 5-cow farmer to become a 10-cow farmer because the state bank of India or the ICC bank can't give them loans. We see them every day. That way, they're able to improve farmer income. They're able to
01:20:39
Speaker
and give them market linkages. We are able to give financial inclusion. We are able to ensure that if you are a women farmer, you get better interest rates. Because women farmers repay better. They don't go get drunk at the end of the day kind of stuff. So we are able to get all of those. You're able to educate farmers with your app. Like the app would be giving them nudges on best practices. Exactly. Do this, buy this nutrition. I'm actually giving you a European-grade nutrition. And it can help you get more milk and all of that.
01:21:09
Speaker
Gender, financial inclusion, carbon footprint reduction, and income improvement, right? These are the metrics that we touch. Hence, we're able to impress upon folks like IDH FarmFate or Gates Foundation, and Arum Seed from Japan to say, hey, look, it's a hard problem to solve.
01:21:32
Speaker
It's not a food tech in the city. It's not a platform or a marketplace that is urban-centric. It's not an urban-centric tech platform. It's a hard problem and we need more patient capital.
01:21:46
Speaker
So we're getting that kind of investors, we're getting some really marquee investors like Qualcomm and ABB. And then you also get pure financial investors like Indesage and Omnivore and Bloom and all of it. So it's been a good mix on the table.
01:22:03
Speaker
We are in the market to raise more because this is, as I said, $225 billion industry. Three times the size of the telecom market in India. I don't know if you knew that. There is three times the type of all the telecoms put together. You have half a million milk collection centers in India.
01:22:24
Speaker
That's three times the number of post offices that exist in India. So it's a massive segment. And I think if we get enough capital, we can also replicate this blueprint globally as well. Because milk is milk is milk throughout. Your cows produce milk, people eat it or drink it.
01:22:40
Speaker
The idea is, how do I take this Made in India blueprint to other countries? It could be Indonesia, Southeast Asia, Bangladesh. We interestingly had a subsidiary in France as well. We were actually incubated by business France in Normandy, just according to Michelle, where they said, look,
01:23:02
Speaker
Why don't you try to replicate some of this in Europe using France as a base? By the way, Europe and France are well-automated but not digitized, right? So why don't you use this blueprint, adapt it? And we like the concept because in Europe, people can pay more.
01:23:18
Speaker
But then we realized that it needs more capital because the cost structures are more expensive. So we said, look, people heavy business, like you need a lot of people heavy business. Exactly. People heavy business. And either we need a partner who OEMs and adapts it there, but then runs the operations themselves.
01:23:40
Speaker
But all of this needs capital. We decided, look, let's make the unit economics work in India. Let's hit the bar out of the park in India. And then if you get enough capital, we'll start replicating this blueprint elsewhere as well. So that's the journey where we are right now. So it seems to me that Derry is a
01:23:59
Speaker
supply-driven industry in the sense that demand is not a problem. Supply is the problem. If you can get supply, you can sell. As you increase your supply, wouldn't you be competing with the customers of your SaaS or your pure tech offering like the other dairy companies who are just deploying your technology? Wouldn't you be competing with them for that same supply?
01:24:20
Speaker
Yeah, no, no, good question. Good, you are able to see through that actually. So what happens is that the way this dairy supply side is split, right? About 25% of the milk is in the organized segment. 75% is still unorganized, right? Okay, like that doodwala, like on the motorcycle, like I used to live in Noida. They used to be these guys in motorcycle coming to apartment complexes and
01:24:48
Speaker
Like, you know, exactly. Exactly. Glass by glass. Absolutely. I mean, so the 75% is, as you said, the guy coming in the bike to your home, the guy selling to the local sweet shop, the guy selling to the local marriage halls, or even domestic consumption and all of that, right? Only 25% is the one that is coming through the Amul network or a Moomark network or a Stellabs network, right? 25%.
01:25:13
Speaker
So thanks to the pioneering work done by folks like Amul, you at least have 25% of this in the organizing. Look at fruits and vegetables. Fruits, vegetables, pulses, and all the other agri products, less than 5% is in organizing. There is probably the crop where you have five times more in the organizing segment than rest of all agriculture put together. And I would give credit to Amul for actually having pioneered this cooperative
01:25:40
Speaker
which other cooperatives picked up. And even private dairies have adapted these models for their benefit. So when we go into a village and compete for the supply side, you have enough headroom there to compete on the unorganized side. That's number one.
01:25:59
Speaker
Number two, this industry is known for its cohabitation. So what we've seen is while Nestle procures milk up north in Moga, down south, Heritage actually processes and procures milk for Nestle and their own brand as well. So we have seen that cohabitation is OK. As long as I'm not competing on the consumer side or the supply side, depending on who has what access, that's OK.
01:26:27
Speaker
Number three, do remember that our gravitation and orientation is to work with brands who do not have any inclination to get onto the supply side as long as they can get assured and traceable supply. The Amazon freshers of the world, the Britannias and the ITZs of the world.
01:26:49
Speaker
who have invested billions of dollars in building a brand and distribution network.
Future Outlook and Strategic Growth
01:26:57
Speaker
They would rather leverage that than fight the battle on the supply side with the farmers and the tech and all that. But we fancy our chances there.
01:27:05
Speaker
And the fourth one, which I think will play out eventually, is that we think over time, even if you're a backward integrated dairy only commodity player, we'll probably become the cheapest way to source milk because we're doing at scale for multiple people in a multi-tenanted manner. It's almost like the ODC model that Wipro, Infosys, Cognizant, TCS. What is ODC?
01:27:29
Speaker
offshore development center model where they actually set up offshore development centers for these European and American companies, for the Ericsson's, Nortel, Citibank's of the world, wherein you use a common factory model of engineers to service multiple customers without violating the intellectual property and all of them.
01:27:50
Speaker
Because at scale, you probably become the cheapest way to develop that software, using that onshore, offshore, that kind of model. Similarly, here, we sort of become the best possible way to run the network. This is also replicated since we come from a telecom world. Today, Ericsson actually runs Atoll Networks.
01:28:14
Speaker
They started off as selling the boxes to Atel, but they run the network. Atel is only in the business of branding and marketing. Exactly. Atel is a retail company. The Atel IT system is run by IBM. Atel is a retail company. It's actually an FMCG company. Yes, it is.
01:28:34
Speaker
But they didn't start that way. They started by running their own network. They started by running their own IT systems. But now they don't take care of any one of them. So I think the dairy industry and Agri at large will move in that direction, where you have people like Amazon, Dunso, Geo, Reliance, who crack the consumer access.
01:28:56
Speaker
who cracked the last-mile distribution, which needs billions of dollars. But then you need multi-tenanted, multi-service traceable providers of any agri-produced, not just dairy. So I think that's the model it will go to. It's still early days because the telecom industry has had a lot of capital flowing in and added maturity and tenure to flow through this. Because agri-industry will see this pan out with some tweaks over time.
01:29:25
Speaker
Okay, okay. So what are the constraints for you to scale up supply? Is it capital? So right now it is the right capital, the right talent, and the right execution, right? We need capital because I need to put out those cold chains, those IoT devices. Yeah, you need to spend on the chain. Second is talent because
01:29:51
Speaker
It's very easy to look at this and people say, look, I'm building a dairy. And let me do it the brick and mortar way. We keep reminding people saying that we are not about milk. We are not about digital supply chain. And the agri imports, financial services, and all of that are an incidental outcome of the digital supply chain. So all of you, so to that extent, I'm trying to become the de facto digital proxy or the default Amazon off dairy.
01:30:16
Speaker
So, I need the leadership team, the execution team, the hands and feet on the ground to think that way so that they don't think that they're trading milk from point A to point B. They're not trading nutrition from point A to point B. They're not selling cat from point A to point B. They're not trading. They need to think that I'm a multi-service Amazon manager who is leveraging this digital supply chain to sell anything and everything that any stakeholder in this chain wants.
01:30:44
Speaker
So getting the right talent. So you need to have that startup culture in people you hire rather than the cooperative. Exactly. You hit the nail on the head. That brick and mortar thinking can ruin us. So that constant talent engagement and driving home the point, it all suffers from tan effect. You drive home the point today in one month, they come back to their old ways of doing this.
01:31:10
Speaker
Third is execution. Execution is hard because milk is a 24-bar-7 industry. It starts at 4 a.m. and ends at 1 a.m. You get the milk no matter what at your doorstep to drink your tea and coffee every day. It's a rural driven supply chain, a remote area where electricity is a problem.
01:31:30
Speaker
During marriage season, transportation gets hit. During chut, something happens. During holy, something happens. It's politically sensitive areas. People like to play politics with this segment. You're vulnerable to politics, absolutely. You're vulnerable to those. It's hard on execution. It's a crackable problem, so you just can't afford to take
01:31:57
Speaker
even one hour of a pedal on execution, right? So these are the three things if you crack at scale, I think you have a pretty, you know, a multi-billion dollar opportunity that we can crack. So isn't the talent problem also like a tech problem only? Like say Amazon has like thousands of drivers, warehouse workers who are probably not on the payroll also, but then they have these
01:32:22
Speaker
pure automated systems through which the compensation is linked purely to performance. It's like being a part of a machine almost for employees. There are a lot of complaints about working at Amazon, but they've solved that productivity problem through tech.
01:32:38
Speaker
like productivity of people. Absolutely. You can hit a very, very pertinent point. So the things become very optically intense, right? And especially if a person on the ground is supposed to render multiple services, right? The only way to do it is to do it in a tech way. Otherwise, it becomes too expensive. It's like saying if an Uber driver has to figure out where to pick up his next passenger from,
01:33:01
Speaker
Tech has to assist him that there's someone two minutes away from it. And by the way, imagine that he has to also deliver a pizza in that time through Uber Eats. Within that comes in. So the only way it can solve the upscaling, cross-scaling problem can be solved through this tech. And this is exactly the point that we were brainstorming last night with the leadership team here on saying, what are the features that our pharma app should support?
01:33:28
Speaker
so that a farmer or the personal tending to that farmer knows that it's not only about cat nutrition, it's not only about A, B, C, it's also about Y. But he's not a PhD in all of those. I need to upskill and cross-kill in all of this. And tech actually comes to fore and it has to be
01:33:46
Speaker
Yes, absolutely. For him, it has to be some pop-up come, yes, I have to do this. And these people may not have the same level of commitment as someone who's in the city. So they have to be reminded of and do this now. If you're in a farm to fix an IoT device, ask the farmer, why didn't he pay the last month's EMI?
01:34:05
Speaker
He probably never did an EMI interaction before. He only had a screwdriver to fix an IoT router in that form. He also has to do something more. So that is something that you're working on. I'm not saying that we have cracked that problem, but it's something that we would want to crack, but that's something that would help us improve productivity and all of that. Right. So when you are hiring these people who are all deployed at remote locations, how do you
01:34:33
Speaker
make them loyal towards the company because they would literally hardly ever interact with you because they would all be in remote deployments. How do you do that engagement and culture building and loyalty building?
01:34:47
Speaker
Yeah, so that I very soon realized that after the financial component, the CFO office, the HR office probably placed the next most important role. And the way you engage an IT and tech engineer up here in Bangalore will be very different from the way you engage a personnel deep down in Eastern UP.
01:35:11
Speaker
So, we try to do a lot of these talent engagement, productivity improvement, ongoing trainings, because no matter what good software we write sitting here, no matter how much good your business plan looks on your Excel sheet and PowerPoint, the guys on the ground who can take ownership and drive it are the final who matters.
01:35:29
Speaker
So, we are trying to sort of, it's very tempting not to invest in talent engagement and maybe put that money on an extra software engineer or an extra salesperson. But I think investing in the talent engagement, if you don't do that, we are about 750 employees today. If I don't do that, I think you'll get it, right?
01:35:48
Speaker
trying hard, very, very tempting to invest that extra buck on sales or extra buck on product feature. But investing in talent functions become extremely critical, build that culture, drive home the fact that you're not running a dairy, you're a multi-service personnel, you're a branch manager, you're an Amazon personal. Driving home that mindset, they don't think like a cooperative, they don't think that becomes very critical.
01:36:13
Speaker
And it may not result in upsides next day. It will result in an upside a month, a year from now, or two years from now. That's sort of invest in that. What do you see as your path towards becoming a unicorn? You are actively in the market to raise more funds. What do you think will be the time when you'll hit that mark?
01:36:38
Speaker
Yeah, so we think we should hit that mark anywhere between 24 and 36 months from where we are right now. So as I said, we are actually building four potentially unicorn towers. Yes.
01:36:54
Speaker
financial services piece, the tech piece, the market linkage piece, and the agri-input piece. All of them are powered by the basic foundational digital access network. One of the questions that we get asked is, do we have enough management bandwidth to run all the four towers at the same time?
01:37:12
Speaker
We're just trying to first pick the market linkage tower because everything else powers that one tower. As the tower picks up and we get more capital, we start nurturing the other three towers. That's how we are thinking about it. Hopefully, if you have enough support from capital execution and talent, we should be able to get to that stage in 24 to 36 months.
Podcasting Insights and Recommendations
01:37:35
Speaker
Got it. Amazing.
01:37:36
Speaker
This episode of Founder Thesis Podcast is brought to you by Long Haul Ventures. Long Haul Ventures is the long haul partner for founders and startups that are building for the long haul. More about them is at www.longhaulventures.com.
01:37:57
Speaker
Before we end the episode, I want to share a bit about my journey as a podcaster. I started podcasting in 2020 and in the last two years, I've had the opportunity to interview more than 250 founders who are shaping India's future across sectors. If you also want to speak to the best minds in your field and build an enviable network, then you must consider becoming a podcaster.
01:38:21
Speaker
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