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Gunjan talks about how Tathya has been maturing as a young company and his understanding of the maturing of geospatial SaaS ecosystem of India.
The NewSpace India podcast brings you insights by providing glimpses of the past, addresses the present challenges and installs a vision for the future from experts who have been involved in India's space activities.
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[00:00:00] Narayan: Hi, you're listening to the New Space India podcast, a biweekly talk show that exclusively brings insights from the Indian space activities ecosystem. I'm your host Narin, the co-founder of India's first space focused think tank. Spaceport Sarabi. Guests on the new Space India podcast help you understand space activities related macro and micro trends within.
[00:00:28] Narayan: In all aspects, including space. Local industry, space science, technology evolution, law and policy art, and more. The new Space India Podcast is supported by Dassel Systems, a global leader in providing businesses and people with collaborative virtual environments to enable sustainable innovations, dassel systems, solutions, support startups, small and medium scale enterprises and original equipment manufacturers in developing disruptive solutions.
[00:00:58] Narayan: For space [00:01:00] launchers and satellites. Hi, and welcome to vi yet another episode of the New Space India podcast. Today we have here Gunk who is one of the co-founders of TYA Earth startup that is based out of Mumbai. So Gunnin, thank you so much for taking the time and recording this episode with me and welcome to the show.
[00:01:20] Gunjan: Thank you, Nara. Thank you for having me.
[00:01:24] Narayan: So let's begin with a little bit of the origin story of your founding team itself. You guys have a very interesting background and the way you've stepped into the geospatial applications domain. It's very interesting to see.
[00:01:37] Narayan: Non-space people always come into the space sector. So I would say for the benefit of the audience, it would be very interesting to know, what you guys' background are and how you came across this domain of geospatial analytics and insights and how that led to then
[00:01:53] Gunjan: Okay. Okay. So we have to go pretty back sometime back then. Let me introduce the founding team and our background a little bit, [00:02:00] and I think from and how it led to the genesis of the idea and the company. We so myself and Naish, we are the technical folks in. So our background is predominantly in analytics, data science and machine learning and software engineering.
[00:02:18] Gunjan: And NIIT and , they are they are, they look after the sales and business development side of the business at this point of time. Now with regards to how we look at our space, we don't think of ourselves as. Space tech or space related startup. As such, we are , we are in the commodities business.
[00:02:40] Gunjan: We provide insights on the supply chain of commodities. So I think a closer description would be, we are an analytics company wherein we provide realtime intelligence on supply chain of commodities. Satellite images happen to be one of the good sources of data that we use for insights. And [00:03:00] this combined with other data sources like shipping data.
[00:03:04] Gunjan: Or bill of Laings, et cetera, combined the former good data sources for us on which we run our algorithms to provide intelligence on the supply chain of commodities. So this is how we look look at how we describe ourselves now coming to how the genesis of the idea was formed. Now being from a analytics background, so I was working with a company called Money Control.
[00:03:29] Gunjan: I was leading their data science and analytics team. And at Money Control we used to work with a lot of economic data. And I think one of the constant sources of one of the constant. Discussion points with our research team was that most of the economic data, they used to come with a lot of lag.
[00:03:47] Gunjan: And in some countries or certain economies, the data was not even correct. And it used to be revised multiple times. And at that point of time itself when there's a lot of explosion in terms of [00:04:00] new and alternative data sources and satellite data being one of them. We, so it triggered my mind, whether we can look at this other alternative data.
[00:04:09] Gunjan: To study different types of economic activities that are happening on the ground and then predict or measure those economic indicators, which are at this point of time derived through through human service. All published by the indu companies themselves or industries themselves.
[00:04:25] Gunjan: When we were looking at that, we saw some, a lot of examples where researchers were working on satellite images to look at overt levels in sub-Saharan African areas to look at how the policy decisions of World Bank were impacting progress. So I think that is the first time where we came across satellite data and its application, and then really thought, if we could look at every point of the earth, every every day, it could lead to a lot of other applications.
[00:04:57] Gunjan: And in our case, we knew from our experience, [00:05:00] when it comes to economic data, economic information, there were some gaps in the type of data that we were getting. And that is where we started our journey to, no looking at satellite data and measuring different kind of economic activities.
[00:05:12] Gunjan: So when I say economic activities now, again, that's a very huge space. So when we have to make business sense out. We started speaking to more people and then soon realized, we have to focus on one particular industry or one particular genre. And then we started focusing on the metal and mining industry, and in particular on commodities.
[00:05:30] Gunjan: So at this point of time, we ma we monitor supply chain of commodities like steel I donor coal. , copper, aluminum, et cetera, and cater to multiple industries be it metal producers, physical traders, financial institutes all around the world. And the core still remains the same, which is to monitor near real time supply chain of different kinds of commodities.
[00:05:54] Gunjan: Yeah. Yeah, so that, that is basically how we came to form this form. The. And got [00:06:00] into them using and got into using satellite data.
[00:06:04] Narayan: Yeah, that's very interesting. And obviously I think there's a lot of space for people like you who realize that there's a lot of power in using satellite imagery to.
[00:06:13] Narayan: Help other industries and stepping into the space tech from software, SaaS oriented business model to come into the sector to create a lot of value. That is definitely a lot of presence in there. So from the time that stepped away from money control and maybe your colleagues as well from their own journeys starting , what is the. Approach that you probably took to validate the idea, because obviously sitting out of India, I think the space that you are in with all this economic tracking and on the end users may often also. Not be as mature in India as other countries, because I guess even in the middles and minerals industry, there's a lot of players in US and Singapore and many other countries.
[00:06:55] Narayan: So the customer base for you like many other companies [00:07:00] as well, maybe 95% of the market is outside of India to a large extent. So how do you deal with assessing product market fit and doing a lot of customer discovery at the early stages. , like sitting out of India and is that a very big challenge?
[00:07:15] Gunjan: Yeah. So the way we went about doing customer discovery at the beginning was I think we spoke to a lot of, we reached out to a lot of no people from the. Via LinkedIn or other sources through our connects common friends, and you are right, most of them are not in India. So for our industry, we started off with Paris steel supply chain, and majority of the trading, fertility, mining companies, all the headquarters are in s.
[00:07:43] Gunjan: Most of the headquarters are in Singapore, and when we started off it was just the beginning of the pandemic, so around 20, 20, 20 beginning. And by April, obviously everything shut down. I think in the beginning, in 2020, it helped us a little because what has happened was [00:08:00] most people have some downtime They were opening to discussing new ideas.
[00:08:04] Gunjan: So we, so as I said, we use multiple channels, right? We called email, cold call, we called messaged them on LinkedIn through our advisors. We connected with people. So I think the primary focus, or the first year of our business was to Two things correctly. First was to talk to as many users as possible and to validate the problem statement.
[00:08:27] Gunjan: And second was to build the work outta all the products possible that we could build build one product which could solve, which would be the most impactful for the industry. So we talk to many many companies, right? Static, small, large, and try to guard the interest levels to the type of products that we thought would be interesting to them.
[00:08:49] Gunjan: Now even when we do that, there are there's. Difference between say just asking. So if we can ask, whether this would be useful to you, whether you'll buy the buy it. So [00:09:00] sometimes the answers could be very positive, but when it actually comes to buying and paying that is when you know the, where the real worth of the data our product is.
[00:09:09] Gunjan: Although we got a lot of positive feedback, so it was only around 2021 when we started actually no beta testing the data with our customers. And initially itself, I think some of the large publication houses like IHS Markets, they picked up a data, they validated our information they published it in their report and which cater a lot of us or credibility for us at the initial.
[00:09:32] Gunjan: And we got Then from there, we picked, we got picked up by other very reput publications. And they published our data. So that sort of created a credibility for the information or data that we are publishing. And from that, from our discussions that we had started around 2 20, 20 onwards, beginning onwards, we knew what kind of.
[00:09:51] Gunjan: Clients that we should go after. So end of, so mid of 21 is when we started selling subscriptions or providing subscriptions of our data to [00:10:00] our clients. And yeah, so the journey has been good. From there. So this year we have been able, we have been able to partner with some of the large 1400 companies also most of them based out of some of them based outta of Singapore, some of them based out of London and some ins some in Switzerland.
[00:10:16] Gunjan: Yeah, so the journey has been long, but I think they just the learning curve has also been steep in our case because that industry itself is not very matured in India. So it was a lot of reaching out to people and and yeah and you're right having being, being present in the same geography as our clients is very important.
[00:10:34] Gunjan: Last year was the first time that we actually went out. After all the lockdowns got over. So we visited Singapore. We met all of our clients. So all of our clients are basically in the same 500 square meter in the same it's in a small vicinity. All of them are located, so it creates a various different kind of, get to know him.
[00:10:51] Gunjan: And the sales process is very different, I think, when we can meet your clients face-to-face rather than doing it only on the on a zoom call or a [00:11:00] teams call. So that creates a difference. And and because of that, I think next year onwards, we also want to have a presence, a permanent presence in Singapore so that we can meet our clients, move more often face to face.
[00:11:12] Gunjan: And so that creates a lot of difference. In the sales cycle.
[00:11:19] Narayan: And so what would be very interesting to know is what kind of impact you believe that you are creating for your customers because always I think in any of these kinds of interesting business models around decision intelligence. I know insights about an industry. Yeah, it all comes down to, value capture then depends on the return on investment that a lot of the enterprises are making on such tools, right? . So have you guys done any kind of analysis on before you guys providing them these kind of data and these kinds of inte.
[00:11:51] Narayan: that their business was affecting X and now because of this, you are able to prove to them that you're creating an impact that is X that is y and that's [00:12:00] how you're able to then build a business case around it, .
[00:12:02] Gunjan: No, in a product like ours where we provide intelligence, it's very difficult to assign a specific.
[00:12:08] Gunjan: But I can give anecdotes or examples to prove or to say, how that we are creating value for our customers. What happens is basically we provide sets of information, right? And the company or the client combines it with other information sources to to make business decisions. Now, debt is dependent on a number of factors.
[00:12:28] Gunjan: It depends on what the kind of information that we are giving. It depends on the person and the analyst who is making that call. And it also depends what kind of other information they have. So combined all together, they make a call to say they make a business decision now. To now anecdotes of whether we have been able to provide positive impact on the business.
[00:12:49] Gunjan: Say there are a couple of examples, right? There are customers, large customers who when we started off, Say beginning of this year, they started off very, with very small packages. Let me [00:13:00] monitor only India or let me monitor only Southeast Asia. So they did that for around six, seven or seven, eight months.
[00:13:07] Gunjan: So the amount of value they saw, then they came back and said, no, now I want to monitor the entire world. Give me data for China. Give me data for Australia, give me data for Europe. So that created that flywheel or. The initial trust, this data is useful. They're able to take, they're able to make business calls.
[00:13:24] Gunjan: They're able to make profits I have entered into multi-year contracts now from the initial results they and it's not just one client, it has happened with two other clients where from the initial results, they have been able to create enough confidence. They have able to show enough ROI to their business stakeholders so that they can.
[00:13:41] Gunjan: Take a larger, much larger package in a subsequent years. So those are some of the examples that we see where I think it two steps we have been able to create impact. But it's still difficult, I think, at this point of time to quantify how much would it, that impact would be. And that depends on a number of factors for the industry.[00:14:00]
[00:14:03] Narayan: Yeah, I can definitely understand your perspective on that. And obviously that's always a challenge Yeah. To look at it as a whole in terms of the impact from a standpoint of data availability and the sources and all of the sources that you would want to use to build your data sets to be able to drive these decision.
[00:14:23] Narayan: Obviously you mentioned about how the demand for your services has been increasing. , as people adopt this and the geographical era of interest is increasing and the kind of customers are also diversified, what is your review of the existing sources in the industry and are they sufficient?
[00:14:42] Narayan: And it'll be very interesting to know if you. , see a market for absorbing commercial data in different bands or different sources as well. . Cause one of the main themes of a lot of the earth observation systems, commercial ones, new space ones have been around, is that, that they [00:15:00] are going to empower people like you to make, better services. , is the pri. What will be also interesting to know is your thesis around free data and commercial data and in commercial data easy is it to absorb their prices and their if their performance is good and any insights around it would be really nice to see here.
[00:15:18] Gunjan: Yeah. Yeah. That's a very good question actually. And this is the thing that we struggle with always with regards to commercial images versus three images and the value they provide the r i l provide and the cost. And the cost that one has to, in. So in our case specifically, we use a combination of free from European Space Agency, nasa, and and commercial satellites from we maxar or planets.
[00:15:40] Gunjan: Now I said where we struggle. is with, say, information like data from some of the commercial satellite providers or studio images or thermal data, which is just coming online from companies like Satellite View or ao Now it, it becomes very [00:16:00] difficult in a commercial. For people like us where say the number of clients may be lesser and if the product price of if I have to pay for one image 600, 700 dollars, right?
[00:16:12] Gunjan: And for a product like us, it's a weekly weekly monitoring of an asset. So you can imagine the price of the end product, that it's gonna be incurred only in buying the commercial images. And there are very few companies in the world at this point of time who would be able to incur the entire who would be willing to pay, incur the entire cost upfront without doing the roi.
[00:16:33] Gunjan: And the. Only becomes a very apparent say after a year of using it when they have been able to consist, consistently use it to make business decisions. Say after the year's time, they'll be able to decide what is the roi. So that becomes a very big, hard hurdle in terms of adoption. Of new data sources or commercial data sources.
[00:16:54] Gunjan: And this is something that we are struggling to figure out, how do we use it in in the initial [00:17:00] phase? Who will be funding it? So should we fund it? Should we, should it be funded between clients and us? Should it be divided into multiple clients? So if there's only one taker for one product, it's just very difficult to make it.
[00:17:11] Gunjan: If there are multiple takers for the same product, maybe it becomes more economically viable. Those are the kind of things. There are certain products which everyone who needs that we are building, which, for which we use commercial satellites because we can divide the cost and other people can use it.
[00:17:25] Gunjan: So each client did not pay a lot of dollars. But if there's something new product, which no say there are few customers at the beginning, how do we create the initial trust and take it to market? That the go to market becomes very difficult? When it comes to when it comes to expensive commercial satellites actually.
[00:17:45] Gunjan: And I think for that, some type of partnerships with satellite companies could also help, which is not happening at this point of time.
[00:17:53] Narayan: Yeah. I think it's a very important topic for the Yeah. Years to come actually, because although people have been trying to [00:18:00] reduce the cost of imagery for the last 10 years, they've still not got
[00:18:04] Gunjan: there.
[00:18:04] Gunjan: Yeah. And it's just too high for a no if you have to buy, say, one image a month, that's also is fine for us. But if if there are hundreds of assets that we monitor and every week that we monitor that's when the cost becomes very high. If you use expensive commercial.
[00:18:19] Narayan: So from a standpoint of also, apart from the sources, it's also about cloud and the nature of cloud that you wanna use. How is that evolving for, companies like you? Because obviously today there's Google and Amazon and Microsoft who are primarily, like fighting out in that space.
[00:18:37] Narayan: And they're also right uhhuh, lot of them are also now focused on space as a vertical, right? So is this something that as advantages to you with the costs? Are the costs on the cloud for computing decreasing or they, are they increasing? Or, how is that impacting your, the business?
[00:18:53] Narayan: Because obviously that is the second bit of the cost. That the human resource
[00:18:57] Gunjan: cost. . Yeah, so cloud cost is a very [00:19:00] no it's a very important line I in expense. So as is, as you rightly mentioned, there are multiple cloud providers and currently we are working with aws and they have a lot of focus on, I think space data or space startups.
[00:19:12] Gunjan: So we have been lucky at this point of time. To have to be, to have enough credits which have been able through using, which we have been able to keep our costs down. But I think the cost itself is coming down with time, but still is significantly higher for any startup like ours. But with a lot of programs which gives credits, we have been able to utilize that.
[00:19:32] Gunjan: And at this point, our cloud cost, in terms of actual dollars paid is quite gli. Thanks to multiple programs.
[00:19:39] Narayan: And from a standpoint of the, geospatial community within India what do you see or how mature do you believe, because I think you might have through the couple of years that you've been around now, Building this product, obviously I think you might have seen other companies or been to other geospatial events, Uhhuh how mature do you think is the geospatial [00:20:00] ecosystem in India and, are we at the very early stages where there's far too little companies or is there some level of maturity in terms of building these kinds of SaaS? Because I think India has been a very big outsourcing hub for geos.
[00:20:13] Narayan: Yeah. Large companies have been outsourcing a lot of work. There's a lot of off type of business models being present. A lot of companies that provide individual outsourcing support or, auto rectification and these kind of very basic changes that you can do on satellite imagery to prepare that to be absorbed.
[00:20:29] Narayan: , those kinds of services have been around for a lot of time annotation and things like that. . . But in terms of actually building full value SaaS businesses using US special Uhhuh , that is something that I don't see as much as the other. So what is your kinda assessment?
[00:20:45] Gunjan: I think it's maturing is starting. I think the major challenge is not satellite data. I think the major challenge to that is knowing the industry where we have to deploy our use sales space space data. So let's see. No. And I completely understand your point [00:21:00] going where India was primarily no outsourcing hub earlier where a lot of geospatial analytics used to be done.
[00:21:06] Gunjan: Working on dataset or providing analytics on data. So what we are, I think what we are talking about now is converting all the data sets into products, which can be our SA platform or assess SaaS offering, which client can use. So I think if you look at geospatial data now there are certain industries where geospatial data becomes more useful or more handy.
[00:21:29] Gunjan: It's, and I think it's mostly industries where it's asset heavy, heavily distributed. Systems have it distributed supply and distributed assets everywhere, which has to be managed. Oil and gas, agriculture metal and mining, defense, shipping. All these sectors, I think other prime candidates for applying satellite data.
[00:21:47] Gunjan: Now, I think as s no, as far as I'm concern concerned, I think I can. For some, in, some other people also whom I know. So our exposure to those industries growing up while doing our engineering or while doing our schools are [00:22:00] our exposure to those industries. Less so our exposure to say metal and mining industry to commodities industry to shipping to defense those the typical engineer would not be, I think, exposed to such industries.
[00:22:14] Gunjan: I think, and once we get exposed to, I think that once we get exposed to those important industries or industries, other industries where geospatial data can be applied or can be used as one of the inputs only, then I think you will see more offerings. For those for those players or for those industries where geospatial data can actually add value.
[00:22:37] Gunjan: So I think just to summarize, I think it is exposure to the industries where geospatial data can be used and add value, which is more important for for us rather than and it's not a technical challenge. I think it is more to do with exposure to the industries itself. So I was not aware of metal mining commodities where I'm working as of now to say five years back.
[00:22:57] Gunjan: So that's how. Our learning curve has been, and it's [00:23:00] really, and it's very fascinating, right? So all these industries, traditional industries, they drive our economy. They're the most important parts of our economy with which everything else is dependent on. And we as in we, most of us are not exposed to those sectors.
[00:23:12] Gunjan: I think exposure to those, to such industries are the key where we can leverage satellite data other satellite data, just special techniques to drive value. Yeah, that's my thought. My thought on that.
[00:23:22] Narayan: And from your company's perspective what is the barrier to entry in terms of cost?
[00:23:29] Narayan: Or is it because, at the end of the day, upstream in space is extremely difficult to build rockets and satellites. You need tens of millions of dollars and it's not very easy to. That space and , there's some companies that have managed to do that in India and obviously that is a very big barrier to Yeah.
[00:23:44] Narayan: To enter given the investment landscape as well. But for anybody who wants to like, look at a geospatial business or so , what is the baseline foundation based on which they can really start up. Is it, cause cloud gives you credit. There's a lot of free imagery that is out [00:24:00] there.
[00:24:00] Narayan: So from your experience what is the kinda investment that a typical, let's say a very bright Indian kid who wants to start a space or a geospacial company, how much of an effort it has to go in, in terms of capital
[00:24:13] Gunjan: in resources? I think it's less to do with capital, more to do with understanding the business statement.
[00:24:18] Gunjan: So I think what has to be crystal clear is which industry one has to target, and which particular problem statement one can target to which can we solve with geo special data. And one has, I think one to always remember geospatial data is one of the important indi one, one of the important inputs.
[00:24:34] Gunjan: There are many other inputs that goes into the spinal solution, which makes it usable for the end customer, right? So one is recognition of the fact. So one is a study industry very well under identify those pain points. And then design a system which can use multiple data sets, including geospatial data, which can solve for that problem statement.
[00:24:55] Gunjan: And ITing for that is pt is not mostly a function of money. [00:25:00] It's mostly a function of domain understanding. So one has to understand the domain and and problem solving abilities. The other systems, like the other things like no, working with satellite data working on cloud, all these things, a bright engineer can figure out.
[00:25:15] Gunjan: A satellite data is nothing but another roster data. It's just that the number of layers is higher if we can interpret the layers differently. But at the end of the day, it's we should treat it as a input which, and it's a means to an end, which is to solve our business statement or a business problem.
[00:25:31] Gunjan: Clients don't care whether it comes from satellite data, it comes from any other sources. For example, in our case, the problem settlement that we solve for is that high frequency data and coverage anywhere on the earth. For that particular use case, geospatial data is very it's unique in its capability that we can use just special data to.
[00:25:49] Gunjan: Particular problem statement. So knowing those problem statements, I think is the biggest barrier to entry and knowing what else is required to solve it, along with your special data is something that is required [00:26:00] to make the final build a final product, which can be used by a client.
[00:26:03] Narayan: And how big is the market for Tata? And, how do you see yourself evolving into a company? How large can the company get in the next, let's say, five to seven years timeframe? What is your sense of Growth here.
[00:26:16] Gunjan: We are focused on the at this point of time, we are focused on the metal commodity sector, right?
[00:26:21] Gunjan: So metal commodity means steel, aluminum, copper nickel, et cetera. And our goal is to provide realtime supply chain intelligence for all these commodities. Now, there are three aspects of the supply chain that we monitor. First is to map in real time or near real time supply demand supply demand indicators.
[00:26:41] Gunjan: Number two is to monitor sustainability or environmental impacts of this supply chain. Number three is to monitor Climate risk to the supply chain. So anything that can impact or is affected by the supply chains, that is what we are going to monitor in the next, say, four to five years. And [00:27:00] that itself is a very big market.
[00:27:01] Gunjan: We the kind of industries that we go after or the kind of industries that we cater to are all the, so they're basically all the stake. To the commodities industry. So these are physical traders financial institutes. Metal producers mining companies and then downstream companies.
[00:27:17] Gunjan: Downstream companies means any company with buy commodities for the end products. So even they are impacted by the fluctuations in the commodity prices. And the fluctuations in the commodity prices is basically understood if we can monitor the supply chains. Okay. So the final goal for us is to monitor prices, is to predict prices of these commodities.
[00:27:35] Gunjan: Which that can be used by the different stakeholders to make appropriate business decisions. So as you can see, these are different different industries that we are catering to, which is a very large market. So in our case, I think the serviceable market that we had calculated would be around five to 10 billion.
[00:27:51] Gunjan: And that does not even consider the. Sustainability part because there is a, because that is a very growing industry a lot of, there's a lot of unknowns. But I'm sure with the [00:28:00] type of conversation that we are having with different participants of the supply chain, that even the sustainability or the climate part is going to be a big aspect of the commodity supply chain.
[00:28:10] Gunjan: There are clients who ask us whether, so if you can monitor, say floods around the coal mines in Australia, or what is the impact of a storm? In the I r o mines in Brazil. What has been the impact in the ports around Canada or us. So all these kind of factors. Also, if you build in, so it becomes, if you can imagine, it becomes a holistic supply chain monitoring platform, which has supply chain intelligence.
[00:28:34] Gunjan: Climate intelligence and impact on the environment. So all these factors taken together, it becomes a large enough market size for us exciting market space for us to go after. Now at the end of the day, if you can see whatever we are building is an asset monitoring platform, right?
[00:28:49] Gunjan: So if an, if we open, if we look at. Plainly Art as an asset monitoring platform so we can extend or use this platform across different [00:29:00] other edges, industries also. So oil and gas industry. Agriculture railways, utilities all of them become lucrative industries where we can extend our products.
[00:29:08] Gunjan: At the end of the day, we believe we can build a multi-billion dollar company in this space. And and I think solving for important problem statements for some of the most important industries that we have in our. and yeah, we are very excited about the pro about the future of this.
[00:29:25] Narayan: And the two other aspects that would be very interesting to know from you in your experience is really one the investment angle, the appetite for people in India, Indian investors, essentially to understand your kinda business. , cause often I think there's a lot of people. I guess fairly have a very good understanding of e-commerce and, other things where it's much more mature and, but understanding your kind of businesses where, , it's a SaaS platform and they need to understand either the industry or the technology the service.
[00:29:56] Narayan: . So is there enough understanding to raise enough capital at [00:30:00] different stages? Maybe you find good investors at the seed stage, Uhhuh or so on Uhhuh . So what is the appetite for understanding your kind of business at various stages of investment? The second aspect to this is really what is the maturity of the human resource?
[00:30:16] Narayan: In terms of ability to recruit, is there a lot of time that you need to spend. Training people to get them up to speed or invest a lot in them to then them be productive for the product itself. So what are your experience around this?
[00:30:29] Gunjan: Okay, so let me take the first question first around investment and appetite for investors and sector like us.
[00:30:35] Gunjan: So we operate in the commodity sector, right? Site data sets that we, or technology that we use, the commodities market itself is not a very lucrative market in. And as I had mentioned earlier, also, I think even as I was also not exposed to the industry, I, most of the VCs or investors are also not exposed to the industry.
[00:30:53] Gunjan: So it's an most people would not have any thesis centered around. Monitoring supply chains of commodities. [00:31:00] Now they understand the commodities market in depth, right? So that's an issue in India and hence the kind of capital that a company like us in the commodity sector would be exposed to would be on the lower side.
[00:31:12] Gunjan: So it's very limited now, but to to counter that point again. The industry, the same commodities industry is very mature in the Western economies. We we'll be trying to fundraise in Singapore and US. So in Singapore, this is a brilliant butter industry, right? Peop students are exposed to the industry from from the, from universities itself.
[00:31:34] Gunjan: They're special commodity courses, shipping courses. So people are exposed to this industry. And there are there are investors who have have the thesis, around. Shipping commodities working on industrial sectors, who in my opinion would be the correct sources for capital for a company like us.
[00:31:53] Gunjan: And we are talking to a few of them, hopefully sometime in the first half quarter of next year will be able to have more traction on that. Yeah, [00:32:00] so I to your question, yeah, India probably is not the right place to fundraise for a company like ours. But again, there are certain investors now who look at companies like us from a sustainability angle.
[00:32:12] Gunjan: Because we also have a angle where we look at the sustainability side of the supply chain. Those are the thesis driven investors that we can speak to and who have been receptive to the product or the concept that we are working on. But the kind of understanding and reception or feedback that we get from investors in Singapore and US is very different.
[00:32:32] Gunjan: So they have been far more receptive to to a product like ours and and and they seem to know more about the industry and seem more willing to invest in the industry like us. So that, that has to do with investment Now. Second with terms of human capital or recruiting engineers to work on product like us yeah, that's I mean compared to, say, a full stack engineer compared to a data regular data science, of course it is more difficult.
[00:32:56] Gunjan: But there are fantastic, I think universities [00:33:00] programs from where we have been able to recruit. So our pro, I think a special shoutout should go to the bomb based program, MS program tech program, master's program. Their CSI department is really good. We have been able to collaborate with them hire people from there.
[00:33:14] Gunjan: Then on IRS institutes where they have trained people in remote science. Then we have also been able to train people who have a background in data science or software engineering to work on satellite images. So the training part does take some time, say for a relatively smart individual, probably it'll take around month or two to understand in one sense of satellite imaging and learn about that and then start applying all the concepts.
[00:33:39] Gunjan: Yeah. So these are some of the resources that we are leveraging at this point of time. And I think and the hiding has been, I would say we have been fortunate that we have been able to work with. I would say smart people who have been able, who have a fast learning curve and who have been able to ingest or [00:34:00] understand new types of data sets.
[00:34:01] Gunjan: Be it, we started with optical, we went to sar, we went tother. So it's a fast learning curve for everyone. So I think the key is to work with smart people who can learn fast and adapt to different kinds of situations, different kinds of data. So yeah, that's the key. I think. And India.
[00:34:21] Gunjan: The last pool of engineers, I think there's a huge potential to work on geospatial data,
[00:34:26] Narayan: right? One of the things that I am currently discussing with a large corporate house is to potentially put up a geospatial accelerator in. Huh, I don't see any prominent geospatial technology based programs that are dedicated because, there's some commonalities there.
[00:34:45] Narayan: Where cloud is a commonality. Yeah. Is a commonality. There may be different sources of data that are common to a large extent. So a lot of the foundational pieces that are needed, Can serve to a lot of [00:35:00] interesting new companies to be firm. And based on that, there could be also exposure or a community that is built towards end users who can act as mentors to find a product market fit.
[00:35:12] Narayan: Experts in infrastructure or mining or other areas, right? . So I see that this is something that many of the other countries do have the UK has this the US has some of this as well, and there's a lot of other countries, but. Nothing really in India that I see for all this.
[00:35:27] Narayan: Do you think it's an interesting thing to have in the country? And if there's what would be your suggestions around this? ,
[00:35:33] Gunjan: I think it's very interesting at I think the prime example of how ISA works or European inspire Space, NC works at different companies, right? So I think what's required in the ecosystem is our.
[00:35:45] Gunjan: First of all clients or companies would be able to adopt the solutions. So first deciding what kind of solutions have to be built for whom it has to be built and who has to build them. Example Visa. They work with they, and they work with different industries identify problem statements.
[00:35:58] Gunjan: Then they work with startups[00:36:00] give grants for them to to solve for their problem statement using say ESS data and combination of multiple data sources. So it solves the problem of capital, the initial capital, the problem statement for was to solve for, and. And I think the human capital we always have.
[00:36:16] Gunjan: So I think what has to be onboarded first is our industries who would be will, who would open up their problem statements which can be solved using geospatial data. And then the second step would be to see who would be willing to fund it through, via grants.
[00:36:31] Gunjan: And I think from there, I'm sure you'll be we'll be able to find some startups or engineers who will be able to take up those problem statements. I think those are the models I think we can look at, and it has to, it has proved to be successful in other countries. I don't see any reason it can't be successful here.
[00:36:48] Gunjan: And I think not only Indian customers I think we can look at any customers around the. Who would be willing to provide the problem statement and I think one of the core advantages that we in India have as a [00:37:00] SaaS business or outsourcing business is that our inherent cost structures are very low.
[00:37:04] Gunjan: What. Costs to build a product in say, Paris, or cost one fifth of that in India. For the same quality. Everything remains the same, right? And I think that's big advantages. Very big advantage that we have to we should take advan. We should use that advantage to basically build up scalable businesses.
[00:37:20] Gunjan: Yeah. Yeah, so I think those are the key points that we have to keep in mind when building up a accelerator like that or a setup like that. ,
[00:37:27] Narayan: Congen, final question. What are you looking for yourself for tk and is it investors? Is it people? Is it so what is the horizon like?
[00:37:35] Narayan: So if somebody is listening in to this podcast and they can reach out for something or the other Uhhuh ,
[00:37:41] Gunjan: what would it be? I, we are always looking for clients and capital, and I think if you have that, will the talent pool, the engineering pool, we can. .
[00:37:53] Narayan: Great. So you guys are doing a terrific job with trying to build it us out and roll this out as a thank you [00:38:00] as a global enterprise.
[00:38:01] Narayan: So terrific work around this and, congrats on all the progress that you guys have done. And please send my regards to your colleagues. Sure, I'll do, yeah. As well. So I hope to meet you guys in person at some point of time. Yeah,
[00:38:14] Gunjan: definitely. Definitely. Yeah. Yeah. Yeah. Definitely.
[00:38:17] Gunjan: When next time you're in India, we should yeah. Meet up.
[00:38:20] Narayan: Yeah, absolutely. Thank you so much for taking the time in recording this with me and I leave the links for you guys the website and Leno LinkedIn profiles in the show notes for anybody to then reach.
[00:38:33] Gunjan: Yeah. Thank you so much.
[00:38:34] Gunjan: Thank you so much.
[00:38:40] Narayan: Thank you for listening into this episode of the New Space India podcast. If you enjoyed this conversation, please share this episode with anyone you believe will enjoy listening to it. You'll be able to find the new Space India Podcast in any of the podcasting platforms that you may be using, including Apple, Google, Spotify, YouTube, and others.[00:39:00]
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