Decarbonising rice: Mitti Labs founders on their plan for future of sustainable farming

We have all the solutions in place. It's how do you build the business model where you fit the different pieces together so that once it's all together and for us right now, it's really about how you get money flowing from the regulators and the corporates that are emitting that need pathways to actually offset those emissions into the hands of the folks that need an incentive to actually create a change today. All the levels that we need to put to make this change, one of the emerging thesis is that, yes, the carbon markets exist and as a result, you know, pool of capital is available. Private capital is available to solve this problem. As compared to, you know, the traditional sources of capital for solving a problem like this, being either philanthropy or through sort of, you know, government spend, right? - Hi, wherever you're joining me, I hope you're doing well. Welcome to India Tech Report, a podcast dedicated to chronicling and supporting the growth of India's deep tech and climate tech ecosystems. I'm Harry Arkely, and in today's episode on the occasion of World Enuron Monday, I bring you a conversation with Dev Dat Dalal, Havya Lahota Soler and Nathan Taurbick, Founders of Mithilabs. Rice is a nutritional staple for half the human population, but its cultivation is also a formidable contributor to global warming, accounting for 10 to 12% of all methane emissions from human activity. And methane is 80 to 86% more potent than 0.2 in warming the planet over a 20-year period and about 27, 28 times over the century. By drowning their fields to suppress weeds, farmers have inadvertently cultivated methanogenic microbes, not release the super pollutant. At Mithilabs, Howard Business School alumni Dev and Shavi have teamed up with Nate, a distinguished scientist, who's worked at NASA and JAXA to build a full stack remedy. They started work in India first some three years ago, persuading farmers to try out a technique known as alternate wetting and drying, but entails periodically draining their fields, interrupting the anaerobic feast of methane-producing bacteria. This is a known practice developed at the International Rice Research Institute. What the entrepreneur's admitty labs are doing, however, is to plug in an innovative digital monitoring, reporting and verification platform. Using tools, including satellite data and digital twins of the farms, they aim to convert the methane deductions from AWD to equivalent carbon credits. The planet this venture, which is backed by VC investor light speed, is to become a vertically integrated carbon project developer, providing farmers with free tools and the share of the revenue from the sale of the carbon credits. Dave, Shavie and Nate and their 100-plus team are already working with some 70,000 farmers in India to partnerships with various NGOs and other such grassroots organizations that work closely with the farmers. The long-term success hinges on mobilizing a substantial share of some 150 million smallholder rice growers who have found the same way for generations. (upbeat music) So Dave, Shavie and Nate and thank you so much for Nate. Thank you so much for making time for this. Really excited to bring this conversation to my audience at India Tech report. And I've known a little bit about mid-telapse, followed some of your news. And so personally, as well, I'm quite excited to get a sort of firsthand conversation with all the three from this. I'm gonna stop there. Let's just dive right in and tell us a little bit about the parts that brought you to mid-telapse and where you go from there. - Yeah, maybe I'll start. So look, I've been an operator personally in the Food and Ag space for quite some time. I've always been passionate about solving something for, I'd say, the nation's benefit when you look at India as a particular context. Our mandate is soon expanding to consider all of Asia and perhaps the global south in a general sense. But that was the sort of personal mission that I thought of myself. And I met Javi when we were doing our MBA in Boston and we happened to be in the same section. And at first we just became friends. And then when it comes to the summer, we just got to pick a path to sort of do an internship or plan something entrepreneurial. And that's kind of where we had a lot more deep conversations about the intersection of agriculture and climate and how it can be applied to a context like India, right? And Javi himself will share his own experience, but he comes in with a wealth of expertise. And I would say the demand side of who's paying for climate outcomes or who really wants to solve for climate change? Understanding of corporates, understanding of the mechanism of carbon markets and nature-based solutions, particularly. So my understanding on the supply side and being an operator in agriculture and Javi's understanding on the demand side and understanding what carbon markets are and what who's paying for climate outcomes, that's kind of where our synthesis really began. And in the first summer, we came down to India with the broad thesis that, okay, we're going to explore the intersection of climate and agriculture. And through conversations and through research, it's a thesis emerged around solving rice farming as a program statement. One of the peculiarities of rice is the overuse of water. I mean, firstly, it's the largest crops that's grown in the country, right? So we have approximately 40 million hectares. Now maybe 45 million hectares of rice farming that happens across the country. And the biggest issue is the overuse of water, whether you see statistics like 3000 liters for every KG or five to 10 million liters for every hectare. And you add in the context that India is the pleating as groundwater resources and many regions, many states are much lower in terms of their groundwater threshold than they need to be. So that was one of the things we learned. And then of course, the flip side of the water problem is you have, when you have stagnant water on rice fields for a very long period of time, causes anaerobic digestion in the soil and that causes methane release. And methane is a super pollutant as people know it today. It's a short-lived climate pollutant. It's aggressive and it's impact on climate change as compared to eating carbon dioxide. And this is somewhat that we saw a bit of an overlooked opportunity, let's say. And so that's where we learned a little bit more about climate smart practices and how you can solve this problem. And the double-vammy impact of reducing methane emissions while reducing water consumption or something that attracted me personally and of course to Kichadi as well. And then once we came about after that summer and we were pretty serious about wanting to build something in this topic, that's where we were fortunate to have met Nate. And one of the thesis is around, when you look at who's paying or who's going to put money behind this, the element of making sure that the work that happens on ground is trustworthy, it's robust, it's credible, it's fruitful. And that's where Nate's expertise in building what we call MRV systems or monitoring reporting and verification systems really came in. Fundamentally, when you look at small word of farming context, it's very hard to rely on hardware or institute IOTs to track every single eco because as you know in India, every farmer on average holds one hectare or there about stride not much larger land-loading. So you can't have a monitoring system that's based on IOTs, you can't have it purely based on human data collection either. And that's where the use of Earth observation data or most satellite information to sort of track on monitor what's happening on ground really becomes the source of enhancing the quality, the perception of quality of programs that happened on ground. So yeah, I think that's sort of quick and true to how we came about and what we're doing as well, but Javier Nate, you're out obviously and you have your own versions to this. - So briefly, some other dimension you all came down to India to sort of test your ideas. This was three, four years ago, 20, 22, 23 kind of their words. - Yeah, it was the summer of 2022 when we started exploring the thesis. - Okay, and we started the company. - Yeah, we came down for every. - All other company, late 2023. - Okay, all right. Can you also talk about, I know that, I mean, a little bit of homework. You and Javier met from Howard. Can you also briefly talk a bit about how the three of you got together? I mean, it is an anecdote about how you met Nathan. Whether I love the sandwich story from Howard, how you and Javier would get the same sandwich from the same cafe. - I saw this in the interview you did with him on lovely anecdote. Sorry, I'm gonna stop talking. So just a little bit about all three of you, a bit of background, how you got together. - Maybe I'll just jump in there and, truthfully Harry, I tease him a little bit. When I first met these guys, it was probably 2023 and they were at Harvard and I was working essentially at a card-man marketplace in Europe where I was kind of mapping tillage practices and these young guys. guys called and they said, "Hey, we're kind of interested in an MRV. Can you tell us a little bit about it?" And I thought to myself, "Oh, what are these young guys doing?" They're too green, they're too young. They just want to hang out and backpack across India, which is fun and cool, but are they really ready to start a business or launch a company? So we had that one conversation and we kind of followed up a couple weeks later. And I live about an hour and a half north of Boston and of course they were in Harvard and Cambridge and downtown Boston. So one conversation kind of led to another and we kind of kept talking and I thought, "Oh, no, these guys are these guys are serious and they're pretty passionate and interesting and kind of neat background. So we all kind of come together." So it was probably 2023 where I then drove down to Harvard and we were in the innovation lab and we started just writing on the whiteboards and kind of one thing went to another and maybe fast-forward three or four months and we were kind of getting all the the paperwork together to kick off an official company and do some fundraising and kind of get it all going. So to be truthful, initially I was a little skeptical. I said, "Oh, these young guys, are they really ready to kind of do this and take it serious?" And it turns out I was really the lucky one because I get to do this really amazing fun, fantastic work now. So that's how we got introduced initially in 2023. Yeah, I'd say it was really a bit of randomness to the process as I'm sure it is for a lot of businesses. The, obviously, Devon I had become buddies and spent a bunch of time together exploring, kind of almost discovering the space of rice together. I don't think neither Dev nor myself knew before we really started our exploration that rice emits over 12% of global methane emissions and kind of what that really means for warming, its impact on water, kind of the resilience challenges that rice farmers are facing today. These are all things that we explored over time and then kind of the deeper you go into a problem, I think we really realized that to build a solution for this challenge, it's not enough to build new financial instruments or to really build new solutions on the ground. You kind of need a full package, you need what we call a full stack solution, everything from the financing layer, the operations on the ground layer, but also the science and technology layer around leveraging remote sensing at really high resolution is something that just hadn't been done before and really is complex. And then the whole measurement of greenhouse gas emissions of water use yield. So, our approach when you find a problem like that really is to start reaching out to all of the experts. In a space like this one, you realize pretty quickly that the pool of experts is quite niche, quite small and kind of the same few names keep popping up and so, yeah, I think we were lucky that Nate answered our messages and wanted to support and one thing led to another as Nate said. Okay, you've spoken about all the different aspects of the problems that you're trying to solve with Metilabs, but can you kind of pull that together and give us a sense of what Metilabs is today? And I think one thing we probably not yet mentioned is that you're doing this, you're attempting to do this in a way that will sort of even financially benefit the farmers by helping them sell carbon credits because of the reduced methane emissions from their farms. Can you, so in your own words, you could pull that together and talk about what Metilabs is today? Yeah, maybe I'll shoot first. I mean, at the end of the day, what we're really doing here is there's there's a few problems that we can face them today, we can face them in 10 years, but the the realities that a few years ago already we had really high warming and tipping points that are going to happen. And as a society, we need to start finding what are the biggest levers of change that we can create. And so you really start thinking about, okay, well, what are the biggest sources of emissions that you can start tackling? What are the easiest to start tackling? And rice is, I think one that's being completely under-exploited, right? There just hasn't been enough work done for the share of warming that it creates for the share of impact that it has on water, and let alone the social challenge. And so that's really where you see an opportunity for change. You know, I go, okay, well, this is something that if we're able to do something about this problem, the impact will be pretty huge. At the same time, you start to think about, okay, well, who is responsible for this or who is really going to be willing to support this transition? Right? Because at the end of the day, most challenges at this scale that we're looking at will require financing, they'll require a lot of people on the ground doing work, they will require incentives, for farmers to adopt new practices. And so in a point in time right now where we're going through this, you know, AI revolution, which essentially just means a whole lot of additional energy usage, whatever type of energy, focusing on their hands on, you realize that we're really going in one direction and the direction is more warming. And so it's more important than ever today to, you know, from our side of the spectrum, keep thinking, well, fine, if this is going to be happening, whether we like it or not, what are the levers of change that we can keep pulling on? And so for us, rise has become the focal point of, well, this is a solution. How do we go and tackle it? For us, the key thing is to transition or to kind of solve the biggest problems in rice, you essentially need to convince about 150 million small older rice farmers to change the way in which they farm. Today they'll farm one way, which they've been doing for multi-generations. And over time, researchers have found that actually they make a few small changes and mainly how they irrigate their farms and the behavior that they use to actually grow that crop. Then there can be several impacts that won't necessarily be impactful for that specific farmer. They might not necessarily see a huge impact in terms of yield, in terms of, you know, their crop health. It's not that direct, it's more of a wider impact to society, right, to that community. So it'll have an impact on the consumption that they're having on that water shed. So kind of like how much they're extracting from their local river, from their bore wells. So they might not feel it, their children will feel it, or kind of like they will themselves feel it in 10 years from now. They will have a big impact on the pollution in the region, whether, you know, stumble burning is a large problem in the north of India. You know, they might not feel it themselves directly, but you know, Delhi will definitely feel it. And so you have certain problems like that. And so for me, how I see the problem, our job is really about we have all the solutions in place. It's how do you build a business model where you fit the different pieces together so that once it's all together, you know, you're essentially getting money to flow to the right places so that those solutions happen. And for us right now, it's really about how you get money flowing from the regulators and the corporates that are emitting that need pathways to actually offset those emissions into the hands of the folks that need an incentive to actually create a change today. So that's maybe a little bit meta, but at a high level, that's kind of what we're trying to do here. And we can dive deeper into what that practically means on a day to day, of course. Yeah, that's kind of what I was driving towards. I mean, they've been made if you want to add anything in terms of, I mean, as a business venture, that's also very heavily technology driven. Can you give us a sense of what the company is today, little bit of what it's evolving into? Yeah, maybe I'll start and it will feed around, but but yeah, again, like just to synthesize maybe what Javi is saying, I think, you know, as a business, your identity constantly evolves. But as of now, you can think of us as a vertically integrated carbon project developer, focus specifically on mitigating methane emissions from rice farming. What this means right now is that, you know, the pools of capital or the levels that we need to pull to make this change. One of the emerging thesis was that yes, the carbon markets exist. And as a result, you know, a pool of capital is available, the private capital is available to solve this problem. As compared to, you know, the traditional sources of capital for solving a problem like this, either philanthropy or through government spend. These are problems that private companies don't typically need to be the ones that solve it, but because the carbon markets exist, that's one level that we're pulling right now. In terms of what we aspire to be, I think we aspire to be the infrastructure layer that allows for the transition to climate smart farming. And let me go back to the first point, which is as a carbon project developer, what we have developed as assets is number one, this direct touch point with approximately 70,000 farmers as our scale exists today, which will be at 150,000 a few months from now. So that's the first point that we have a relationship with each of these individual farmers. Currently, the only notion of change with these farmers is a simple practice change, which is stop flooding your fields for the whole season, allow the soil to be exposed to air periodically. And as a result, you curb this rapid rate of methane and emission growth and you curb the amount of methane that is emitted. And in terms of the cost to the farmer, there's none. In the relationship that we build with the farmers is on the context of giving. We provide the tooling for free. We provide the advisory for free. And at the end of it, if the farmer is successful in making their practice change and we're able to monitor that and track that, the farmer also receives a reward for their efforts. So this becomes a very strong asset, which is this individual farmer that's called a distribution. The second asset, and I'll let Nate speak more to it, is this whole MRB infrastructure. So how do you use digital tools to collect information? How do you make farmers start engaging with the program more directly as compared to just field agents that go and make this practice change happen? What more can you do with remote sensing in terms of understanding not just whether they adhere to the practice change of periodically drying their fields or not burning their stubble, but also estimations on yield and so on and so forth. So what do you package up for different payers in this industry to leverage from an MRB infrastructure? And then the last point was around why we picked methane and rice. So number one, the scalability of the problem, I already alluded to it, but it stood out. And when you talk about economies of learning or economies of scale, it helps being focused on one intervention. And as I mentioned, 25% of India's agricultural land mass is rice farming. And when you consider all of Asia, you have 160 million hectares of rice that is grown in this region. And this is the largest region where all of these topics are grown. And these are the regions where you have big issues on water tables, et cetera, et cetera. So scalability of the problems, the co-benefits of the problems, which is in order to reduce the methane, you have to reduce the water. I think those are the two emerging thesises that stood out. The last thing, obviously, is that it's a fairly low effort practice change. And it's feasible, achievable. And as a result, your cost point of entry is a little bit lower than some of the other interventions that are being leveraged in the carbon markets. And we found that scalability thesis resonating well with buyers in this space where you can get high volumes for relatively affordable prices in terms of a carbon credit. So I'd say those were some of the emerging reasons why we picked to be doing what we're doing. I'll pause there if Nate, you want to add any more. Well, thanks, Devon. Just to layer in a little bit of the technology aspect, I was lucky that I got to work on a lot of cool projects kind of in my former life, former career, working with NASA and Jaxa in these different space agencies where they were very interested in essentially using different satellite remote sensing, particularly radar or SAR, synthetic aperture radar, protracting rice really for food security. They're kind of these big global food security programs that really want to know about how much rice is going to be exported or imported from different countries. Or if there was a big typhoon or a storm, maybe what would happen to production in the Mekong Delta and whatnot. So it was really geared at food security themes. And then it started to gain traction when there were some big price spikes in '08 and 2012. And countries kind of started hoarding or not exporting. So kind of different government agencies and space centered wanted more information on rice. Where's their rice? When is their rice? How much rice? And in parallel, there's now been a lot of new satellite technology coming into space in that SAR and that radar space. There are sensors like Sentinel-1, C-band radar, and now we have a lot more L-band, which is a longer wavelength. And without getting too into the technical components, those longer wavelengths can really penetrate clouds, penetrate canopies. So with all these new data streams, we can really begin to extract very specific information at field scale. How often is that field flooded? When is it flooded? And then we combine those different satellite data with high resolution imagery, like X-band, with Umbra. And we can really begin to understand what are the different management practices in a given field for a given geography? How many farmers are practicing traditionally irrigation? And then how do we begin to infiltrate and convert those villages, those farmers to these new sustainable practices and were able to really track and monitor that? And then essentially, we blend that with different AI, with different greenhouse gas models. And then we can really begin to tell that picture over vast scales, but very high spatial resolution. So kind of where I'm going is methane, a big problem, a really big impact if you want to help pull the emergency brake on climate change, addressing methane is really a top thing that we want to do. Then we have literally millions of farmers spread all across big geographies. Their fields, as Deadside, might be a couple hectares, maybe a dozen hectares. So how do we capture all that over space and time? So it's a combination of important growing global change issues with all these new technologies, Sarasatellites, AI, digitalization of farmer logbooks. So a lot of what we do now is blend all that technology with our ops team, with our field team to really help make the best decisions, help farmers optimize. So that's our core mission of where we're at today and scaling up as quick as we can. OK. So individual farmers are directly your customers. Do you also work with farmer producer organizations and other such organizations as well? Yeah, maybe I'll take that very quickly. The definition of the farmers, not necessarily our customer. Currently, there are a supplier, if you would, or they're the beneficiary of the work that we do. A customer typically involves them paying us for a service. Currently, that's being provided for free. Maybe someday they will be if we leverage this platform that we've created to do a lot more or do a platform of services that a farmer can benefit from. But as of now, I'd say the farmer is a beneficiary. So in terms of our go-to-farmist strategy, currently, the leading approach is working with NGOs and local grassroots entities that have spent a bunch of time winning the trust of that local community. So they may have done work on agricultural improvements, livelihood improvements, health care, education, et cetera, et cetera. So we work with entities that have got very hyper-local trust. These entities then recruit individual field agents within a cluster of villages or a cluster of blocks. So the people that are actually approaching the farmers are from the same community or known to the farmers, et cetera. So there's not just individual level trust, but also an entity level trust that we borrow and seek to leverage. We are also working with FPO's that have done the work of already aggregating farmer bases. And some FPO's operate better than others. So we actually do a grading and rating of how strong the management infrastructure of a given FPO is. And then we do make the FPO a focal point who then disseminates the training and the information that is required to each individual farmer. So yeah, I'd say those have been our leading approaches. So NGOs and grassroots entities working on field extension. That's the leading approach to reaching the farmer. But then also, yes, FPO's through NGOs sometimes as well, or directly is the second type of entity that we work with. OK. Can you give us a quick snapshot of what Mitty Labs has already achieved first farm? I mean, you already mentioned 70,000 farmers. You're touching them. They work now. And you want to double that in the coming months. And I would imagine you want to keep going that way. That apart, in terms of the commercialization of what you're building, should we see that as a tech product or a platform? How would you describe it today? And what's the direction in which it's heading? And other things like investors, funding, anything else that comes to mind if you could give us a snapshot? Yeah. Over the last two and a half years or so since we launched the business, I'd say we've really been able to build out this whole technology stack. That's allowed us to now have over 70,000 farmers that have not just transitioned to these new ways of farming rice, but actually achieved credit issuance. So essentially generating carbon credits from that transition, having those issued and delivered to our customers, which are corporates that are offsetting their emissions through these credits. So we've really gone through this whole loop in a pretty short period of time. To do that, we've had to obviously build these relationships with all these farmers, develop the technology stack, everything from the remote sensing side to the greenhouse gas measurement side to the data collection platforms for the fields on the ground, so onboarding farmers, training them, supporting them in this transition. So we've really gone through this whole loop. To do this, we've been lucky to partner with some really great investors, such as light speed in India, Boils, your ventures in the US, Cisco, a few other partners. We've got some exciting news that we'll be sharing the next couple of months on fundraise that we can quite share yet, but really it's been great to have really solid partners on the investment side, really solid partners as well on the commercial side. This year, we're looking to reach about 200,000 farmers by the end of the year, and we're really on track of that, probably doing even larger numbers than that. So we're really focused on expanding our work on the ground, we're also focused on productizing and expanding the features that our DMRV platform can do, really thinking about how do we prove things like additionality, really looking at how we leverage this remote sensing that Nate was describing to get further insights from what we see on the ground. I think we're building one of the most robust data sets in a very data scarce environment, which is smallholder agriculture. And so with all of that data, it's really a gold mine for insights. Already those insights are being used to obviously generate these high quality carbon credits. So the buyers that buy these credits from us are very interested in seeing this data to really get proof that all of this work is happening on the ground, and it's happening at the level of quality that they're looking for. We're also using this platform, our technology platform to serve some of the largest food and agriculture businesses in the rice space that might not necessarily be buying carbon credits, but are already working with a lot of rice farmers are interested in gathering new level of insights from the ground from their programs. And so doing that type of work. So yeah, it's been a pretty exciting few years. I think we've already crossed the 100 employee threshold. So we've got really an incredible team that's allowed us to get here so quickly, and we're growing incredibly rapidly. I'd say we're looking to expand outside of India, we're expanding heavily within India. So a lot of exciting things coming up as well. - And hey, Hari, just to jump in there, you mentioned the technology, we do have a lot of technology, and that's always evolving, always changing, right? That's kind of the one constant in the space for technology, it's always changing. So we have a lot, a lot of remote sensing, a lot of AI, a lot of modeling, a lot of kind of digital boots on the ground, but really I don't, and we don't necessarily believe that technology by itself is kind of a quote unquote product. While we get inbound requests to kind of leverage and license and rent our technology, really kind of the impacts is really the product for us, kind of the working with the farmers, the carbon credits as a vehicle to improve, you know, the environment and address these grand challenges. I think for us philosophically, that's the product. So yes, we have a lot of really neat, exciting technology. I believe we're very early in kind of the whole space economy, and it's scaling and growing quickly, but really the technology by itself, for the platform or all the MRV work, for I think for a lot of us is really just the tool to kind of get to that, those end impacts of helping smallholder farmers of addressing these big grand challenges. So yes, a lot of technology, but it's really about the impacts and kind of the carbon is really the product today at Midi. Okay, I want to ask you about how on a day to day basis, you work with the farmers and bring in the aspect of, I think something that's central to the work that you're doing, which you previously described as alternate, waiting and drying of the of the fields, but before that, if you could just take a minute, just around out the snapshot, just a minute on explaining your business model, how would Midi Labs make money as you go along? - Yeah, I'd say our core business model today is essentially in this generation of a carbon credit. So it's essentially, you know, Midi Labs will spend time and effort in supporting farmers through this transition. We will incentivize farmers to adopt this new farming practice. We will collect all of the necessary data from the farmers that have adopted the practice, so that have gone through a season and transitioned to their practice, and then we'll work with certification agencies. So organizations such as Gold Standard or Isometric that are essentially the ones that will ingest all of this data that we're providing, you know, the farmers, information, the plot information, all of the information related to what changes to place on the ground, and we'll convert all of that into essentially a credit, which is just a token, right? And it's equivalent to one ton of CO2 or CO2 equivalents, in our case, because it's methane, it's really about converting that into a ton of CO2 equivalents. And so once we have this token, this is something that we can then sell to a corporate that's looking to offset their emissions. In our case, we're currently mainly working within the voluntary carbon market, eventually this is something that expands into the compliance markets that are currently growing as well. And so that really is our business model. We sell this credit, that's the product that we're selling, and we use part of the money that we receive from this credit sale to pay for all of these operations on the ground to create this incentive for the farmer, so direct payment to the farmer, and then we obviously have our margin that covers all of the mythy lives as expenses. So that's really the core of the business. We also do have a second business line, which is really around the sales of data and insights from our technology platform. Currently, the main focus there is food and agriculture businesses, but that's also got a lot of potential of expansion over time. - Okay, all right, so let's talk about the alternate wedding and drying process. Maybe you can also give us a very quick history of how this process came about, who invented it or discovered it, how long has it been prevalent, and now you've kind of zeled in on it in getting the farmers that you're working with to switch over to this practice and walk us through the benefits of doing it, and then maybe from there we can get into how your DMRV platform helps or feeds into that whole thing as well. - Yeah, maybe I'll quickly take a stab at the history of how rice has been farmed. So before the advent of grid power across all of the country and techniques of developing and extracting water from different sources, etc, I think alternate wedding and drying was the norm, right? When rain fell, rice was grown, when it didn't fall, it was not grown. Then you've had advancements in obviously the government providing free energy, free water, and then an access to an MSP, right? A minimum support price and therefore guaranteed market. And as a result, you've seen the amount of rice cultivation increased pretty significantly and increased significantly in controlled irrigation ecosystems, right? Where even in the winter season, and there is no rainfall, the farmers are able to grow rice because they extract water from the ground and therefore they grow rice. So AWD was invented or was proposed by the International Rice Research Institution maybe 20, 30 years ago in order to sort of combat this overuse of water and stagnation of water and the thought process, I mean, you'd have to speak to them on why they developed it or how they developed it, but the thesis obviously was to, you know, in a way, it's a climate adaptation technology, right? You're teaching a farmer how to farm the same output with less water. Knowing and cognizant that water is a resource that is probably the most valuable and most scarce, but also one of the most under looked. And we always kick the can down the road and nobody realizes the urgency of solving for this water problem. I think, you know, Nithi Ayog will say India's going to need two times the amount of water than it has supply for and you then also hear that one third of ground water extraction is as a result of rice farming, and which is why you don't see this in many regions. like the US and Europe, very small pockets, but all of Asia is doing it. And it's also fundamentally important to the category consumption of these geographies and regions. So, yeah, it was probably 20, 30 years ago that it reproposed alternate wedding in drying as a thesis. And as I've already mentioned, I think the rationale is that it's a very simple to understand practice change, right? And the act or the action required by the farmers is to shut their taps off a few times in a season as compared to leaving them on pretty much the entire duration of 150 days that the rice is grown. And the benefits of it are pretty outside of the water savings and methane reduction is a couple. So, one is, if you understand, when is practice well and is practiced? What is the reason that farmers flood their fields firstly? The reason they do that is to curb weeds, right? So, they want to weed control by suffocating the weeds underwater and let the rice shoot out and therefore get the most nutrition and access to sunlight and nutrients, et cetera. The weed problem is more pronounced in the beginning of the season. So, for us, when we talk about AWD, we say, okay, fine, from the date of transplanting for the first 15 to 20 or even maybe 30 days, like you can flood your fields. And that's where weed control really benefits as a result of that sort of layer of water on top of the field. Once that period is through and up until sort of, you know, the panichel development or tailoring begins, you have a window where you want to try and dry those fields a few times and it has no impact on yield and you have a lot of peer reviewed research that will suggest that, not just in India, but across the world. So, it is a safe practice to implement. More interestingly, what we've noticed is, by giving stress to the plant at those time points, it's the right time to give stress to the plant. You actually have much harder panichel development and grain development. And when you consider the impact of less milky grains, sort of more hardier crop growth, that has benefits to both the farmer and then also to the mills that end up procuring this. And therefore, they have lower rice, broken rice percentage, et cetera, et cetera. So, there is a slight improvement in grain yields as a result of doing AWD because you've provided stress to the plant at the right time. The last thing is also, you know, stagnant water anywhere will increase the incidence of insects and, you know, BPH or mosquitoes and so on so forth. So, by practicing this alternate wetting and drying, you're actually killing a little bit of that activity happening as well. And farmers from a more personal and subjective gain, don't have to deal with, you know, infested feroos, et cetera, et cetera. So, that's one sort of added benefit, you know, to alternate wetting and drying. So, I thought maybe, yeah, that's a few topics that I thought I was sharing. And maybe if you want to add on the second question, yeah. - Yeah, just to add in there a little bit in dovetail, I think geographically it's fair to say that, you know, AWD probably started more or less kind of in the Philippines near Manila kind of where Eri's headquarters is. And then over time, there were kind of research projects in the Mekong Delta and Vietnam, a lot in China. In other production systems, there tends to be kind of hotspot production areas across the globe, right? Arkansas, USA, California, Indonesia. So, I think you will find over history, there were different, you know, trials of AWD and different conservation or sustainable management practices. And then that kind of dovetails with a lot of our DMRV work or our philosophy on the data science team and that we want these deep learning architectures, these crop greenhouse gas models, these AI models to kind of work across those different production systems. There's an algorithm and Bangalore work in Jonesboro, Arkansas, work in Bangkok. So, a lot of what we do is kind of, you set up pilot farms are kind of these supercites, these CalVal sites in a project domain. And we probably spend a season or two working with a set of select farmers kind of essentially measuring and quantifying and tracking all those practices and impacts. We kind of then tune our models, our remote sensing deep learning architectures or crop greenhouse gas models. You kind of tune them to those supercites in each project domain with the goal that each cycle, the transfer ability kind of gets better and stronger and more robust. So, a lot of what those tools do is essentially track who's doing AWD, how much or how intense is AWD? It's really not a categorical variable. Like, yes, they're doing AWD or no, they're not it, but it's really more of a continuous variable. How many dry downs, how often, how long? So, a lot of what we do is kind of track that across those different geographies and then kind of broadcast those models, take our platform and essentially drop it down in those different geographic domains to kind of scale all that up, to measure it, to quantify it, to kind of mint and generate those, auditable carbon credits. So, that's kind of maybe where geographically, AWD got started and then how it's kind of spread and spread if that makes sense. - Okay, so typically, what's the frequency, or what's the cadence of putting water in the field and then taking it out? And then can you give us a sense of how much water would be able to save? - Sure, the short answer is that there's variability across those geographic hotspots, right? And it might also depend on irrigation infrastructure or land preparation and big commercial production regions. Maybe they level that field to zero grade and they have recirculating pumps and tailwater recovery versus other places and more, you know, the developing south, maybe they use more contour leddies or small plots or have, you know, canal irrigation and bore wells. So you kind of have to have digital systems that are adaptable to those different regional management techniques. I don't, I tell folks, don't get too stuck on like the absolute numbers here, but kind of the relative percent differences is what's good to keep in mind. And typically, depending on all the moving parts, you'll probably save between 40 and 60% of your total irrigation water reduction. Now, you could go into a landscape experiment and really optimize that, you know, you could go into a field and maybe get the water used to drop by 90% or the methane to drop by 90%. But truthfully, those are highly manipulated kind of research projects, which is good and we want. But in the practical sense, for what we do, we want to do what the average farmer is doing. A typical farmer is probably not going to sit in the field every day and measure the soil moisture or monitor the exact moment, it gets to minus 15, et cetera. So a lot of what we do is kind of optimize the average farmer and track uncertainty, track quantification. We're happy to share data. We release a lot of our data, kind of open access. We want knowledge sharing and transparent data. Typically, you'll see 25%, 30%, operationally from an average farmer for water savings and about 50% 5% zero for methane reduction on average a typical farmer in our program. Just to add on the first point, I mean, AWD, the way that it's practiced is we essentially gave the farmers a simple, funny pipe as it's known in India or it's a PVC pipe with perforations at, you know, five centimeter intervals and we sort of install that pipe at ground zero close to the irrigation source and we train the farmers that typically a conventionally flooded farm would keep their water at plus five to plus 10 centimeters of water and you can see that in the pipe. Our objective is once that Safe AWD window begins that we want to see that field dried to minus 10 to minus 15 centimeters at least twice or thrice in a season. And what that means typically is that if a farmer is irrigating, you know, they feel, you know, maybe 50 to 60 times in a season, we're seeking to reduce that irrigation to approximately 30 to 40 times in a season. And as a result, that's when, you know, the water goes down to that minus 10 to minus 15 level and that's when the farmer knows, okay, fine, it's fine for me to re-wet the field and that's when they re-wet the field and that's essentially physically how the farmer sort of engage and practice, you know, make this practice changing. And can you help me understand a little bit more about on a day-to-day basis what is some of the top data, the most important data that you collect and please expand DMR view one more time for me. And what are some of the things that you're telling the farmers? I mean, what is the information that you're giving the farmers on a regular basis? - Maybe I'll start. So for any given cohort of farmers, we start maybe three months before their transplanting date is expected. So typically for a career season, we would start say, you know, career phase is the monsoon of the summer season as it exists in order of India. And, you know, typically transplanting dates would be June or July. So three months before that. So March 8th, April is when we start our campaigns on ground. We first start with village-level mobilization. So we work with a bunch of local stakeholders. So we call for the agricultural university experts, the agricultural officers from the government, the local KVK is the sub-punches, the NGOs that have operated and we do this massive stakeholder meeting where we explain why we're doing what we're doing. And this is at a sort of broad village-level campaign, let's see, and we visit multiple villages in that sort of road show. Then we seek to see how many farmers within a given village have shown interest towards, you know, trialing these practices or want to engage with these practices. then what we do is individual farmer onboarding and what that means is you know, speaking to the farmers one on one, taking a set of documents that we need, that okay, they own the land, this is their land record, this is the sort of plot that they own, we draw a field boundary, a digital field boundary, or a KML file of that farm, and that's what allows the remote sensing to take over. And then through the season, the field agents essentially post this onboarding window, we'll teach the farmer how to do alternate wedding and rank, so how do you install your pipe? You know, when should you irrigate, when you should not? And then there's obviously a large behavior change pitch that we aren't these field agents with, and more often than not, as I already mentioned, it's a little bit around this climate adaptation strategy, right? And farmers are perceiving the dose of water as a real need today, right? Many farmers are not able to take their second crop because that community doesn't have enough ground water for the winter season, so that one asset that they own is not productive or not as productive as it could be as a result of low water usage and low water availability, sorry. So we explained to them, or we give them real examples, they're okay in your boil. In your village, how many boils existed last year? How many boils existed 10 years ago? And more often than not, the number has increased pretty significantly. So when there was five boils in the village 10 years ago, now there's 50 or 100. How many pumps does it take for you to take water out for your normal drinking needs, et cetera? Like at one point, you could pump water after two or three pumps. Now you need to do 10, 15, 20, et cetera. So those are some of the real challenges that farmers face, and that's what we sort of leverage to communicate with them. And once the sort of pipe training and how to use the pipe and how to implement AWD is done, and the field agent essentially visits every single farm once a week and is collecting information of various types. So what seed did they use, what fertilizer did they use? Did it change from the baseline case? Did it not? Et cetera, et cetera. And that's how we collect sort of a digital farm log book that is then replayed and given back to the farmer as a source of information that they could use in the future. And then finally, we obviously take harvest details and we uninstall the pipe. So just on a day-to-day basis, it's not like every day that a farmer is visited, but once a week, our field agents are going and checking what's been the progress, have you had any challenges? And the advice is not just limited to AWD alone. Our field agents are a granomy graduates or are a granumist by nature. So farmers will relay a bunch of problems and we do what we can to solve some, if not all of these topics. So it becomes a little bit of a weakly check in from a fairly mean person that has the objective to sort of help them out more than anything. - It's very negative. If you can quickly jump in and just tell me what DMRV is and the most important data that you collect. - Yeah, good question. We call it DMRV or digital measurement reporting and verification, essentially all the metrics the KPIs, the kind of enabler attributes that we measure with the different remote sensing and data science and modeling, or another way to say that in kind of late terms are, there are certain levers that we want to help these farmers pull. And we can bucket those into kind of different management practices. So that includes things like seeding, or there's a direct seeded rice or transplanted rice, the irrigation management. That's really kind of the big one for us as a AWD, is it Meary, is it Farrow, is it conventional, or continuous flooded, and then another big one, just as an example, is kind of the residue. What do you do with that residue at the end of the season? Do you burn it, do you till it, do you bail it? There's kind of other ecosystems thinking about ways to kind of address some of the residue management and we collaborate with some of them. Organic amendments, kind of all these different management activities happen throughout the course of the season of growing a crop of cultivating rice. So obviously certain times of year, certain management activities are happening, seeding at the beginning, irrigation kind of during the cultivation cycles, tillering flowering, and then residue typically at harvest. So working with our ops team in agents, as well as kind of what we call our SIAPs, our science operation team, we'll collect different data points throughout the season for those different managements. And then we essentially train these models, these deep learning architectures, machine learning models of what that looks like in the field. Then maybe some sensors come every day, some come once a week, some are optical, some are radar, we kind of source all these different satellite sensors, some open source, some commercial. And we pull those into the platform. We kind of have our unique processing streams that we're now building on tens of thousands of data points that we collect every season. So we're able to kind of understand what's happening at that field as well as across the landscape because it's important not just to model what that one farmer is doing, but we want to understand what his management is in the context of his watershed, his village, is he unique, is everyone doing AWDs? Is it just four farmers? So kind of the DMRV platform helps track all that thing. We spend a lot of time on the data science team, kind of doing what we call physical retrievals. So we want meaningful metrics. What's the soil moisture? Is that field inundated? What's the leaf area index? Kind of all those physically meaningful indicators that we kind of put into this living breathing model that's kind of always growing and kind of feeding the ops team. So it's really a big kind of circular business where the DMRV technology is operating and feeding the agents, which then helps them feed more data to the system. And just to give you kind of one cool thing that we're pretty proud of now that we're working on is trying to make this a little forward going. So help forecast what's happening. So when a farmer should be irrigating or drying down a field, and maybe we can help feed our agents, feed our field team where they say, hey, these 10 farmers still have their fields flooded, they should really start trying to do a dry down, reduce that water. So that's just kind of one example of where we're taking some of that DMRV technology now, kind of making it a little forward looking to see if we can really help optimize sustainability, carbon credit, rice production. How do you get that sweet spot for each individual farmer? - Okay, this is a super, super fascinating to me. And if you'll indulge me in a couple more questions on the tech enabled side. Does it make sense to have like a smartphone app for a farmer like a MyMityLabs app? And is that a direction in which you want to grow? Does it make sense? And I think you mentioned automation somewhere along the conversation. So maybe I also want to talk about what are the ways in which various aspects of all these processes can be automated for you, for the farmer, and so on, and for your partners. - Want to click that tap? - Yeah, happy to. So yeah, I mean, this is something that we are pretty, keenly exploring, and it's, you know, we've completed our first cycle of issuances and payments as Javi mentioned. So that's obviously more often than not what trying to leverage the UPI infrastructure, et cetera. So many farmers have smartphones and are digitally enabled. There's a ratio that are not. So we'll see at which go and they pick up and have that digital literacy. So we can't have only model that works on every farmer sort of onboarding themselves, et cetera. So we'd have to have some kind of hybrid. But as we engage in the beginning, I think the support from an individual or a trusted partner sort of visiting that farm and working with them once a week is important. But once the program goes into steady state, I'd say, you know, we are in discussions of launching a WhatsApp flow to start with because many farmers will understand that piece, or then also building our own app, which, you know, the farmers can interact with directly and start feeding their own information directly to us, you know, without the need of an agent. And the agents will still exist, but maybe they roll evolves into becoming more broader support as compared to, you know, just enabling this practice change. So for us, yes, the flow would be, you know, one thing that we didn't mention in the DMRV infrastructure is what we call QHUC of the data that either the field agents or the farmers input. And we put a lot of, you know, agents and now a lot of automation towards that as well, right? So if you draw your plot boundary, does it match with the area that you said you own in terms of your land records? Does it not clash with somebody else's field, et cetera, et cetera? So those are topics that are QHUC infrastructure make sure in terms of, you know, the quality of data that is provided. And the more robust that that piece is, the more you can actually give agency to the farmers to sort of be, you know, self-serving, you know, themselves for the generation of these programs and credits. So, yes, I mean, it's in pilot. It's not something that we've deployed. And as I mentioned, I'd say the first few seasons, you do need that hand-rolled and that support. But once you've gone there, you can take the sort of training wheels off and try and provide as much maximum impact directly to the farmers. So it also means that when you look at the unit economic stack, like the more that the farmers do themselves, the less that we have to pay for, you know, operational costs. So these field agents and field extension costs and as a result, the farmers can actually make a little bit more money. So just to throw ideas out, like could we actually gamify this experience for farmers and say for every data point that they share, they get extra money rupees, you know, once it's validated and sort of approved. And that's one core component of the DMRB infrastructure. So yes, it involves a digital mobile app, which the field agents currently use. How do we sort of take that to a more distributed user base, which is the NFAMA, a QAQC system that checks these data points, whether it comes through field agent or farmer, on how robust and how truthful it is. is does it have logic? Is it you know, fraud proof, let's say? And then finally, the remote sensing infrastructure by which we can actually nudge notifications, currently to the field agents where we say, "Hey, the farms in your control, you have 200 farmers that you're working with, only 100 have done their dry downs and 100 have not." Because that's what we've seen from the remote sensing, what's happening with the remaining 100? Why don't you go into it? Or now when it goes to the individual farmer, like we say, "Okay, look, this is the right time for you to now start your, you know, drying activity, etc., etc. Over time, I'd say if we have a touch point with individual farmers, that's where the platform becomes a lot more meaningful. Can we give them price discovery inside market intelligence, provision of other benefits that the farmer can have by switching from fertilizer X to say a bio-fertilizer or from switching from this bestest site to something else, which is more effective blah, blah, blah. So, not to get too ahead of ourselves, but this is sort of the thought process that we're developing and engaging with as we speak." Sorry, quick, I think QAQC is quality assurance, quality control is there. Exactly, yeah. So quality assurance is mainly to ensure that the practice changes happen and quality control is before we send this for auditing to, you know, the registries and third parties that come into audits, I guess, that data fit for the generation of a carbon credit or not. Okay, a couple of sort of standard questions. Can you talk about really big opportunities and challenges from a Mithilab's perspective? I mean, throughout this conversation, you've obviously spoken about all the many different ways in which you can impact farmers' lives, climate change, and all of that saving water, and all of that. Dr. Mithilab's as a venture-funded company, you know, so overall, can you give us a sense of what you see as really large opportunities? And then we can talk about challenges. Yeah, I'd say maybe I'll kick off and let me end up jumping. Look, I mean, it's quite unfortunate, right? But the reality is that the way we're going, there's really a lot of problems to solve when you think about the heat waves taking place in India, when you think about the water level depletion, when you think about the delay and of seasons, the disruption in normal monsoon cycles, all of these things just really cause a trickle effect in everything from farmer livelihoods to the commodity of rice, which obviously a lot of people need to depend on. So really, these are all challenges that become opportunities for us to tackle and solve if we're really working towards more resilience in the crop of rice. Combine all of these challenges with now, additional interest in more data centers, like consume even more water, consume even more energy, and so you really have this effect that's going on right now where we're really going in the direction of you know, more of these resilience challenges that will keep popping up. And so for us, this is obviously something that motivates us to continue doing a lot more of the work that we're doing to do it as Nate mentioned earlier, not at an R&D level, but rather really at scale, to help develop what we think are the right blueprints for governments, for large institutions and the space to pick up and adopt, and adopt whether it's within subsidy channels or whatever other instruments that can be done. So for me, this is kind of again at a macro level, really what's exciting, there's we're seeing a lot of you know compliance, market activity coming up, whether it's Corsita with airlines or the Japan ETS market or you know Singapore article 6.2, there's a lot of I'd say demand drivers for a lot of the work that we're doing, and so this is really going to be driving more and more opportunity for us to continue scaling the work that we do. And so from from a macro lens, this is this is quite exciting opportunities. Of course, you know, and maybe Nate can develop more on this, there's a whole lot happening as I'm sure you've seen on everything that is earth observation side, new satellites coming online, you know at the end of the day we are really a data company and we use that data to do a lot of things in the physical world, right? But you know obviously more satellites means more information, more data that we can collect, and we can test again. And so there's a lot of excitement there. So yeah, there's just a few opportunities, maybe I'll pass it to to Devonator, there's anything you guys want to add when we can discuss challenges as well. You know, for me the biggest opportunity without a question is you know our our vision of you know tens of millions of smallholder farmers helping them improve lot of the hoods and prove resiliency, that's the biggest you know motivator for me. I do believe it's still very early kind of in the whole space economy and even carbon credits are still forming. I think it's fair to say that there's a lot of new companies and startups and big companies trying to you know figure out how to do carbon programs and different scopes of emission types. So that's kind of created a big delta of quality out there and that's okay because the market is still early and it needs to develop but it can be hard to distinguish between those tiers of quality. So there's you know carbon credits that are maybe just the notcher two above greenwashing versus you know super robust with high go with high co benefits. So helping buyers, corporates understand that delta you know is just kind of one current commercial challenge that we're working through not just midi labs but as a community. I'm optimistic we'll get there but it's it's changing quickly but as as Javi said with with kind of all the advances in an AI and in our system change this is going to happen very quickly and I'm very pro equitable you know economies for smallholder farmers and and we want to kind of share in that those resources. So that's kind of a current challenge that that I like to think about. You know geographical expansion is one so we exist in India and we've entrenched a pretty key rice growing states within India there's still a lot to go so that's one opportunity to expand our programs within India and then you can add other geographies as I've already mentioned Southeast Asia etc etc where you stay focused on the rice thesis. The second is you know how do you sort of work upon the vertical stack of services you provide to farmers right today it's a little bit more around the impacts from water and methane but then there's also impacts on yield there's also impacts on how these farmers are financed etc etc so how do you sort of increase the the value that you create per per hectare of perform that you that you work with. The third is how do you attract a wider set of payers today the the main pair for our work is the carbon markets but then how do you as Chappi mentioned get the governments to sort of you know look at this problem statement since we've built this MRV infrastructure now can we use this as one of the sources of distributing subsidies that the government seeks right so today if you look at the energy spend of you know the government on agriculture it's very large the subsidies that they have towards fertilizer very large so can you chip away at some of these things make the farms more resilient make the soils a little bit more healthy you know make the farms draw less water etc etc and this really taps into a state government or a local government or even the central governments budget so I'd say yes diversifying the payers set diversifying the you know the geography diversifying the platform of services that we offer to the farmers these all present themselves as opportunities as a quick summary and and any points on on challenges both specific to mid-tillabs as a developer technology and and also German to the markets in which you need to operate what what might these challenges be yeah I'd say like as a business of course we said earlier right we just crossed a hundred employee mark obviously you know less than three years ago is a definite and myself and so you obviously start facing a lot of challenges in how to continue scaling this team I think for us the focus is really keeping that density of talent incredibly high so how do we scale the team while continuing to to really on board really strong talent and and the realities that you know the majority of our teams sits in India we've got some colleagues in here in the US as well in Europe but all over we're seeing really passionate folks that are really excited by the mission that we're building on so there really is a lot of talent but but we're really keeping that standard high is probably one of the core focuses that we have right now and then I'd say that in terms of challenges as well kind of outside of within the organization so really a little bit more uncontrollable for us is the day our our user base is the smaller farmers and I think there's going to be a lot of disruptions and a lot of challenges that they will be facing in the coming years and and really being able to support them but also manage our programs regardless of be weather events and other challenges that will come from the environmental factors is going to be something that we're definitely spending a lot of time thinking about. Let me ask you about the vision for our Mitty Labs, so sort of in the foreseeable future, three years, five years, down the line and probably another way of connecting that question to the opportunity. How do you look at this vision? I mean, at the practical level, do you think about, is there something for which Mitty Labs can sort of become the de facto platform or provider or a sort of a more philosophical level? How do you look at the vision? And we can all three if you can sort of take a stab at this. Yeah, I can't even start with that. I mean, look at the end of the day, what we're really building here is we have a, we've built a technology platform with access to data at a time where data is super critical, right? I mean, you've got all these new AI models and all these new technologies that at the end of the day, all you need is to feed them with really high quality data. And we've seen a lot of advancements in places like Alalens where you just got unlimited wealth of data online, right? In the physical world, in agriculture, and mainly in places like Indian Southeast Asia where this data is just not accessible, there is a whole lot of value in generating that data, which we do constantly day in day out. And so once you've developed that asset, there are really endless possibilities of the products and services that you can develop using that. And so that's something that we're very excited about in the medium term is how we continue developing really innovative products and services with this technology set that we have, everything from remote sensing to biogic chemical models and really leveraging that data platform. I think another area that we're also very excited to continue exploiting and this growth of partners on the corporate side that are going to continue to deliver services to their own customers. And in order to do that, they will continue consuming resources and they know that they need to be responsible to their shareholders, to their customers, to their employees in offsetting these, in replenishing their watersheds, in offsetting emissions. And so really being able to support those organizations in those efforts through the work that we do on the ground, I think that's something that we're going to continue finding new ways to do that, whether initially the interest was very high on methane and overtime waters becoming a very key topic. So really how do we support organizations in working on the water piece. So there's really exciting ways in which we can continue supporting these customers. That's it for this episode. We find relevant links to mid-tea labs and the founders' bios in the show notes. To support my work please subscribe to my posts at indiatechreport.in. I'm Hariyaki and signing off.