 Love Languages is Food, so at Jelada Menfonya Povizuri Sana Kwayo Video. I hope you have been with us. If you haven't, please welcome, welcome, welcome to the show. This is why in the morning, only on your favorite channel, that is Y254. I am Valentine of One Boy, ama. Color me, val, on everything, Karibu Sana. This is Entrepreneurship Tuesday, and we are going to have a very interesting conversation on AI. I know you've seen these images on social media where, you know, AI, they're generated pictures and all these things, but we're going to take a different angle. And I think one that hits home, especially now with the worrying state of the economy. Now I'm going to allow my guest to introduce himself before we get into the heart of the matter. Good morning. Thank you so much, and thank you so much for having me. Yeah, thank you. Yeah, so my name is Joffrey Nyaga. I run a drone company in Kenya that is specializing in agriculture, where we are using the technology together with AI for food security, advising farmers, figuring out the areas on the farms where are unhealthy. Before you can see them with your naked eye, predicting yield so that we can be able, even before the market, being able to predict how much yield are we going to get and doing things like counting of crops. And all of this is being enabled by the drones that we are flying and the analytics that we're able to do out of that. I'm sure majority of us have seen a drone like in a wedding scenario, where just taking photos and selfies and that kind of. But there's much more that you can be able to do with artificial intelligence, especially in the agricultural sector when you're looking at food security. And that's what we've been building for the last five or six years. And I'm very excited to be here to talk about the achievements we've been able to make in Kenya with our own technology here. You look excited. Very much. 2015, first of all, it sounds very early to start with the drone, because we haven't started hearing about drones until a couple, two, three, four years ago to Kenosana. Yes. 2015, we must have been just breaking the market. That's very interesting. One, and two, yes, our particular demographic only has been exposed to drones in terms of, you know, like you said, weddings, music videos, basically, entertainment. Entertainment, yeah. So this is quite new, and it sounds very exciting. So let's start with already the current situation in Kenya, where we've been hit by a couple of environmental disasters. Yeah. They say the F word we don't like talking about. That is samite. Samite, yeah. So tell me how you have maybe played a part in curbing this particular situation? Yes. So a majority of the problems that stem from the food security in the country, you can trace all of them back to lack of data, like do farmers know when to plant, what to plant, depending on the region they are at. Even during the planting season, throughout the entire life cycle of this plant, do the farmers have an indication of the performance of their farms and also what to expect? And so we found this gap where, especially looking at smallholder farmers, as we say, Mamamboga. So this is something that the farming is not data-driven. And we looked at the comparison between large-scale farmers in Kenya who have the money and the expertise and the talent to do that. But the same is usually not translated to the smallholder farmers. So you find your normal big farms, they always get their targets. But if you look at, like when I was growing up, my parent was a smallholder farmer. So how can we better equipment with this information? So for example, one of the things, one of the exciting things we've just done for one of the counties is, they wanted to do value addition, as we've been talking, for mangoes. But nobody has an idea where the mango farmers are. How many mango trees are there in that county? Per farmer, how many mangoes do they have? So usually, the majority of these things is guesswork. You go ask a farmer, how many mango trees do you have? I think like 40. So even when the county is trying to look at aspects like, where do you build a distribution center? We really don't have the data to do that. So one of the things, for example, we've used the drones to do is map this area, tell you exactly where the farmers are, how big their farms are, how many trees each farmer has, and also like a prediction of output for each farmer. So even as you are creating value addition, you're doing it from a data perspective that has been autonomously done by the systems that we are building. And we think that this is something that we need to scale. The second thing, just quickly to touch on that, when you're looking at, there's another part we're working with a cooperative that does a lot of barley. And you find that when they're trying to estimate how much barley their farmers in this cooperative are going to sell, because majority of these markets, you have market linkage companies who come and tell you, I'm going to buy your product when you plant it. So you find a lot of people overestimate. Somebody says, I have five acres, but they're only planting three or one, because they've subdivided the rest of the land to their sands and other things. So you find that most of the time, the amount of products that we are expecting to have in the market is not the actual number because we've overestimated or underestimated. So, but using drones, what we're able to do is we map all these smaller farmers, we're able to quantitatively tell you, like this farmer has this amount of produce depending on the crop. And this is what we expect, then we track that. So we are looking at how can we embrace technology, especially using drones flying up because you can cover a lot to generate insights that then go to feed a lot of systems from access to loans, access to insurance. Like now when it's farming, you talked about farming. So one of the projects we are actively actually doing is in the livestock industry, where majority of, with an organization in Lakepea County, when farming comes and there's devastation, it's usually very hard for farmers and even livestock farmers to ensure because there's no tools to measure the extent of loss. But now with drones, what we're able to do is map these areas and actually quantitatively tell you this is the extent of loss for these people I've had. And then that data is now being used by insurance companies to sort of now help out because now you can have a single source of truth. So this is the technology we are building and looking at how we can also go into other industries, one industry at a time to generate a positive impact and especially when you look at sustainability aspects of our economy. How precise is your data and what's the margin of error? To give you a perspective, drone data is very high resolution. So the way you visualize how a platform works, you've used Google Maps to see around. And so it's like, if you had Google Maps, but you can zoom all the way down and see rocks and blades of grass, that's how high resolution it is. So if you are mapping, for example, like a farm, we are able to tell you, like count all the crops, you are able to see where the weeds are and advise the farmers. If there's like water logging issues which we've seen or any other underlying issue, you're able to see that. So it's virtually as if you are looking with your naked eye and what that has enabled, especially like the cooperatives and the extension officers to do, is instead of somebody going with a border border to each farm, you get out, you start working the farm looking for diseases, go to the next guy, next guy. The drone is able to cover like one drone, like a thousand people in like six hours. Then we're able to tell you, okay, for that farm owned by Mrs. Njoki, go to that corner near the tree, the crops there are the ones which are damaged. So we reduce the time that a lot of these extension officers and cooperatives are taking to isolate issues so that they can use majority of that time not to address these issues. And that is now what is leading to this increase in yield that we are seeing. So it's very exciting and the most scary part for us is it's not even what we've started to do, it's just that every time the possibilities of even the more requests we are getting is what is actually scary because with that now, you can virtually be able to scale and do quite a lot. I like that you brought up the difference between small scale farmers and large scale farmers. And just out of curiosity, I know we, especially if it's a generational type of situation, so if my grandparents were farmers, then my parents are farmers, then I probably will be a farmer. So the seasons at which they planted or harvested are expected to trickle down. But do we count climate change and all those wonderful things? Is that now where you come in with the data as well? True, I would say 50% of that plus something else. So if you look at generation wise, I was lucky enough to see my grandparents' farm, then so my parents' farm. And now even in my own private capacity, I'm also a small holder farmer somewhere. And the shift we are seeing, the advantage with Kenyans is one, everywhere we've gone, we've seen the positive attitude that farmers have and their need to, as long as for majority of Kenyan farmers, if they see a value in something, they're not afraid to try new technology as long as it's going to help them solve another issue that they have. So even as we are trying to solve the issues of climate change, drones being part of a solution among other technologies, we've seen that generation wise, at least for the current farmers that are there are willing to embrace new ideas, whether it's new seeds, new types of farming, new ways of conserving water, and also consuming data, whether it's weather data or any other type of data. But coming back now, which is the most important issue of what you've suggested, we've found that majority of these cooperatives, they are working with other organizations that now a lot of farmers are being sensitized about climate change. Because of two things, first of all, they can see it, they can feel it. I've been places where they say, for the last three years, we've not seen any rain. So they know that. And now we are also working with these organizations that are now sensitizing the farmers, teaching them because now you have to change the way you farm, the approach you do, how you do your irrigation, how you do your chemicals and everything in between. So the aspect of climate change, I think it's something that will have to be tackled from multiple angles. Now, for example, for us, what we've been able to do is, we are the data bridge between all the actors and climate change. And I can give you a few examples. So like now for the pastoralist community, I told you about, we mapped the Awa Soniro River to sort of showcase over time, this is how the river shrunk. And you can be able to see that. In the same area, there's like a forested area where we are able to see this is how these forests have been affected. We were able to count all the exotic trees and indigenous trees using AI and then show because of climate change, this is how now people are being forced now to go to the forest. And now this is leading to deforestation because there's not enough resources. Then the third thing that struck out of that is that there was this spread of rift valley fever, I believe it was the name, that it's a disease that gets transmitted between animals. And the reason this disease is being transmitted is because the more fewer water resources the farmers have, the pastoralist, means that they have very few horses where the animals can get water. And so usually what happens is that now you have more huts of animals congregating to one place from different villages and all of that together with all the animals. And so with drones now, there's something that we're able to easily pick out and now say, okay, here's the source of the problems is where the diseases are spreading. Yeah. I did not see that coming. Yes. All right, okay, that's great. Okay, forgive me for asking this, but it's a necessary question. Africans were very set in our ways and I imagine your services come at a price. I don't know how big or how small, but have you met any kind of resistance and like, ah, you're telling me something like I just walk around and see, ah, ah, ah, I can just look at this guy and see if the rain is coming. Have you met resistance of any kind? Yes or no. So remember what I said, Kenyans are very good at adopting technology as long as it makes sense. What I meant by making sense is that price is right. And also, like, it's going to add more value with the investment they make. I can give you another example that I didn't mention. One of the services we offer, we have like a huge spring drone, like it carries like a lot of water, it goes and sprays the farm. So you find like when we price that, we price the same price like less than a tractor and just slightly more than a person. And what this drone does is that it sprays like five acres in eight minutes and it's more efficient. You don't lose your chemical, it's digitized. So if you put a certain amount of chemical is to the last drop. And so when farmers, you go and tell them, hey, I'm cheaper than a tractor. I'm six times faster than this tractor and 15 times faster than you giving guys pumps. To go around, it's safer. You don't breathe it because the thing just flies itself. And you won't waste your chemical. Then they're like, the price makes sense because it's cheaper, it's faster, it's more safer. And I don't waste my chemicals because now, if you go now, like with what people are doing, especially in large farms, giving guys pumps, you find that there's not a lot of safety because people don't wear masks. The same guys in some areas, the same guys you give to spray your farm, they're also your neighbors and they've planted the same maize. So when they go in, they also chow down. Small for themselves. And a few other things, so they get tired, they skip. But the technology that we're building, the autonomous systems don't do a lot of these things. So we found that price-wise, it makes a lot of sense. I'll just maybe give you another small example of what we've done. Our drones are also being used, the same AI to help in the health sector. So like one of the problems we are having right now, it's like spread of diseases. We've actually done a lot of work in Kisumu, Mombasa, for malaria mapping, where right now in trains, there's a lot of water puddles all over the place. And it's very hard for government and other agencies to find out where this water is so they can send people to spray the water. And so what our drones do is, you fly the entire area, like we've done the whole of Deania as an example, and pick out where all the trash is, all the water bodies are. And this is being done autonomously. The AI picks it up so that when they're sending it, Kazikua vijana or guys to go and clear the bushes and the trash is targeted, like go there, go near that house, go near that house, and then you can be able to measure impact. So the cost of these guys deploying, like 50 guys to go around every corner behind every house to look where it is and record, like on a piece of paper, digitize that, it's usually much more than it takes to. And we saw that case, for example, in Isiolo where manual labor, they have to send like 50 guys. When you send this 50 guys, you have to buy the milk or these things, it's tedious, it's not autonomous. So when you price it, then it usually make, but we are usually cheaper than the traditional means there is of collecting that data. Is that by design? Did you set out wanting to be cheaper or? So there are two ways you can run a company and we did this very deliberately. One, because you're making tech locally, we are not relying on any AI system from anyone outside the country. We build them from the ground up. Second, we are building to scale. We are not interested as entrepreneurs to build a solution that only works, let's say here in Nairobi, but does not work in Mumbai, or works in Mumbai, but does not work in DRC or does not work globally. So actually, like for AI system, the first users of our systems, like the first three customers were not even Kenyans. So right now, the first client we ever had was Stanford University in the US. It's one of the biggest universities in the world, like using our software to do a lot of these things. We've had researchers and all that. So because we're building to scale, we have to work with a pricing mechanism that is inclusive of everyone, because when you look at smaller farmers, the margins are small, and you cannot afford to overcharge. So, but how can we accelerate this development of technology so that every Kenyan at the end of the day, you can go to your phone, you see what your farm looks like, where all the problems are. And we pick plant by plant. We'll actually tell you, go to row number 10, crop number seven, that crop has an issue before you see it with your naked eye. So we work with cooperatives to make it much more affordable. And then without, we've seen a significant scale and we are interested now to roll this out not to the rest of the world. Wow, you're very impressive. Okay, last question before we have to wind it up to the interest of time. There is a danger, and this is something that was rolled out by tech giants elsewhere. That AI may just overpower us as developers and which I find is ridiculous because it was our idea in the first place to, you know. So do you believe there'll come a time where we in technology will, you know, kind of call it quits and start from scratch? No, I don't think technology is going to replace anyone per se, but for those people who are not going to, specifically AI, for those people who are not going to embrace it, they are the ones who are going to be replaced. But the people who are going to embrace it are going to be 10x better than what they do. So if you write blogs, you have just GPT, it means you can write 10 blogs in a day, diversify, even into industry that you're not well aware of and generate more content. But for the writer who says, I won't use this, then the people who are 10x better now than you are the ones who are going to take. So every technology comes at an interesting intersection as humanity where we have to, it's like when the car came, people said, oh, horses or these things, but the people with cars, you're able to get to work better, travel faster, open more trade, and all of these things, the same is going to happen with AI. My prediction is this, with AI is going to make all the work we are doing much better, regardless of the industry that you are working with. The reduction in time means that as humans, we can spend more time in more productive things and spending a lot of time in things that maybe don't generate more revenue. And at the end of the day, it also comes at a point where, and this is for me speaking to Kenyans, when we looked at first industrial revolution, we were out. Second industrial revolution, we were out. That industrial revolution, which was mostly the dot-com era, we were almost there, we just came in a bit late. In the 90s, we just came with our M-Pesa right around the millennium when we were starting off. But now this next step that we are coming with the young people that we have, I mean, our median age is 18, most of the guys here are tech savvy. We cannot afford as a country to miss out. We've been late in all of this, at least for this one. Please, all the young people who are watching me and the government and all the people making decisions and entrepreneurs, we are on it. We have the same experience as anybody else in the US. It's something new. So why can we not take it up? Make it our own. The same successes we had with M-Pesas and everything that we've done locally also transformed that into something that puts us on the map, like already it is with us in the drone space. And make that also something uniquely African, uniquely asked to solve our own problems and also lead the market in this globally. And I think that's where we are going. I am all about solving our own problems and I can't wait to see more TED talks with Africans pioneering. Please. Last words before we round it, wind it up. Yeah, so the drone industry is an interesting space. We are only two years old as an industry. Purely run by young people. You won't believe me, like in my company I'm the oldest guy. So majority of these guys who are doing these things are guys who are still in campus and doing all of these things. So I think this is an industry where with the right support, like what the government has been doing, can generate a lot of employment opportunities and also opportunities for young entrepreneurs too much because an industry for young people and it's what I like describing us. It was like made in heaven, by God himself to young people because this is something like, of course you'll never see like an old person with a drone flying. So this is something that is uniquely ours, for us to dominate, for us to expand it across the borders. And for any young person that is looking to join this, you can start off with our website where you'll see some of the work we are doing, which is www.swiftlab.tech and also on all our social media pages, is swiftlab.tech, LinkedIn and Twitter. And personally you can follow me at Joffrey Nyaaga or on all social media handles on YouTube. All right, you are a force to be reckoned with. Thank you so much. I cannot wait to see what the future entails. But now we really, really gotta leave, gotta go. And I think I'll do it on behalf of my co-stars as Brian Sakwa 101 likes to say. So from myself, Valentine or at color, me Val from Stephanie Ayeta. And Brian Sakwa 101, we wish you a fantastic day. Be safe, we'll see you tomorrow. Have a wonderful time.