We have a discussion with Felipe Ayerbe, the CEO of Demetria on his innovative Agtech solution and the recent deal with Nespresso. We ask him about progress at the company, how Nespresso is using the technology and what this means for their farmers. <\/p>\n\n\n\n
So we’re here with Felipe Ayerbe, who’s the CEO of Demetria, and I don’t get to pronounce Demetria correctly.<\/p>\n\n\n\n
Yes, yes.<\/p>\n\n\n\n
Perfect, wonderful. When we spoke, I mean, a few months back when you were just launching very exciting products, which which which which people can go back and take a look at. That video we won’t dwell, too much on that. But you’ve got some pretty exciting news to say. I read your your press release a few days ago, which was under embargo, I think, until this will get released, which will be on the 4th of August.<\/p>\n\n\n\n
And the first thing that crossed my mind was, wait a minute, how did we get how do we get here so quickly? And so so probably the best thing just for those that are new to your company, why don’t you give us a quick one minute overview of of who Demetria is and and then we’ll get to the get to the news.<\/p>\n\n\n\n
Yes. Well, thank you very much. Good to see you again. Yeah. It seems like ages ago it was only five months ago. So so what we’re doing is we are the first company who has been able to measure taste in green beans. So we’re able to predict what the taste is going to be of green beans it once it’s toasted, but we’re doing it on green beans and we’re using revolutionary technology, which is portable sensors and A.I. to do this.<\/p>\n\n\n\n
And so essentially what we’re aiming to become is sort of the new industry standard. Right. Which we do not want to. Basically, what we want to do is digitise the most important variable in coffee, which is taste, and not only be able to measure it ubiquitously, but to put real big data applications into work.<\/p>\n\n\n\n
And one of the things that just sorry to jump in quickly, because one of the things that jumps out at me when I when I first saw your technology was just how small and compact it was. This is the thing the size of what I was going to say, the size of a thumb, but is smaller than a phone. It’s a tiny little handheld scanner that pairs with your mobile phone, right?<\/p>\n\n\n\n
Yes, that’s that’s correct. In fact, I have one here that I can show you. Yeah, let’s see it. I have big hands. But still, this is this is the size. Right. So it’s literally the pocket size. So that is that is part of the revolution that sort of we are piggybacking on is that with sensors and everything like that, this this technology has been around for for quite a while. But like with computers and with cell phones, everything has gotten miniaturised and democratised as well.<\/p>\n\n\n\n
Right. So this sensor I know 10 years ago would have cost tens or 20s or 30s, even 50 thousands of dollars, and it would wouldn’t fit in this table. Right now, it’s at the palm of the hand, its cloud connected. So it enables a lot of the things that we were we are doing.<\/p>\n\n\n\n
Right. And and so this is a scandal to you holding your hand. You literally just wave it like a magic wand over the green beans. And it’s using, I think, light sensor technology to pick up attributes of those beans and be able to interpret them not only for taste profiles, but also for for understanding the origins as well as that, correct?<\/p>\n\n\n\n
Correct. Correct. So what we found is that because at the end of the day, what we’re measuring is, is the chemistry of the of the of the green coffee beans. But we are not directly measuring the chemistry. We’re not interested in understanding how much caffeine or how much clchlorogenicoregenic acid. or how much sugar it has. We’re interested in the chemical sort of markers and in the way they represent sort of what we feel is taste. So. So essentially what we do is this this technology basically looks at the chemistry of the coffee beans, but through light, through optics.<\/p>\n\n\n\n
Right. So it is it is very versatile in the sense that it is it’s not destructive. So you’re literally just shining light on beans and and reading what whatever that sensory fingerprint does.<\/p>\n\n\n\n
Great. Well, let’s get on to the news that you that you’re ready to announce. I don’t want to steal your thunder. I’m going to let you do the talking, but it’s quite a big deal. Why don’t you especially for a company, frankly, as young as as you are. Why didn’t you want you to do the big reveal?<\/p>\n\n\n\n
So. So the big reveal is that despite the fact that, yeah, we’re a very young company, we in November. Just recently, right, we announced in March, but it was only in November last year we were able to to convince the industry that this was, in fact, possible. Right then we showed it with with an actual working production of an application that is 90 percent accurate. Right. So this is comparable accuracy to to an individual or very experienced cupper.<\/p>\n\n\n\n
So before that, a lot of the people in the industry told us that we were crazy. You couldn’t do that, that that’s impossible. So in a very short timeframe, we what we were announcing is that we are starting a very ambitious project with Nespresso, which is one of the evidently one of the leaders in the coffee industry and one of the leaders in in understanding and embracing this technology and how it could impact their whole value chain. And our our initial work with them even is not necessarily related to the coffee beans per say, but it’s also related to the the way they manage an integrated value chain and they want to get the highest quality possible.<\/p>\n\n\n\n
So in fact, we’re using the same technology. But instead of using it on the coffee beans initially with the special, we are doing that as well. But we’re using it to help them ramp up their production capacity for seedlings where they plant these seedlings for farmers and they give them for farmers. So we produce the grafting application that allows somebody at the field to understand if that seedling is viable to take to the to the field, then plant it.<\/p>\n\n\n\n
And so it’s it’s it’s it’s very exciting for us, not only because it’s a new it’s a new sort of areas of application not related directly with the green beans, but it also gives us what we want to achieve, which is a complete value chain sort of transformation through technology to the whole coffee industry.<\/p>\n\n\n\n
So I know that it’s interesting you say about the seedlings aspect of it, and that is that’s something new to me, too. I don’t think we touched on that last time. So we didn’t so, and in fact, one of the questions I was coming into this conversation with was that I know that you have different applications for the technology. I was thinking of all of them on green beans, but also in terms of whether you are coming at it as a buyer of those beans or whether you’re the farmer.<\/p>\n\n\n\n
And there are different ways that you can you can use an application depending on who you are. So now I seen so I was coming in with a question of like, so how is how is Nespresso using your technology? And you’ve partially answered that by saying, well, actually, no, actually, we’ve got something else now, which is also the seedling. So you are you’re really broadening out the spectrum, pun intended and the. But but but what else are they doing?<\/p>\n\n\n\n
Can you just give us a little bit about, I guess, trying to understand how how this is a value to Nespresso. And it probably helps put it in the context of actually how Nespresso works with farmers, because if you can explain that first and we can see how your technology plugs in.<\/p>\n\n\n\n
Oh, so Nespresso is is relatively unique in the sense that they they already have a very organised and integrated value chain. And so they know with first name and last name who their one hundred thousand farmers are across the world. So they know them. And so they work very closely with them because Nespresso is in the is in the business of very high value high, the highest quality possible. So they work hand in hand with them. They have agronomists that help them.<\/p>\n\n\n\n
They have a very close relationship. So one of the things that they’re doing is they they have developed a series of new sort of genetic varieties of coffee that produce very high quality coffee. Now, these generic varieties are hybrids. So they’re they’re they’re a hybrid between a European variety. Most of Arabica coffee came from Ethiopia, but this is sort of new varieties of European coffee that have been adopted, for example, for the climate of Colombia. And the reproduction of these varieties has to be done by grafting if you don’t know what grafting is.<\/p>\n\n\n\n
But essentially, it’s like magic, right? You basically cut a piece of one plant and stick it into the roots of another and it becomes a new plant producing whatever you want it to produce from the. The top end of the stick, if you will, so it it it accelerates the process of adaptation because it allows you to produce high quality coffee, but using the roots of a more established plant that is more robust for that particular environment, if you will.<\/p>\n\n\n\n
So in what we are solving is that these grafting process, it’s surgery at the end of the day. Right. So you cut the plant that you need to stick it together. And so some of those surgeries are not successful. And the problem is that you only find out typically late in the game. So once you’ve planted it or you’ve taken it to the field and where you’re already fertilised, that you’ve you’ve incurred in a significant amount of cost before you do that.<\/p>\n\n\n\n
And so what we develop with with the same applications, same sensors, same technology is an application that allows us to understand and predict what is the survivability of that seed so they can understand what what seedlings they are ready are to to take to the field and. Prior to this, the only way that they could do that was with an expert, so an expert had to sort of examine each seedling by each seedling and say, OK, this one is viable, this one’s not.<\/p>\n\n\n\n
So essentially what we did is we expanded the capacity to assess the ceiling and expanded the capacity to produce those seedlings and expanded the capacity for farmers to receive those things optimally.<\/p>\n\n\n\n
Right. But you just on that point, this is this is pretty fascinating because I’m trying to work out in my head almost reverse engineer what you’re saying a little bit, so. How did you at the beginning of this, you mentioned you use markets, so you’re using the spectrum analysis to pick up markets and and actually a markers piece of data that somehow presents itself. Right. Let’s put that into the very Barney style language that I can understand. So it’s information that has exposed itself in some way that your tool can identify, right?<\/p>\n\n\n\n
Correct. And presumably it’s information on the surface. It’s not doing any kind of X-ray or anything economic crisis. On the surface.<\/p>\n\n\n\n
It does penetrate a couple of millimetres inside the the tree and and the same for the beans. It does have some penetration capacity.<\/p>\n\n\n\n
OK, so so there’s this analysis that takes place around the surface and just below the surface of the the thing that you’re analysing. And it identifies traits, character traits that exposed themselves that you are able to pick up. But in order to be able to pick them up, you’ve got to know what you’re looking for. And so this goes back to a question I had, which is like, how do you know what to look for? Did you hire an expert?<\/p>\n\n\n\n
But in my experience, a lot of those experts, they can’t explain how they know something. They say it’s more art than science that I just know I can look at a plant, I can look at a thing, and I’ll know that it’s how did you how did you turn all of that, all of that anecdotal data. But that’s subjective information into sort of hard empirical so that numbers based things that you could then make into an algorithm that that you can identify.<\/p>\n\n\n\n
That’s that’s a that’s a great question. So typically, maths doesn’t lie, right. So at the end of the day, that’s what happens. So we we look at the data and we correlated with the expert judgement and we see that our sensor analysis is exactly correlated with the expert judgement. And essentially, that’s what the A.I. does, right. The A.I. is not smarter than humans in the sense of conceptual smarts. It’s smarter than humans with with respect to repetition.<\/p>\n\n\n\n
Right. So so that’s that’s that’s a boiling it down to very Barney terms, like you said, is, is we’re able to to codify that experience or that sort of what you could say is subjective experience. But we’re able to codify it with data, with with actual data. So it’s amazing because going back to the to the to our other piece of the business. Right. Which is on the green coffee, once you see the data, you can tell and we’ve had this conversation with our clients, as you can tell them, this cupper is a little bit off with respect to the other cuppers, because it’s it becomes evident, right.<\/p>\n\n\n\n
Once you see the spectral fingerprint and you see that it’s not you see that they they record different things and the spectral fingerprints are the same. It’s chemistry. Right. So you’re saying it has to be the same? It’s impossible to to say that it’s different. And in fact, that’s that’s that’s part of what we’ve seen that once you put very, very let’s put it this way, it’s it’s it’s it’s completely standardised data. Right. That’s its objective.<\/p>\n\n\n\n
So you’re able to to say that says those. Right.<\/p>\n\n\n\n
And is that data part of your job identifying. So you’ve got now to let’s call it a special black book full of such a database or something. But you got that black book of of of markers and information and data that that says when you see this, it means this. And when these things combined means that. Is that part of your intellectual property or is that information that’s open to the community?<\/p>\n\n\n\n
Correct. So it is it is part of our intellectual property. But then in some senses, what we’re doing is and it’s also shared intellectual property in the sense that it’s something that is sometimes belongs to our customers. Right. So. Right. Of course. So because we’re codifying. If you will, the recipe of our customer, we hold that dear, right, then we go hold that dear for them because it’s just putting whatever they had codified in their sort of collective knowledge and sort of their collective cupping and the way they they buy and sort of mix and blend the coffee.<\/p>\n\n\n\n
We we codify that and sort of we keep that as a secret as well. But the way we do it is evidently our intellectual property.<\/p>\n\n\n\n
Fantastic. Now, I’ve got a question that is threatening to be a very, very dumb question, but I’m going to be very bold and ask it anyway on the basis that it might turn out to be a smart question, which is so the way Nespresso systems work is you have a bar code on the top and you put it in and it reads the bar code and decides what to do with that coffee. Is any part of your recipe, is it able to inform Nespresso as to how it should not just not just choose which beans are the right ones to to to to to use and and obviously through the whole farming process?<\/p>\n\n\n\n
Can it go a step further into actually how how it how it brews the cup?<\/p>\n\n\n\n
And. Eventually, maybe, yes.<\/p>\n\n\n\n
OK. It wasn’t a stupid question.<\/p>\n\n\n\n
No, it isn’t. It isn’t. So let me let me let me answer it on a different way of what it can do and then we’ll go to that question if it if it eventually could do that. So what what it can do and it’s a it’s a lot of the things that we’re working with them to be able to do is so today, despite the fact that Nespresso is a is a is a vertically integrated company, they have no visibility on quality.<\/p>\n\n\n\n
Right. Because the only time they would have visibility on the quality available is when actually somebody cups it and tells them, OK, I have a batch of whatever coffee ready for you because it matches what you’re looking for.<\/p>\n\n\n\n
Right, I think I understand what you’re saying, because you mentioned earlier that they work with farmers like they’ve got they’ve got a very tightly integrated supply chain. They don’t go out and buy in the open market and cup and then say, we’ll have some of those. They’ve got what they own already, which is part of that farm, said they. Yeah, you’re right. So they’ve got that. I suppose in some respects it’s a it’s a strength, but it’s also potentially a problem as well.<\/p>\n\n\n\n
Yeah. So but the problem is it’s a strength, but it’s analog right. It’s not digital. So they do not know how much coffee they’re going to have available to make that special sort of pod up until they receive it. Right. Or relatively late in the game. Right. And so this technology, because it’s all cloud connected, will give Nespresso the ability to understand and predict, OK, it’s going to we’re going to have more of this or less of this or whatever of this, OK?<\/p>\n\n\n\n
That’s one aspect. Right. Which is the visibility aspect and the other aspect, which is more forward looking. And I think we discussed this in our earlier talk five months ago. Is that. When you start being able to measure quality, you can go back and define what are the characteristics or rather the processes that produce that quality. Right. And so one of them sort of very on the side is, OK, you need to have a special variety of coffee that’s the grafting.<\/p>\n\n\n\n
Right. And you need to have you need to pick the beans at the optimal harvest time. So they need to be exactly at the same sort of ripeness, if you will. This technology helps to do that as well. Same technology and you need to ferment the coffee with a very specific, specific recipe. And you need to be able to manage that recipe so that you know exactly when it’s done right. Like when you stick a thermometer up, up, a turkey’s behind and you understand exactly when it’s done.<\/p>\n\n\n\n
It’s the same thing. But today, those tools are unavailable, unavailable to the farmer. It’s only intuition. So a lot of high quality coffee gets lost in the process there. So what we’re doing is de bottlenecking those things with data, with true data to understanding of what they’re looking for. So what you don’t measure, you don’t manage. So we’re starting to measure it and now we’re starting to manage and that that’s the revolution. Now back to your question.<\/p>\n\n\n\n
So eventually you will be able to have that data to tell you, OK, the best way to mix or the best way to do this or the best way that consumers will will accept this flavours are this because that data is going to be able to speak in those aspects today. It’s completely you’re blind, you’re completely analogue. It’s just intuition. Right. Like you said, it’s it’s the experience. But we will be able to codify that.<\/p>\n\n\n\n
Understand, I remember when we spoke that there was a something it really stood out to me and I’m pretty sure we highlighted this in the story was he said he said a farmer might one year produce a like a world class coffee, but he won’t know how. Correct. He won’t know what he did. He won’t be able to go and replicate it. And so what you’re doing is, is your, as you say, codifying it. But you’re also you’re putting numbers against it.<\/p>\n\n\n\n
So you can say here’s what you did and therefore here’s how you can replicate it and maybe you can identify again, it’s call the markers within the data to say this was the best coffee ever produced. He still did some things wrong. Don’t do everything the same way. Maybe these things change these things. But these things were definitely what contributed towards the towards the the the the the great result now with Nespresso. Mm hmm. Where are you in that journey and has that changed at all?<\/p>\n\n\n\n
Because because that would mean that you’ve got to go at least a year or two in before you can start to analyse its results.<\/p>\n\n\n\n
You’re right. You’re absolutely right. So we’re we’re in the beginning of the beginning. And so it is a Genesis chapter one, if you will, capturing the data. Right. That’s that’s the that’s the big that’s our big input. It’s getting all the sources of data and building that huge data lake and database that you were talking about where that allows us to to build all the schools sort of models and predictors. And now that being said, in that process, what’s what’s perfect is the enemy, what’s good.<\/p>\n\n\n\n
Sometimes when you see the data, you see that you’re starting to solve issues immediately because you’re you’re you’re starting from a very low base. So you don’t need to be 100 percent precise to start doing applications that actually start working. Right. Right. So so that’s where we are. So we believe that there are applications that are going to be starting to be used by farmers relatively soon, let’s say, as early as late this year. And a but the brunt of the work is probably going to be sort of by mid next year.<\/p>\n\n\n\n
So it’s it’s a it is a it is. It’s gigantic challenge to to sort of try to get data that was never there. It wasn’t created. We need to create it from scratch.<\/p>\n\n\n\n
Yeah. So it’s a journey and you’re at the start and they’re aware of that. But the boy, the dividends a couple of years down the road, you know<\/p>\n\n\n\n
It is it is, it is it is exciting because and I can tell you from from the experience of actually walking the farms. Right. Small farms in Colombia. And you show them the. Technology and they feel like they’re in a sci fi movie, right? They’re literally coming out of the Dark Ages in which basically they were doing this completely intuitive and they’re sort of being thrust into the 22nd century.<\/p>\n\n\n\n
Right.<\/p>\n\n\n\n
It’s you know you know, I did the same by Arthur C. Clarke. And I don’t know if you know who our C Clark was. You know, I’m a sci fi writer. And he he wrote something along the lines of and I get this very bad. This is quite bad, but it’s it’s very pertinent and applicable here. He said science, when sufficiently sophisticated, cannot be differentiated from magic. Correct. So, yeah, it is magic to them and probably to me too, to be honest.<\/p>\n\n\n\n
All right, correct, obviously, once you understand what’s behind and everything like that, people people need to understand that for it to use it. But it’s the level of of excitement. This is amazing because, like I said, it’s the difference between knowing and not knowing if they were completely orphaned from technology, you know. And so so it is it is exciting. It’s exciting times.<\/p>\n\n\n\n
How much do you think this is going to impact the farmers? So, I mean, Nespresso does really great. They make a few more million. I’m sure they’ll love me for saying it, but another zero on their bank account. But but but how how can this help the farmers now actually talking within the Nespresso deal? So within the Nespresso deal, they say<\/p>\n\n\n\n
this is this is actually good for everybody. Right, because a. They will keep bottlenecking the production capacity for high quality cost.<\/p>\n\n\n\n
High quality coffee gets paid at a significant premium. Let’s say it’s even 30, sometimes 40 percent. Mm hmm. So for the farmers, it’s the difference between sort of barely making a living, living and making a really good living. Right. So this is actually very revolutionary for the farmers. It’s probably it’s good for Nespresso as well, because they will have higher quality coffee to be able to sell. But it’s it’s it is probably the most the most benefited player in the value chain.<\/p>\n\n\n\n
They’re going to be farmers and the farmers aren’t cut out of the deal in the Nespresso deal. They are. And they’re not in some way sort of excluded from the additional value that’s brought.<\/p>\n\n\n\n
No, no, no, no. That’s that’s part of what what Nespresso has done very well, that they do it today. Right. So this is not something that we did. Right. Right. It’s already done right that Intergration Nespresso did it because not only they want to have access to that high quality coffee, but they want to be sure that the the farmer gets that additional value that they’re actually paying for. So so so the industry, the industry in general and I have been been, pleasantly surprised that the industry understands that the solutions like us are important for that, for the whole industry and for the health of the whole industry, because despite the fact that today, for example, prices of coffee are are high.<\/p>\n\n\n\n
Right. It’s part of the sort of climate cycles and whatever sort of long term people are worried about the sustainability of the industry. Right. Worried because there needs to be a generational change. How can you get young people to get excited back to to go to the farm? Right. So you need to give them these tools, technology, all the stuff for them to get excited. So the industry is is is really concerned about this. And they see these solutions where we’re actually putting additional money, fair money and good money into the hands of farmers.<\/p>\n\n\n\n
Not only hand out money is are very good and they’re good for the for the health of the industry.<\/p>\n\n\n\n
I agree. It’s something that I’ve talked about, what we talk about regularly Bartalks. But it is something I’m personally concerned about. And I mean, most people it’s the boiling the frog syndrome. You know, Felipe, where where we are right now, we are the frog in the water and the temperature is going up and up and we’re not really noticing. But the fact of the matter is, you look a little bit further ahead and you see real challenges for the industry.<\/p>\n\n\n\n
Now, I’ve just opened up a lovely bag of coffee this morning from a friend of mine who roasts just down the road. And he always makes amazing coffee. And and I look to see where he’s buying his coffee from. This particular one is a blend from different areas. And I literally look at that coffee and I think to myself, I wonder how long I’ll be able to enjoy this or when this will become such a luxury that I won’t be able to make it my daily cup.<\/p>\n\n\n\n
It’ll be something I have once a week or whatever else. And it does worry me. And I’m not a paranoid person, but I’m just looking at the facts on the ground and they don’t lie. So if you want to talk about numbers, I wish somebody would crunch the numbers on. And I know they’ve done it on individual basis about age of average, age of farmers and the attrition rates. And, you know, the you know, obviously all the climate change issues that we’re facing, obviously Brazil’s problems at the moment.<\/p>\n\n\n\n
But in a world like shrug it off until it becomes until it comes to a point where we can’t buy our favourite coffee anymore and then we’ll worry. We’ll wonder how we got here. So, you know, our job as champions in the industry, I like to include myself as a champion, like you Felipe because really you’re doing all the hard work. But I’m going to associate myself with you, not one of the things<\/p>\n\n\n\n
you’re absolutely welcome to, to be a champion.<\/p>\n\n\n\n
Show you what I what we need to do is we need to save the industry and before the crisis hits. So I think this is I think this is a fantastic initiative, I have to say. And a lot of businesses start up. I’ve started up businesses. It’s hard. You know, I know you’ve done a few successful ones and you’ve got that probably that golden Midas touch. But nevertheless, I bet it’s still a lot of hard work. And the fact that at this stage in your business, you’ve done a great deal like this with a company, with a company like Nespresso, which I know does take sustainability seriously and puts a lot of walk behind the talk, I think that’s a really fantastic step forward.<\/p>\n\n\n\n
So now I want to ask you a couple of difficult questions for sure. So what? Ease it in with a teaspoon of sugar, what was what in this whole process going from where we were five months ago to to today, what was easier than you thought and what was a lot harder? What did you what did you fail at or struggle at? And what was more significantly harder than you thought?<\/p>\n\n\n\n
Yeah. Er, nothing was easier for. So the only thing easier is to answer that question because<\/p>\n\n\n\n
Let’s move to the hard part.<\/p>\n\n\n\n
So, no, but look, in one of the luxuries that we’ve had and then joking aside, is that. And once we were able to announce that this worked right and there is much more interest than capacity for us to handle the increase in capacity to work with all the people that want to work with us. OK, that’s that’s that’s a that’s a good luxury to have, but it’s a problem. It’s a problem, so our issue today is that we cannot work with everybody we want to work.<\/p>\n\n\n\n
Right. And that’s and obviously we’re trying to solve that. We’re raising capital. We’re doing whatever we need. We’re ramping up. But that’s it’s a frustration. But it’s a it’s a problem anyway. And it’s a good problem, but it’s a problem anyway. And so let’s say that the commercial part, which is I’m not saying it’s it’s it’s easy by any means. It has been er much easier than we had anticipated. OK, so we’re able to talk to the likes of the Nespresso’s of the world, which I don’t know, six months ago, we wouldn’t have dreamed about it.<\/p>\n\n\n\n
OK, so that is awesome. Now, the what is very difficult is sort of the typical growing pains of a small company is we’ve already proven that we can do this, but we are already proven that we can do it sort of in a in a very controlled lab setting where we sort of control everything, where we do everything right. So now the big challenge is how do we scale it up? Right. How do we make this instead of depending on people and knowledge, on processes and automation and stuff like that?<\/p>\n\n\n\n
So that is that is the big challenge. And it’s it’s hard work. It’s a lot of work. It’s a it’s a moving target. Never ends right there. But but that also makes it interesting. Right? It’s something that is really cool. And like I said before, the other thing is that this is a it’s it’s it’s a pathway of actually we need to be able to be very efficient of how to manage data. That’s that’s that’s the core of what we do.<\/p>\n\n\n\n
And and and that is that is always a challenge. That’s always a challenge. It’s it’s it’s it’s difficult. We’re managing a team that is multinational. We have people in Colombia, Brazil, Europe in a very short time frame. So all of them are growing pains. So I won’t I won’t whine more about it because it’s these are good problems to have.<\/p>\n\n\n\n
Absolutely fantastic. So the final we’re coming to the end of our session. The final question I want to ask, of course, is a question you always need to the end of the interviews, which is where next. You’ve mentioned the growing. You mentioned the scalability. And I’m going to take that for granted. As you know, that’s the hardest part of growing. The business is scaling. And it’s and it’s actually one of the most dangerous parts as well for it for for some people.<\/p>\n\n\n\n
Because, you know, they they if it’s the first time you’ve done it, if you’ve scaled a business and I know you’ve done this before, but for those people that have never scaled a business before, it’s where they often find the most difficulties. They they underestimate cashflow and whatever else you want to focus more on the technology side. When we spoke before, you mentioned that the potential application for cocoa in the future, et cetera, et cetera.<\/p>\n\n\n\n
But of course, all of that, it depends on your bandwidth, on your ability to deal with things. And, you know, sometimes something comes in from that. You weren’t expecting like some huge Nespresso deal. And, you know, cocoa gets put on the back burner until we get that done. And that might be three years and whatever else. But where in your mind, with the information you’ve got now in terms of the company strategy, where do you where do you see this going next?<\/p>\n\n\n\n
No, cocoa is definitely in in our back of our heads. Right. So what we’re want to do is buy more bandwidth at this point in time. That’s what we’re looking for. But it gets more money and get more bandwidth. And being able to do that, because the advantage is that the coffee world, there’s a lot of overlap. In fact, in coverage, you cover cocoa as well. Right? Right. So there is there’s so much overlap with respect to industry structure, all the kinds of stuff and the type of problems.<\/p>\n\n\n\n
But the players are the same. And some of the players are telling us already, OK, let’s start to talk about cocoa. Let’s start working. And we have to say to them, wait, wait, wait, I do not have the bandwidth. I need to ramp up the bandwidth to be able to do that. So cocoa definitely. Right. That is that is an area that we we really want to push the more we take, which we haven’t dug as deep as in coffee.<\/p>\n\n\n\n
But very knowledgeable people in the industry have told us that this could be even potentially more revolutionary in coca because the base is lower and. At the end of the day, the industry, the coffee industry already has a standard, they’re working with that. There is some organisation already to that in cocoa is a little bit further back. It is true. So so cocoa definitely from from with respect to to to sort of where we want to take that technology.<\/p>\n\n\n\n
And it probably is a combination not only of the near Infra-Red, but on the on the computer vision, because as you as you know, a lot of the other quality characteristics of cocoa today are done, are visual. Right. Is you do the guillotine analysis and you analyse sort of the colours of the bean. Right. That that that we can do that we can do in fact, we’re doing something with that technology for the coffee industry. You may well know that the first thing that somebody that buys coffee, what they do is granulometry analysis, right the size of the beans.<\/p>\n\n\n\n
And they also count the physical defects that you can see, right?<\/p>\n\n\n\n
That’s right. That’s the SCA rules for for grading the beans. Right?<\/p>\n\n\n\n
Correct. And all that thing you could do with a picture. Right. And so that is one of the applications that we have in line to come up. So that same technology and that’s a principle. We could take it also to cocoa for the guillotine analysis. And it’s right. So and so. Cocoa. Absolutely. Yes. Now, the other things that happen is once once you do such a deep dive that we’ve done in the coffee industry, we find a lot of problems that we can solve with our technology.<\/p>\n\n\n\n
Right. And we were discussing some going back into what are the inputs to produce the better quality. Right. Understand, for example, what is the correlation between fertilisation and quality? We don’t know today. We know if we’re fertilised, we get more coffee, but we do not know if we get better coffee. Right, or we don’t know what we need to do from a fertilisation point of view to get better coffee. And so those are questions that we want to answer, right?<\/p>\n\n\n\n
We want to help answer that.<\/p>\n\n\n\n
You know, just very much on that point that I remember editing a story was only a few weeks ago, I think it was in Colombia where they did a study on bees and the role of bees in not so much in pollination because, of course, it’s self pollinating, but just the role of bees, which was thought to be, well, you know, bees are involved in pollination coffee plants to pollinate. So Arabica does. So it’s it’s not a you know, it’s not important.<\/p>\n\n\n\n
But they actually found that the quality of the beans was and are the yields where higher where bees have been involved. I don’t know why. You know, so there’s so much that we’re still learning.<\/p>\n\n\n\n
Yeah, that’s exactly right. So it is that is an example, right. The other example is the helping farmers make decisions on when to harvest right how to fertilise, when to fertilise, making a helping the farmers make decisions on on on planting. Right. Right. This this this variety versus this variety. That’s what we’re that’s what we’re starting to so. At the end of the day, all this power of information, of data, we need to harness it to to help to improve those decisions that today are very, very and like we said, artisanal, intuitive and stuff like that.<\/p>\n\n\n\n
So those are the two directions, right. Sort of a new industry and back in the industry. Right. Sort of deep dives into sort of using this data to be able to do it. And obviously or horizontally, we want to do other regions. Right. So right now, we’re doing Colombia and Brazil, Southeast Asia. Vietnam is next. Robusta is next. And whatever we do next, though, there’s a we have a lot of work.<\/p>\n\n\n\n
Right. So we needed to do to buy one piece at a time. But it’s it’s exciting.<\/p>\n\n\n\n
Well, talking about exciting to end it there, because I always come away energised and excited from from talking with you. Felipe, it it really does inspire me. And I love talking with entrepreneurs and I love talking geeky about science and learning stuff. So, you know, this call has been a real joy. As always. You’ve got to promise to come back no matter how big you get and how successful you are. You you’ve got to come back on the show and talk to us about it at the next stage of your development.<\/p>\n\n\n\n
We will. Thank you very much. It’s always a pleasure to talk to you. And hopefully it’s it’s it’s the second of many more to come.<\/p>\n\n\n\n
Fantastic. Great.<\/p>\n\n\n\n
Thanks, Phillipe. Thank you.<\/p>\n","protected":false},"excerpt":{"rendered":"
We have a discussion with Felipe Ayerbe, the CEO of Demetria on his innovative Agtech solution and the recent deal with Nespresso. We ask him about progress at the company, how Nespresso is using the technology and what this means for their farmers. Full Interview Transcript Nick Baskett So we’re here with Felipe Ayerbe, who’s […]<\/p>\n","protected":false},"author":10,"featured_media":21980,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"footnotes":""},"categories":[3],"tags":[],"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/posts\/21979"}],"collection":[{"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/users\/10"}],"replies":[{"embeddable":true,"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/comments?post=21979"}],"version-history":[{"count":0,"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/posts\/21979\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/media\/21980"}],"wp:attachment":[{"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/media?parent=21979"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/categories?post=21979"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bartalks.net\/wp-json\/wp\/v2\/tags?post=21979"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}