S1E3: Tokenising Social & Climate Impact with Kevin Pettit from Proof of Impact

Meet Proof of Impact who are using Blockchain, complex algorithms and a Micro Services approach to verify environmental, social and health impact at a granular, unit level. Kevin discusses the unique process of digitally verifying impact projects, unitising and creating impact securitisation models, and creating customised portfolios for enterprises. A fascinating and scalable approach to driving social and climate impact.

In this episode we discuss:

- How securitisation (the financial mechanism behind mortgages) can be applied to social impact projects

- Defining what is a 'unit' of impact, the required digital verification models, and creating immutable proofs

- Dynamic impact 'pricing' based on differing levels of verification

- Using the Ethereum blockchain for tokenisation, and which is the best protocol for tokenising a Rhino

- How to scale a global Blockchain impact platform 

- Proof of Impact's involvement in the COVID19 response, and a call for support

You can find more about Proof of Impact here: https://proofofimpact.com/

Proof of Impact Twitter: @proofofimpact

And Kevin's LinkedIn profile: https://www.linkedin.com/in/kevindeanpettit/

Transcript (Courtesy of Sonix - Apologies for any errors from the AI):



Anthony: Welcome back, everybody. As you may know, climate and social impact are important topics for me, and I believe exponential technologies can help us to drive exponential change. And with that in mind, I'd love to introduce Kevin Pettit from Proof of Impact. He's the C.O.O. there, the chief operating officer, and they're looking at using blockchain and other technologies to accelerate engagement in social and climate impacts activity. Kevin, welcome to the show.

Kevin: Hey, Anthony. Thanks for having me.

Anthony: Really excited to have you here. As soon as we talked the other week, I really enjoyed the work that you were doing, the examples that you talked me through, some of the projects you're working on. And I really would love to share some more of those stories with the audience. Let's start off simple. Tell us a little bit about Proof of Impact. What do you guys do?

Kevin: I work for a startup called Proof of Impact. So we're a technology company that uses a series of exponential technologies, including blockchain, to support environmental, social and health impact globally.

Anthony: And Kevin, tell us more about the people you're working with. What problems are you looking to solve with Proof of Impact?

Kevin: So our goal at present fact is to radically redefine what is impact. And so we're trying to basically find ways to help people fund and experience impact an entirely different way. And we define impact as social, environmental or health good. And that's measurable. And we see that one of the biggest problems is that there's this massive inefficiency between the people on the ground who are doing the most good and the people who are looking to fund impact. So we primarily work with companies everywhere, from startups to fortune five hundreds who are looking to make a meaningful difference. And we want to connect them with these amazing projects that are on the ground who are making an impact every day. So the biggest things is that we're seeing is that there is a missing link between funding to the impact at a unit level. So we're trying to guarantee these measurable outputs so that people know what is it that I am participating in and really bring a lot of that transparency. We verify impact. So that means that we want you to be able to have access to this granular level data that supports and showcases what is the good that's being done on the ground. And ultimately, you know, the purpose of that data is really just to bring this rich and humanized experience. Right. If you look at the impact market, you could call it, which is inclusive of donations, is inclusive of impact investments. I think one of the biggest problems or two of the biggest problems are there's a lack of trust and there's a lack of engagement. And when you talk about trust and engagement, the core experience now is, you know, very top. You fund money into a black box. You're not really sure where it goes. And we're using blockchain, and a lot of different types of exponential technologies so that we can bring that data from the ground to life and really bring a rich and more human and engaging experience.

Anthony: And so the payment that you saw was a big part of that, so was the proof, the verification of the activity happening on the ground.

Kevin: Absolutely. So you think about just the funding cycle, right? There are people who are delivering impact every day and they're doing, you wouldn't believe, we're working with projects and programs globally that are doing the most amazing things. And they are the experts of what is the best interventions and what is the good that can be done. So the question is, how do we verify that they're doing those things and incentivize them to do more of it? Right. And that's kind of this idea of performance based finance, sending money to the activities that we know are the most effective and that are doing the most good.

Anthony: Fantastic. And obviously the technology plays a large part in that. How did you get from the original problem statements to some of the technology that you've designed and implemented now?

Kevin: Sure. So I think it's really important to just think about the problem. Right. And the problem is that most of these programs and the way the impact is being implemented now and its inefficiencies.

So if you think about the way that capital flows to impact either projects or programs or nonprofits or social enterprises, it's being distributed really in a top down nature. So there's some sort of funding cycle. There are nonprofits who have to apply for grants to apply for funds or go on fundraising.

And that's essentially taking people away from the core activities, which is making an impact. So we try to go the exact opposite. We go bottom up. We say, OK, if I can prove impact at the granular unit level, then I can then allocate funds to the unit level a lot more effectively. And then we'll know that the people who are on the ground, who are highly effective, they'll have an avenue where they can say, if I can deliver more impact, I can deliver more funding. And that's basically how we started going from this bottom up. Let's gather the data on the ground approach.

Anthony: Very good. Tell us more about how you found yourself working with Proof of Impact and the work that you do today.

Kevin: Great. So I've been an avid blockchain enthusiast since not since the earliest days, but it's been a while. So I've been into blockchain since. 2016 before Proof of Impact. I helped launch and scale a multiple currency, multiple blockchain. Cryptocurrency wallet. So that's really how I got deeply involved with blockchain that was on both Android and iOS. But we also came out with these B2B blockchain APIs. So I've kind of worked with amazing groups on a lot of different chains. But before that I actually spent most of my career in financial engineering and securitization and large scale portfolio management. So I've seen firsthand a lot of the inefficiencies that blockchain can solve in financial and other applications. And I stress other applications because a lot of people think about financial applications in terms of blockchain, but there are definitely a lot of others. So in addition to that, I've also been super passionate about social impact for a long time. So when I was in finance, I helped structure, you know, unique financial instruments that supported affordable housing, for example. And then, you know, one of the core parts of the blockchain company, which was called Ethos, was really I was really interested in building into the vision, the idea of self custody and ownership of your own finances and banking the unbanked. So really, through that journey where I had this background in securitization and finance, I had this background in blockchain. My primary goal was, how can I combine these two things together to try to make a lasting social or environmental or health impact?

Anthony: That's brilliant. I can relate from my perspective of being able to try and do both. Working with the technologies you're interested in working with and also in the domains that you love and being able to create an impact at the same time feels like you've really found a sweet spot. Tell us more about then the learnings that you then took from working in blockchain and finance into working with Proof of Impact. How does blockchain fit into your story today?

Kevin: I think of it kind of like an impact securitization model. Securitization is one of the most effective avenues for allocating capital. I mean, trillions of dollars are securitized every day in the form of mortgages. And it's an interesting thing to compare to say, you know, a lot of people in the impact industry impacts face. You know, you think of water, some different interventions. Right. Water delivery to a village in Kenya or a vaccination that was delivered to a child in Ethiopia or a solar panel was installed, a nurse that's going through the crisis gets delivered a meal like what is that impact unit? Right. Well, all of those different types of units of impact, they seem very different. But if you look at the securitization market, all of the houses that are in the US, for example, are totally different. They're in different school districts, they're different sizes, they're different shapes. So although they seem very different, they're actually, from a data perspective, can be structured very similarly. And that's kind of the thought process or the seed for me that really got planted on how you can allocate more capital to things like impact. So what we do there is we say, OK, now that we have data about all these different types of things, how do we structure it in a way that it looks similar? So if you're trying to prove that a vaccination did in fact occur, there's really only a limited, finite set of data points that could be gathered about in this case of vaccination.

Was there a picture taken? Is there a timestamp? Is there a geotag, like, you know, geospatial data of where it happened that could be grabbed from a mobile device? Is there a notes from a nurse that confirmed that it happened and all of these different data points can be structured in a finite way that that then you can prove that the impact occurred and then put it into more and more interesting structures like a donation product, so that if you wanted to donate to a vaccination, you know that you're going to donate specifically to that individual vaccination or to a fund. Right. If you wanted to donate to a bunch of different interventions, as you say, child health ‘basket’, for example, which is one of the things we're doing now in Ethiopia. So it could be child nutrition, it could be outpatient visits, it could be vaccinations all together. You can structure them into a basket so that people could donate directly to that or the broader vision which is bringing it to impact investment products. So once you get this impact in a digital form, you can then kind of form more complex products like impact bonds and impact funds and things like that. So I was focused on how we can bring these similarities were in something that seems very different. How do we actually structured it in a way that it can be very similar and then that can create a lot of efficiency where right now there's currently a lot of inefficiency.

Anthony: And I'm just curious, is there a degree then of valuation or quantification of those particular units of impact? Do you look at the relative carbon offsetting that created or at worst case, the value of a life or preservation of a life? How do you go about creating those units?

Kevin: You know, we have this impact design process where when we're trying to approach any problem, we're saying, OK, what is the unit of impact that we want to promote, or we want to incentivize and in this case, let's just say it's a solar panel that was successfully installed. So we just need to determine what is that unit of impact? One solar panel was installed. How do we know that it actually was installed? Right. And that could be a series of data that says there was an installation date. There was a picture from the install. We know how many people were in the house. All this different data that says that it was actually, in fact, installed, was it unique? That's an important one. Is there a unique serial number? Do we have a unique timestamp and geotag? And once you have these pieces of information, this is really where the blockchain comes in, because we want to then stamp all that data to be immutable, to say yes. This unit of impact did occur. And that's where in our case we use the theory, and with blockchain we can mint this data onto either in an ERC20 token or an ERC721 token, which is basically different types of tokenization is that we can do to memorialize that this impact actually occurred. And then now that that unit of impact becomes transactive all and that's kind of where blockchain fits into all this.

Anthony: I'd love to double click for a second on that transactional nature because it sounds like a big part of this is you're creating the immutability or the verified activity on the ground, that something has definitely happened. But is there is there a security here as well? Are you looking to use it, the theory and tokens for funding or is it just for a verification purpose?

Kevin: That is a great question and it's a really important distinction, which is what specifically are we using blockchain for? We are not using blockchain at this stage for a transfer of value.

We're using it to make immutability of impact data. Right. So one of the internal debates, as we know, as a lot of people who are who've gone through blockchain projects, have to go through this journey in their own initiatives. What is the level of decentralization do you want to use?

What features of the blockchain? Because there are many that that are the most important for the business case. Right. So, for example, we had to decide as enthusiast of blockchain and decentralization, we have to decide at what points are appropriate to become more and more decentralized. So if we're trying to funnel capital most effectively to the most good early in our process, we realized that using blockchain as a transfer of value was not the initial best path for the use of blockchain, because there's still a need for more widespread adoption of cryptocurrencies and the ability to have stable coins and access. And there's gonna be a lot of impact funding either coming from the donors themselves who haven't adopted, you know, cryptocurrencies or from the impact creators themselves who are on the ground, who haven't adopted cryptocurrencies and can spend them freely. So we decided that in the beginning we're gonna use the blockchain just to track the data and then hopefully move to a more and more decentralized future as we progress in our product.

Anthony: That's really fascinating to hear. And there’s a couple of things in there. Firstly, hearing somebody working on a blockchain program talking about business value is always music to my ears. And it seems like you've spent a lot of time thinking about that. Also, really interesting to hear that the first application of blockchain is around the immutability and around creating the verified action, a utility token in that case, less around being able to receive crypto payments or even being able to open this up as a global platform than anybody can get access to. But that sounds like it's on your roadmap.

Kevin: Absolutely. Absolutely. So if we're going back to the business value, right, one of the biggest inefficiencies is basically how do we securely digitize this impact data?

That's really what this is. And if you have this impact data in a digital form, then you can get creative, right? Then you can create portfolios of impact for people. So one of the things I said in the beginning that we focus on supporting companies who want to make an impact. Well, if you're trying to offset your carbon footprint, what are your options? You could go to the carbon credit markets and the user experience is pretty abysmal. You pay money and you get basically a receipt. Whereas with digitized impact data, we can give a lot more granularity that says with payments and things aside, with his digitized impact data, we can show you on the map, hey, not only do I care about my carbon footprint, I'm not just off gassing some field.

I'm actually supporting these 50 solar panels that are in Kenya. I'm supporting these clean cooking stoves that are in South Africa. And actually, you know what? I actually realized that part of my vision and part of my mission is I really care about getting clean water to people. I can, you know, make sure that we fund leaders of clean water to people in different at risk jurisdictions, for example. So you can build this portfolio that's backed by all this rich data because the impact is now in a digitized form. And then you have to trust that the impacts that I purchase, that unit is mine. And that's kind of one of the key benefits.

Anthony: I love that. And obviously, I spent a little bit of time looking on your Web site and it's great. You can zoom into an example portfolio and then go into one specific project and you can see. Some of the data you can see some of the images, and I think the difference between being able to see a real impacts to real people versus being able to get a receipt for some intangible carbon credit that you have paid for by obligation or by necessity. There's definitely a more humanizing experience to that. I'd love to walk through a specific example just to close the loop on this one. One of my favorite that I saw was the turtles, the baby turtles on one of the beaches. I'd love you to talk us through. How do you digitize the impact of helping baby turtles? How do you design the program? How do you design the digital impacts activities or the digital impact proofs in something like that?

Kevin: Yeah, that's a great that's a great example. That's actually one of my favorites because it's just so fun, lighthearted. And it's just a it's just a great, a great project. So there's a there's a wonderful project called Tortuga Vida. And essentially they have volunteers who patrol the beaches every night and they look for turtle nests. And you would be amazed at how much information that they are already trying to track about their activities. So what does it mean to say the turtle? Right. We have to define that through data. So it means that so and so volunteers went out that night and travelled X number of miles. It means that they went patrolled the beach and they found a nest and they uncovered the nest safely and they counted every single one of the eggs. And we can help them track how many eggs that they that they counted. Then once you count the number of eggs, the teams safely dig them up and they tag them and bring them back to what's called an egg sanctuary, turtle sanctuary, where basically they have all of these different turtle nest that were successfully relocated. And as those eggs are being incubated and awaiting hatching, they actually take pictures of all along the way.

So they take a picture when they found the nest. They take a picture when it's at sanctuary. And then as these turtles hatch, they also take pictures and videos of the release. And so you can see pictures and videos of the turtle releases if you purchase a turtle on our platform. But the key here is that if I'm a donor and I say, wow, I really want support, turtles, almost all sea turtles are endangered. And that's something that I'm very passionate about. Then you could go onto the platform, you can purchase one turtle. And this is a turtle that was successfully released into the ocean. So one of the data points is maybe there were 70 eggs in the nest, but only 50 actually hatched and made it into the water. You would only be purchasing one of the 50, specifically one of the 50 from that batch that actually successfully made it to the ocean. And now you are participating in a very specific unit of impact that you can feel proud that you supported that that one turtle.

Anthony: Fantastic. And I want to be clear, just in case the SEC is listening, we are not using a Ethereum to purchase turtles. We are supporting the impacts. This is not a taxable benefit.

Kevin: Exactly. Exactly. And I think the interesting thing, it just comes from that bottom up nature is really the verification of it, because when you verify it, what we can do is we can basically say now that we have this large amount of data, we can do a series of checks and algorithmic verification that basically does a series of checks. That's like did the picture did the timestamp that we pulled from the picture matched the timestamp of of when they said that they went out, did the geotag that they set said that they were at match the geotag that we pulled from the metadata, the picture. Right. We have hundreds these different checks for all the different types of impacts, units that we track. And when you have these really small like data checks by a high number of them, then you can basically build a level of confidence that, yes, this impact did, in fact occur and more importantly, this visibility of our methodology. And so that you can see the data for yourself. You have the ability to rate the risk and evaluate the risk for yourself. So you can look at the methodology, you can look at the proof points and you can say, hey, I don't feel confident that this turtle actually hatched. I don't want to do that. But I do feel confident that this solar panel was installed because it has the X, Y and Z, the other data. And it just gives people a level of visibility and and a way to to measure how and if they want to participate in different programs.

Anthony: And so a big part of your proposition is the verification, the the ability to confirm that, you know, one picture of a turtle is different to another. And I guess there's a number of different technologies at work there.

Kevin: Absolutely. Absolutely. So, you know, one of the reasons why I'm so excited about, you know, just personally excited about, you know, my work with privacy impact is that we're a horizontal business.

So we're trying to track impact and transact it end to end. And in order to do that, we actually have to employ a number of different exponential technologies to be able to gather data, verify it. Productize it, our package it and then distribute it out, right? So that's kind of our lifecycle. So if you think about the technologies on the data input side, you think IOT, which is really important because, you know, you can get machine based generate or cherry machine generated data that can have a level of confidence that it wasn't tampered with. You can get mobile data. So picture and geospatial data coming from pictures and mobile devices and mobile devices are becoming super prevalent and available even in some of the most remote locations. Moving to the verification side, right. We can turn these algorithms and use machine learning and AI techniques once we get critical mass of data to actually help determine what are these confidence scores, whether or not they've been verified. We can then once you have this data that's verified, we can then make it immutable on a token. So that's the use of the blockchain and that makes that data easily. Transactive. All right. And once you have blockchain, that's easily transactive all in these form of these tokens, you can then structure it into a fund or a donation or an impact investment product. And we're a cloud first type of microservice architecture, a way to make a scalable system to be able to handle these transactions at a granular level very quickly. So I get very excited about this because we get to touch so many different cutting edge technologies. And our job really is just how to weave them in at the most appropriate time to create the best business value for the people who want to make an impact.

Anthony: I'm glad you talked about the kind of the movement beyond timestamping, because a good friend of mine, one of his favorite face palm moments is when people just use blockchain from a time stamping perspective, saying I've created an immutable thing. But actually what you're saying there is the portfolio with the securitization, the portfolio creation. That is what makes this really interesting above and beyond the immutability. So you've gone to a number of different levels of capability. I also really enjoyed the points around scalability of this. I suspect at the moment you're doing a lot of manual curation of these particular programs, of the impact programs that you support and helping to create the data, the standards for those things. But I guess over time you'll be able to open those standards or allow others to create programs in your platform using those data or verification standards that your algorithms can pick up.

Kevin: Yeah. Yeah, I think you're totally on it because one of our early decisions was to go broad and wide and a lot of people thought that that could be a risky decision to say, OK, don't you just want to only verify, you know, let's just say solar panel installations or something, you know, very specific things first so that you can nail that really well. But we took kind of a different stance. We said, OK, if we really want to make a robust data model that can scale, let's tackle all of these different types and let's see if we can tease out the models that can work. So whether it be, you know, pulling in from a lot of different data sources, including mobile devices, IOT, all these different things, it actually the funny thing is, is that, you know, we've done this for about 20 projects where we've really ironed out the data models for. And after about the tenth project, you really see a lot of similarities between how you can prove that these different types of impact units actually occurred. And that's when we started getting scale because these models become reusable and they become repurposed all. And I can give you a really good example in the wake of this Corona virus pandemic. So we're able to use a lot of or we're actively using a lot of the different data models to prove impacts for let's just say ocean cleanup is a great example. We can reuse that same data model to help track a meal that's getting delivered to an overworked nurse to help our frontline workers. And that's just one way that because we went wide, we can then repurpose these technologies to to the times. And, you know, social impact areas are things that are, you know, really top of mind and really where that needs help the most.

Anthony: It's timely because obviously I'm sure a lot of the listeners who are picking this up for the first time when they get this may still be quarantined or may still be self isolating. The Corona virus has challenged us in a number of different ways in terms of our working practices or how we get business done or how we continue with business as usual. But I'm really interested. It sounds like you guys have been spending a bit of time thinking about how we can apply exponential technologies to support different communities or to help prevent the spread of Corona virus. Tell me more about what you've been working on.

Kevin: Yeah, absolutely. So as you know, through this crisis, there's been so much widespread worry and panic and there's just these huge market disruptions.

And so I think it's really important and I'm seeing this more and more when you look for it is that people are really trying to come together to solve these problems as a community.

So one of the mentalities that has gained significant traction is the idea of flattening the curve. Right. So like, how do we mitigate or slow this crisis as best as possible? So, you know, our team took a deep think about this concept and like, let's just break it down. What does it actually mean to flatten the curve, and I think that there's like really three things that are at play, right? The most top of mind is how do you reduce the rate of transmission? The second one is, is how do you hold that line? If you remember that there is a dotted line that exemplifies the healthcare capacity. Right. So how do you hold a or boost that line? And then lastly, how do you prepare? Which is one of the things that I don't think gets enough attention is how do you prepare for all the negative actualities or the fallout that's gonna come as a result of this pandemic.

So if you think about those three different ways, you see that there's a lot of areas of social impact that need to happen, that need to occur. And so we just try to break down what is it, the ways that we can be there to support the community as the pandemic unfolds. So we kind of determine these five major risk areas at risk populations. Right. So preventing elderly and sick, elderly and sick who need to use the health care system, health care and frontline workers right everywhere from grocery clerks to emergency medical personnel.

Low income communities, low income communities are at risk for disproportionate negative effects to health care, access to care, education, the hard hit local economies. Everyone sees the markets are kind of going crazy, but this is causing major disruptions to local businesses. And then lastly, you know, everyone's talking about social isolation, really like social health and engagement for individual people, for employees, like employee engagement now that everyone is working from home. These are, you know, major risk areas that we need to try to find a way to funnel capital to the groups or the communities of the people who are trying to support these major risk areas. So with these things that are evolving really rapidly, we just went right into the we went right into the community. We said, hey, who is working on what types of things? And we know that there is most likely, like many crises, there's an astronomical amount of money that's donated or deployed. But how effective are those funds going to be applied? And are they going to get in the hands of the people that are most affected? And that's kind of where Proof of Impact comes in. So in talking with a lot of people, we've kind of reached out to people in our network. People in New York, in Washington, D.C., in Colorado, in Southern California, in Seattle. We've actually identified a few different what we think are highly impactful.

We can create impact events, things that people could fund that could really support these five at risk groups. So some examples that we're working on now is how do we get healthy meals to low income children or how do we provide healthy meals to frontline health workers? This is amazing story where I talked to a nurse and she was saying if there was any way that you could just get a food truck outside of the hospital for our 18 hour shifts like that would be the most, you know, the most helpful thing in the world, because, you know, we're working night and day and we don't have time to make food for ourselves. You know, when you hear those stories in the frontline, right, you want to figure out ways to funnel those meals and get those meals funded so that we can support these people on the ground. And we've already defined, you know, six or seven others, including, you know, hand sanitizer to grocery stores or sending soap to at risk communities. All these different types of impacts that we're using, the models that we've already created to say track ocean trash or track the turtles. And how can we just bring that technology directly to these community groups who are already, you know, on the front lines.

Anthony: And this is happening right now. So you're looking for your support to create projects? You’re trying to create initiatives that can be used today?

Kevin: Oh, absolutely. This is this is happening yesterday and the day before.

I mean, basically, what would happen is we're just accelerating our onboarding process. And because that we have worked out our data model, it makes it very easy for us to say. For example, we made a mobile app for beach cleanup crews to track their trash.

To say, hey, I picked up the trash out of this ocean so that if a corporation really cares about ocean plastic, then in their portfolio, they could, you know, pay to say, you know, I really want to reduce trash as part of my impact portfolio and that we could provide it for them. Well, we just repurpose that out. And that's what we're doing kind of actively right now to see how can we give that app to someone who is a healthy meal provider, who could just give three clicks to say, hey, this is when I made the meal, this is when it got delivered out front of a hospital. And this is when the chief of staff of the hospital picked that meal up so that we can gather the data that proves and we can showcase it and put it on our dashboard to show, hey, people are you know, we are supporting the front line and this is how you can bring that data to life. We can repurpose those technologies so that now people can see it and people can say, huh? Did you know that there are 180, you know, nurses on that shift that have been working for 24 hours straight, you know, who wants to get them a meal? And then that makes it so that people can more actively participate, feel engaged and feel like instead of in a time of despair, they feel like they can actually be part of the solution. And actively participate.

Anthony: So it feels like you've got the data platform in place, you've got the infrastructure there, you've got the ability to collect data on the ground. What more is needed for you to help scale? How do we get this out in the market now?

Kevin: So I think the biggest thing is we need people in the community and especially businesses and business leaders and corporate CSR departments and people who have who want to join in and fund impact. We need to be able to show the support to say, hey, I really care about, for example, delivering essential care packages to elderly. Right. I will pledge this much for that impact. And then that knows that we can talk to those bike couriers and say, hey, guys, we actually have the funding. You can do what you're doing right now, but you can expand it rapidly because, you know, you'll be able to get access for funds for every trip that you make. And that just going to make people who are healthy, who are sitting at home or feeling like they don't have a way to contribute, it can get them off the sidelines to then support and. And so getting the funding and getting the commitments and getting just the awareness that, hey, you can do something about this, I think is the biggest way that we can come together as a community and really support those people who are already organizing.

Anthony: Got it. So it sounds like obviously the existing model as you guys are helping to co-create the programs at a local level and make sure that it fits the model. And then there's a kind of a clearinghouse element is trying to get access to at the moment enterprise or corporate capital to be able to kind of mix those two things together, also to connect the funding with the local programs. But it sounds like also in the longer term, being able to democratize that and being able to open those programs up to anybody who can get access to your platform and who can provide even the smallest amount of capital is gonna be a big part of the story.

Kevin: Oh, it absolutely is. So I think that even in the next in the next week or two, we're going to be able to open it up to anybody who could just provide a meal like I'll provide a meal for a hardworking nurse. I want to. And actually, there's a lot of other interventions that I know that I kind of mentioned, you know, some of the early ones. But I don't think that this is going away. There's going to be people in in lower income neighborhoods who aren't going to have the same infrastructure or access to education if there is an extended period of no school. Things like that. So I don't think that this is a just a two day thing. I think that there's as a short, medium and long term programs or different interventions that are going to be really important. And so getting everyone involved to just say, hey, I think the talk that I saw yesterday was that there's a stimulus package where people could get payments out. I know that if I get a payment of those, you know, the first thing that I'm going to do is be able to move out to the people in the communities that I know are making a difference.

So I'm just getting as many people involved as possible is key.

Anthony: Thank you so much for talking through that. I mean, it's topical, relevant, and also sounds like a really interesting use of the technology and has the potential to scale, not without its challenges. Obviously, there's logistics involved in all of these programs, but it really, really fascinating use of the technology while we're here on technology. I'd love to talk through a little bit for those who obviously are more interested in the development side or on the technical side of the program. Could you tell us a little bit more about working with blockchain or the approach you took to building the platform? How did you work with the theory and what were some of the challenges that you went through as you were building this?

Kevin: Sure, sure, absolutely. So we did start with the choice of Ethereum. It's one of the most widely developer friendly blockchains, most tested. So that was kind of an easy choice for us, which after dealing with, you know, multiple different types of blockchains, just having a developer community. Right, that is so rich like the developer community that just that makes that choice very easy. I think one of the most important protocols that we implement is ERC20, which is a token standard that is widely used. It was used for all the different types of cryptocurrencies that that a lot of them were in the crypto bubble back in, I guess. What was that, 2018? But the ERC20 standard is really strong because it's so tested. And the way that we actually use it is what we do is when we gather this impact data, we actually hash it onto a secure data storage server called IPFS, which I think stands for the inter-planetary file system. But we actually host all the data on IPFS because the data is very rich and extensive, that it would be extremely expensive to actually put all of this data onto it this year in blockchain itself. So that was one of the things that as we went to market, that was one of the things we initially were going to just put all this data onto the blockchain itself. But we quickly realized that it would be prohibitively expensive and it didn't provide more business value from the from the feedback of the people that, you know, that we that we were working with. So instead we can actually store data. We started on a secure server that's hashed so that if that data is ever tampered with, that hash no longer that that hash breaks.

Anthony: The data that's referenced on the Ethereum transaction, obviously using a public blockchain, feels like the appropriate application here. Gas fees are gonna be a part of that, right? So obviously crypto has been up and down and relatively volatile. Does that have an impact on your business model?

Kevin: So one of the things we had talked about earlier is the different uses of technologies. And so, you know, we're super strong and are focused on our on our like having a micro services architecture. And what that means is we actually have a series of blockchain services. So technically, we're blockchain agnostic.

We could spin up a way to create Stellar tokens or wait or a different type of Ethereum tokens or bring on other types of blockchain. So if that was or we could use different blockchains for different business purposes. So we're in talks with trying to structure some impact investment products.

And that is even when gas is low, that is prohibitively expensive to do, high volume, you know, investment products. So, you know, we would explore how can you use, you know, other blockchain that maybe have a, you know, a lower transaction fee or faster throughput, things like that, depending on the use case.

Anthony: Got you. And what are some of the other protocols you're looking at at the moment?

Kevin: So for right now, the to the two that we're looking at the most is either ERC20 or for some of the more I could say larger impacts. So like if you wanted to here's just a silly example. If you wanted to save a rhino, for example, and and you really wanted to have all this rich data on a rhino and someone wanted to own that non-functional token, we could put that onto like an ERC721. So those are the two protocols that we work with the most. The second one that we have that we're working with is Stellar. So we're determining right now if Stellar could be a network for us to be able to transfer this impact data in a digital form to to build these impact investment products more effectively.

Anthony: Brilliant. And so then for anyone out there who's listening, if you ever want to know what is the best protocol for tokenizing a Rhino, it is ERC721.

Kevin: There's a lot of cool projects that do that, that do a lot of different things like that. But yeah, 721 would be a would be a good one for that.

Anthony: And so you talk about micro services architecture. You've got the blockchain protocol behind this. Tell us a little bit more about what else is in the stack. So what are some of the other technologies that you're working with on the platform?

Kevin: So when I think about the architecture, right, there's basically like four main components. There's data input, a lot of different sources. There's verification, which is manual at times. You either want to do over humanised verification or dehumanise. Right, but you want to try to get to that confidence score. Then there's the productisation, right, which is you create a token and then you create a structure and then there's the exit.

So that's, you know, putting it on web, putting it on a dashboard for corporate, putting it on, you know, putting it into an impact investment product. So those are kind of the. And then basically our micro servers are cloud based. Multi-cloud architecture is what it has a series of services that that service each of those four functions.

Anthony: And so then obviously a big part of that is the algorithmic analysis of the data that comes in. Right.

Kevin: Yeah. Yeah. And I did talk about it for that's basically like water, all the series of checks. Right. So right now it could just be like, OK, the geotag from the picture was the same as the GOP attacks in their phone. Now we polled, which was this, which was different than the geotag. They said it was going to be in another place, but it should be different. You know, I mean, like there's all these weird little checks that we can do and then we can basically ramp up the automation of those checks as we get more and more independent data sources.

Or we can basically have a volume high enough to get to actually be able to train a machine learning model.

Anthony: Got it. So at the moment, you've built kind of the business logic of this. The step checks for each data that each data point you collect all the multiple data points that you collect to then come back with a positive or negative or this is verified. This is potentially not verified and that goes through the current system. Is that a manual process at the moment or is that being automated now?

Kevin: Yeah, it's being it's being automated now. It is a manual process. It depends on the use case. Right. Every use case is entirely different and how you verify. And that goes to the different types of models.

But the way to think about it is that we have levels of verification going from V1 to the end. Right. And the end date me being, you know, perfect verification, which will never exist. Right. But the idea is that for V1, for example, it can be about completeness. Do I have all the data? It could be about are the data in the right? Is the data in the right format? Is the data. Giving me the information that is required before we can even look to tokenized V2 is verification can say, OK. How consistent is this data with each other, right? Is this? And then that's where you can run a lot of different checks. It's easier to go through an example, right? Let's talk about one of the harder ones to verify, which is beach cleanups. Right. Or removing ocean trash. That's actually a really interesting verification topic, because if you're trying to verify beach cleanup, it's very disjointed. Every beach cleanup crew in the world is going to have a different process. There's different level of volunteers. It's just a lot crazier. So what we do is for this verification process, we say, OK, we want you to grab pictures when you're on the beach. We want sign ups of the volunteers and pictures for when you sort the trash.

And then after you sort the trash, you know, you're going to cart it over to a recycling center. And then we want a receipt from the recycler and weights on scales, the recycler, for example.

So when you have a picture from a beach and you have a picture from a recycler, you can tell that those geotag should be not in the same place. You can also tell that where they said they recite there, where they said they were going to recycle, it should match where the actual geotag of the picture was. Right. And we've actually mapped out all of these different types of logic checks for all the different use cases that we have on the platform.

Anthony: Fantastic. And so then they layer on top of that as the automation of making sure that the machines can read that, that you can build the logic and it can flow through. So it's a more scalable process.

Kevin: Exactly. Exactly. So everything is almost like you've got to think of it as like a generator. So now we have like a mobile app generator so we can basically choose from a menu of the different impact data types.

And now if you're pulling from a menu, then you can come up with what is the you know, what is the what is the minimum amount before we'll even look to verify it? And then what are all the additional amounts that strengthen the verification, for example? But the idea being that we can strengthen that and we should strengthen verification over time. And one of the things that I love the most about it is that it creates a situation where when you want to get more into forward looking, you could go to more dynamic pricing to say, hey, a pound of ocean trash that has X amount, more verification than one that has, you know, maybe less or lower verification score or however the user might perceive it right. Then that could actually go into the price of it. And then that gives the people on the ground incentive to I want to deliver better data because I could receive more funding, for example.

Anthony: That's a really interesting point, is actually being able to say that the different levels of verification can create different value because the relative proof is stronger. And so then you can have competing projects where you incentivizing your creating and incentivization model for the projects to be able to come back to you with better data.

Kevin: Exactly. Exactly. And they should be the ones to be the experts on what is the data that they that they can grab and water better ways of proving it right. So we work closely with all of these partners to say, hey, like, you know, what are the interventions that are the most impactful? And, you know, what do you think is the best way to prove it? And by guiding them through that kind of structured data process where they might not have access to or the bandwidth to build out these technology projects themselves, but they are definitely experts on how to prove what it is that they do. And so, you know, we're very receptive to bringing that in and making it visible.

Anthony: Kevin, this has been totally fascinating and I'm genuinely inspired by the work you guys are doing. In the course of a podcast, we've gone from banking to blockchain to turtles to the Corona virus to micro services architecture. So I hope there's something in this for everybody in the show today before we close the show. How can people find out more about Proof of Impacts? What are you guys up to next and what have you got going on in your life?

Kevin: So the best way to find out about Proof of Impact is you can go to our Web site www.proofofimpact.com

There's going to be a lot of activity on there, especially with all of this stuff to fight the Corona virus. So I really want to reach out to everyone that's listening. And really either if you want to help in the fight, meaning you think you could help them find funding for some of these projects and programs or on the other end of it, if you're in the community, who is making a difference? And you think that access to funding or access to technology is something that's helpful for you? You know, we will have contact info on our website directly. So I urge everyone to reach out because we think that we can really bring these communities together. So that's kind of the most immediate. The thing that's on the horizon is that, you know, we're really focused on our bringing our offering to corporates and businesses because we think that businesses are, you know, major leaders in the community. And there's been an increasing pressure and increasing importance for them to kind of showcase their sustainability or showcase their involvement in the community. And from the people that we've talked to, it's been very difficult for them. To be able to do that in easy and effective way, so finding ways that we can work with businesses who want to kind of create their impact portfolio so that they can engage with their customers or engage with their employees. That's kind of where our business focus is at. And then for me personally, I'm just, you know, super enthusiastic about the technology and the blockchain space. I have been for a long time. And more and more of these use cases, amazing use cases are popping up every single day. So just being able to learn more about these and and try to apply them into the real world is what my day to day is.

Anthony: And to be clear here, you're looking at projects, you're looking at partnerships on a global basis? Right, because the first episode of Blockchain Won't Save the World. I think we had something like 35 different countries all listening in, every continent was represented in terms of somebody listening somewhere in the world. So in terms of people looking to bring you projects or initiatives or support, that's on a total global basis, right?

Kevin: Total global basis. Our business, our employees, everyone on our team is entirely global. I think we're in like nine different time zones right now and we have 50 partners on almost every continent. So, yeah, absolutely.

Anthony: Great stuff, Kevin. So hopefully Blockchain Won't Save the World might be able to do a little bit to help save the world, particularly in these times of crisis. Thanks again for joining me and really appreciate having you on the show.

Kevin: Thank you so much.