All the Answers you Want to Know About Quadrant— Explained by our CEO

Q&A with SkrillaKing: Highlights and full interview transcript

Quadrant Protocol CEO Mike Davie spoke to Skrillaking a few days ago in a wide-ranging interview covering topics such as big data, Quadrant’s dual token ecosystem, and our much-anticipated MainNet launch.

We highlighted extracts after the Ask-Me-Anything Livestream. But, because we think you cannot get enough of a good thing, we are also outlining here below all the detailed answers in a full transcript. The long text has been provided by a third party and has been lightly edited for content and clarity. The text may not always follow Mike’s words exactly. But it is generally faithful to what was said, even if we could not catch every typo! And, if you seek more precision or have any questions on the transcript, please feel free to reach out to us on Telegram and we will be more than happy to clarify.

Full interview transcript

SkrillaKing:

Alright. Welcome back to another live stream. Today I got Mike from Quadrant Protocol here with us. Pleasure to have you on Mike!

Mike Davie:

Thanks a lot.

SkrillaKing:

So, Mike, why don’t you just start off by telling us a little bit about yourself and how you got involved in blockchain?

Mike Davie:

So my background has been over a decade in commercializing new technologies. Prior to coming down in Singapore, I used to live in South Korea, working for Samsung, and during that time we were commercializing on new mobile technologies and telecommunications tech. But while working with the operators globally, we noticed that there is a big need. People were more concerned about their data. What can they do with their own data? There’s a vast amount of data that’s running across telecom networks, but it’s always getting dumped and these data can actually be used to solve a lot of business and social problems. And so, that’s when, in 2014, I moved down to Singapore and launched a company called DataStreamX. DataStreamX is a data transaction platform and marketplace. It has two layers. One is a marketplace. Anybody can go into DatstreamX right now, log in and go and buy newsfeeds from companies like Thomson Reuters or if you want to find location data from companies like SingTel. It’s all available online, like a point-and-click type transaction. You could subscribe to these monthly feeds. With that we became known as a company to go to when you wanted to find data that you couldn’t find in the market, non-commoditized data.

So companies who are doing new algorithms and running AI projects, they realized that in order to run a successful project- you need to have good data sources and they come to us saying, “Hey we need this data from Malaysia. We need it for Indonesia? Where can we find this?” And so DataStreamX was formed and became known as a place to find location sets. And so, in 2017, in the summer, a bunch of our clients were asking us for more location datasets and these location data sets come from handsets, come from mobile devices. So we went to the market and asked suppliers and said, “Hey, you know, we have these buyers- who are looking for these datasets.” And what happened was that we had four suppliers within a week give us almost the exact same data feed (and you have to imagine these data feeds are like streaming data). And what happened is that there are terabytes per month and all of sudden you are seeing the same data and volume coming through. You have to really start wondering who actually owns this data. Where those data are coming from? Who actually has the rights to buy and sell these data? And of course we went back to our suppliers and said, “Hey where do you get those data from?” And they were like: “We own them, it’s ours.” And, of course, they were trying to be as non-transparent as possible. And so that brought us last summer to start looking for solutions around the questions: how can we bring authenticity and provenance to the data economy? how can we create a more trusted environment for people to transact these live feeds, these live subscriptions? And that’s what brought us on the blockchain. So DataStreamX is looking for a solution and trying to implement a solution on top of our platform and that’s where Quadrant Protocol came from. We started developing the technology back last summer and then realized it was much more than just a marketplace; (we realized) that a lot of companies are looking for how to transact between each other. So that’s why we separated out DataStreamX as the marketplace transaction platform and Quadrant Protocol that will power data transactions in general.

SkrillaKing:

Alright! I think you gave us a good picture of what it is actually, but so could you get into more specifics as to how the protocol actually works because I know that you have separate modules...

Mike Davie:

So the first step is just actually stamping data and what that does, is that when data is created at the source, what we want to do is we want to stamp the signature of that data. So what happens is that, say you’re running a live stream and then you might take every like a five minute chunk and this is how you usually would distribute this to your partners. So what you do as a data producer is you stamp that signature, the hash of that data feed, it could be a file. But for us it’s more like a section tying up data. So it could be a five-minute interval, it could be a one-day interval, and then that signature is stamped into our chain. So whenever somebody goes to consume that data — be it instantly, or a day later, or five years later — then they’ll be able to verify that the data is authentic at the source. There’s a lot that can happen to a data set — maliciously or non-maliciously — stamping is the first foundation that we need, and that we’re implementing in our protocol. So once data is stamped, that’s when you can start doing a lot of services on top of it and that’s when you can start doing supply-chain tracing. So what you do is that — we’ll be releasing next data smart contracts — and so whenever someone goes to purchase data, they can then see where that data came from.

But what the protocol does that once we get the stamping then you go to a data smart contracts with a data smart contract then he can start tracing data to its source so you understand that data supply chain because how the data economy works is that it’s not like there’s one producer of data and then there’s one person who buys it and that’s it: fortunately or unfortunately there’s many many middlemen. People don’t like the term middlemen, but in the data space they’re needed and they’ll always be there. And the reason is that an end buyer of data does not want to go to every single data source and create a contract with that and I’ll give you an example: let’s say Procter and Gamble wants to understand how many shampoo bottles are bought globally. You know it’s an interview question that people always ask philosophically, but nowadays with it being a data driven world is that people are actually going to find these solutions. Procter and Gamble wants to understand how much shampoo is consumed countrywide in different categories. So what they do, is they work with different aggregators in each country. Because if you think about there’s no one who has that data and there’s absolutely no way Procter and Gamble wants to go out and start asking every single person hey well how many shampoo bottles do you purchase. They’ll work maybe in one country like the UK potentially with loyalty point companies, like big Tesco which has a loyalty point card. But Tesco loyalty point data only knows shampoo bottles purchased at Tesco, and so then 7–11 and then 7–11 can provide this data. It’s all anonymized data, but it’s like how many people buy shampoo. And so Procter and Gamble work with many different aggregators to get these data sources. They might only work with like maybe one per country and then inside that country those aggregators will work with different loyalty point companies and transaction companies to aggregate those data. And so that’s how a company like Procter Gamble would get data. And there’s always middlemen that are required between what Quadrant Protocol facilitates is that now Procter and Gamble can have visibility on where this data came from previously and in the current state of the data economy is that companies try to hide their sources and indeed try to make it very non-transparent. They want to basically keep that to themselves. They don’t want to show where the data is coming from but the world is changing. One is that people can fake data very easily. So if you don’t show your sources then it’s easy to lie and make it up. And I was asked “Do you have the rights to it and where did you get it from?” And as soon they say, they won’t show us then you know something’s up there. And on the other side you look at regulation we see things like Cambridge Analytica and Facebook . Because the supply chain was non-transparent, people don’t like that. And regulators are going after companies now and saying Can you show us where you got this data? And a lot of companies right now will just shrug their shoulders and say I know we bought it from maybe this guy. And where did he get it? We don’t know where...And so Quadrant Protocol is step two at the data smart contracts we’ll still facilitate this understanding of the supply chain and then step three after that is one where we start building services on top. And if you look we have partnered with IMDI, which is the government of Singapore here to build a commercial layer on top of our protocol. And what that does will allow companies and micro service companies to build solutions on top. And so that’s what we’re up to.

SkrillaKing:

Did you say the government of Singapore?

Mike Davie:

Yes yes

SkrillaKing:

That’s quite big.

Mike Davie:

Yeah! We we’ve been working with them for a while formulating this and the most important thing for us is like there’s a lot of companies who are coming out and trying to build solutions and micro server solutions. But the issue is they don’t have access to data and so they no matter how great their algorithm is they’ll never be able to create a commercial product. And that’s one of the issues that we see in the market here is that no matter how much support you give these startups or these or corporations to start creating these solutions they realize that there’s no data. It really doesn’t matter what that is. So we formulate this, since last summer with them on how can we create a commercial program or a program that will create a commercial and sustainable ecosystem in the eye like a storage space. And so for us it will work and so Quadrant Protocol a foundation and now be working with all our partners on top to deploy these solutions. And as a two year project with them.

SkrillaKing :

Right. So yeah, I definitely see you are coming from an e-commerce background. I know that you know a lot is data driven right now like it’s all about pinpointing which audience it is. It’s all about getting rid of it. They also see that there might be a concern with that. Like you say suppliers may be recycling the same data presenting it as their own as you say. So what kind of partners do you think Quadrant would work with?

Mike Davie:

So there’s two sides of it. There’s one on the data supply side so companies are looking at monetizing their data creating data products from it. So the supply side we’re always looking for new innovative data. This can be anything from an application and IoT company anybody who’s basically creating raw feeds and a lot of times companies don’t understand the usage of their data. They might create a product and they don’t really realize all that other use cases for that. So one on the supply side we’re always interested in looking at different data feeds that can give insights into either consumers into companies under performance. And then in secondary on the other side is we have this concept called Elons, companies basically take data and then create new products and services from it. These are the real innovators and these are key partners for us. So it could be an AI company which is building a new solution that wants to layer multiple types of data into their solution and they’re looking for data sources so that a key partner with us. Second is like innovation hubs either incubators or corporate innovation centers. We’re trying to develop new solutions based on data. These companies are usually looking for multiple cross industry data sets and are looking for partners who could facilitate that. So those are also very key partners force a data hungry data driven organizations.

SkrillaKing:

So I actually found a question here from Mickey, which I want to run with you as we talk about this topic right now and that is how in a practical sense how Quadrant Protocol actually going to help businesses make better decisions? You see some correlation there.

Mike Davie:

Yeah. So there’s two ways I guess to take better business decisions as well as from how to purchase data and then business unused data and then the other business decisions on what data insights the data can provide. So in terms of the first one on business decisions what we found over the course of a year transacting data like with DataStreamX. I think it’s like 20 billion records a month now that we’re processing between organizations and we’ve learned how companies purchase data. And one of the things we’ve seen is that a lot of companies don’t understand the sources and they’re spending millions of dollars on false data. And you mentioned you’re in the e-commerce space that a lot of it is duplicate of its overlapping and there’s actually no value add to it. So what Quadrant can do on it on a procurement standpoint. It can help them understand their supply chain better, save money, and be able actually trace down the sources so that it makes better procurement decisions so. So for Quadrant Protocol on the buyer side the user side of data can help a lot with their procurement processes. Also add regulation. So in terms of the governments coming down ensuring, where people are getting data from Quadrant will help enable us as well. On the other side, on just the usages of data we are finding a lot of companies are becoming more data savvy. They’re hiring data scientists data analytics staff to basically start looking at new data.

And that’s we’re just having an ecosystem of data allows for companies to sort of realize what they can actually do these days on the e-commerce space. We’ve seen a lot of people looking at online/offline, because you can get a lot of data on the online world but how does that translate to off line sales or how does off line patterns affect online sales. So like for example if you just Amazon or any e-commerce shop they want to know how people go to malls when they go to malls. What do they look at and how do they do price comparison. And if they are in a store then in price comparison they want to know that because if you just only took online data at Amazon only took their search data for example then they’d only understand what people are looking for. But for them it’s actually better to know is that person standing in a store doing a price comparison than buying in a store. Or are they actually at home which is a totally different user experience and what users actually doing. And so data from Quadrant will allow people. We see companies making better decisions by using more and more data so more of that becomes available.

SkrillaKing:

Yeah fantastic. Because I could actually relate to that specific example that you have there because I actually used to work in a in an e-commerce but also in retail stores regular retail and we were having those discussions like people coming into the store and just checking the price and going back home and buying it. So it’s definitely going to be useful for businesses. I could see that 100 percent. So could we speak a little bit about the tokens themselves. So you’re having the ICO now right.

Mike Davie:

Yes we are.

SkrillaKing:

Yeah. And you had some private investors and you had to raise these soft cap

Mike Davie:

Oh yeah, we passed a soft cap and we passed our vesting cap, so we raised enough funds to last the next five years, so we’re very excited to be able to continue our mission here.

Skrilla King:

Right. So how does dual-token work in the cause. Because I actually heard that you have two tokens. Could you explain a little bit about that?

Mike Davie:

Yeah. So the form of the tokens that we released is our ERC20 token it’s just a much easier token to work with these days whenever you’re just trying to do the actual token sale. So the ERC20 token on Ethereum and then from there we have a sidechain. So we have our own chain and there’s a one to one conversion. So as soon you add those tokens in your wallet, then you can actually start using services. There’s a gateway between the two chains. And so this just allows people to actually get in and started using our services. So our internal token is offering access to three core services. The first is the data stamping. So using services on a network. So if you’re a data provider and you want to actually start stamping your data into our network then you basically use our token as a gas fee fee for the services. In Phase 2 you’ll be able to use our token to purchase data. So the data smart contracts would be unlocked via the token. So companies will be able to actually use our token to be able to purchase and pay for subscriptions and then the third usage site is a roll. I find really interesting on how regraded using staking in our system when you look at from experience and how companies purchase data they usually want to know and make sure the data actually is useful first and they want to understand how they can solve a problem. The good and the bad thing about that though it drives sales, people who are trying to actually sell data. So like a hedge fund for example they don’t want to spend a million dollars on data unless they can find Alpha from it or if you’re an insurance company or an innovation center and they have no idea what this data can do for them that they’re not going to go and fork out 200 thousand dollars first they want to start looking at the data and start seeing to solve their issues.

And so what we’re really doing for these type of people who we call Elons these innovators- what we’re doing is allow them to stake out tokens and then when they stake they’ll be able to get access to certain levels of data and then they ask lobbyist staking mechanism and so companies data science divisions groups hedge funds they’ll be able to get access to data for testing purposes via staking mechanism.

SkrillaKing:

Right. So I actually got a question from Roxanne here saying what information would you be able to see about the previous owners of that data?

Mike Davie:

So two things on that. So to give an example who’s producing data let’s just say it’s a Thomson Reuters news and some purchases these and then create a social sentiment off that and then resell these sentiment scores. So the party is able to see who’s purchasing settlement will be able to understand it OK this day the original data the news data came from Thomson Reuters. So depending on how they nest they’ll be able to see that complete supply chain. So in terms of how the data goes through that there’s a nesting of the data smart contracts. So as long as everybody keeps it on chain what they’ll be able to do is see where these data came from and what was the inputs into that. On the other side depending on what the question is formed, you all know who purchased the data. You’ll be able to see the wallet ID, but you won’t be able to see your purchases. So say there is Thompson Reuters news and they have a thousand buyers of theses data. You’d be able to see that there is a thousand buyers of these data, but you wouldn’t be able to actually see who those buyers were. That makes sense to me.

SkrillaKing:

So I actually got a question from crypto as well which I think is super good. So what kind of data would you guys handle. Is it any data in privacy as well? And if yes how secure is quadrant?

Mike Davie:

So we are data agnostic meaning that it could be anything from news to social sentiment to weather and etc.. Even if we are data agnostic we do have areas that we’re really focusing on first. The first is the location analytics space. We see a lot of great work being done there, so these are location feeds, point of interest data, mapping data that’s our first just because we know that’s a very robust ecosystem right now and a lot of people are looking for these data feeds from there, we’ll be moving into alternative data, which is used by a lot of hedge funds. And then in the future we see ourselves in the medical data space as we expand the protocol and end the use cases going into the personal data question. So think the second part of that question is no data is stored in Quadrant, so we are storage agnostic. And the reason is that we know from years of experience that every data supplier is a little different every data feeds a little different high velocity strains require a totally different mechanism of access than photos or videos or data like stagnant data that only updates me once a day or once a month. We handle everything from a relational databases to no sequels databases to live feeds and so our protocols self the data smart contracts are agnostic to the storage solution. And so the data suppliers the data providers will have to rule based on their own data. Right. So they based on their own data. So whatever security measures that’s required for the data, health data is very different a requirement than like stock data or whether data. So if you if somebody is transacting health data then they would have to ensure they abide by whatever local laws are required for that those data feeds.

SkrillaKing:

Actually, I want to ask you something that is on the mind of many people right now in crypto and that is the case of regulation and that is both in terms of the view that the tokens and but also as the business idea as a whole. So we start with the tokens. I’m sure if you have an idea where it stands in terms of regulation in terms of it being a security or not.

Mike Davie:

Yeah, we are a pure utility token. There’s no aspect, there’s no profit sharing, or own ownership. eQuad is clearly a utility token to get access to services on the network

SkrillaKing:

Right. So the second part is in terms of the business itself do you see some regulation that you need to tackle there or is it just a straight smooth sailing?

Mike Davie:

In the data space there is already a lot of regulation. So it depends on what data that you’re actually storing what that you’re working with in terms like recently in Europe. GDPR has a fact a lot of e-mail saying that you are in a bind to a new policy. And but the thing is and the data space you really want to be aware of the regulations that pertain to your individual data sets and that we understand and we can provide insight and help and we know how we must handle things like we don’t store data and so forth and that it’s people have to understand what regulations are required for the data. So when you up when I give an example of healthcare days health care in the US has very strict laws on how you can store who can transact it but there’s also other datasets like simple like transactional. I mentioned the shampoo example, if you’re in China and you’re giving economic data or data that that can give insights the economy is a falsity. Like all retail sales data and you’re sending that out of the country that’s actually illegal. Every country has it’s own laws. And anybody who thinks they’re willing to provide data or store data they must be aware of what those laws are and how they pertain to their own business.

SkrillaKing:

Alright. So you wanted this to be a massive success obviously. So what are the major obstacles if any that you need to overcome in order to achieve that and become as successful as possible?

Mike Davie:

Yeah. I think the key thing is adoption of data. And so we’ve been in this space for a while here and we see a lot of news out news articles and PR from companies saying hey they’re doing all these great things a day. But when you start digging behind the scenes you realize that they’re actually not the area. And so the big focus for us at Quadrant, is to be able to enable different use cases one by one and actually change how companies operate change the insights that they can actually get and then replicate it. The beautiful thing about data is that if one is somebody solving an issue in Singapore with location data that seems solution might be needed in Malaysia, Russia, Germany... And so it’s really easy to replicate on a global scale. And that’s actually one of the great results of doing this ICO is that we’ve built a global network of 22 different supporters and that’s available on our website. There’s a map of that and what we want to do is create that global network where we can take these use cases. And so the most important thing for us is going forward into next year to get solid use cases that we can replicate and then take those UK use case into each country and then may expand it so people can do it. And that’s what’s really good ICOs things to grow and we’ve seen this already with DataStreamX and transacting data is that once people know that you know they use case then they come to us that source and they come to us at expert and that’s what Quadrant we want to do is we want to create that global network where people can trust us and come to us and ask us hey we want to solve this issue where do we get the data? And then how do we do it? So our biggest thing is to make sure that the user adoption and that there’s enough people who know how to use data to solve their issues.

SkrillaKing:

Okay so J.C. asks and I hope that this is relevant: How is your partnership with Bluzelle going to evolve?

Mike Davie:

We know that their public Testnet was launched last night. And so when you look at Bluzelle storage layer depending on different data sets and the data use case that it can be a very good storage system. So when you create a data smart contract, you’ll be able to select your storage- how you want to store the data at your storing AWS. Great if you’re storing it in Bluzelle, then we can provide that access mechanism. So when you purchase data on quadrant you’ll be able then to access that storage on Bluzelle.

SkrillaKing:

Yeah, definitely remember that blockchain is the future guys. So Nathan Matthew asks what type of decentralized data are you make a blueprint into and which do you support till now?

Mike Davie:

Yes. OK so yeah, they obviously use a lot of different data sets, but let me give you one example: the location data space- that’s a location data where it comes from devices anonymized data feeds that comes from millions devices. And these are aggregated on STK level. And so we work with these STK providers right now. So we work with a global set of these. And then what we do is we start mapping them together and then providing those on to our clients. That’s where our revenue generating company with clients who are using our data services. And so yeah. So this is one example and this is actually where Quadrant, came from is that when we started mapping all these different STK providers we realized that there was a cross pollination we’re at STK provider we’re selling into another STK provider and then both of them were providing us the data. And so the mapping for us is that we have to identify where the data comes from and then we build it into new products. So that’s a bad one use case right now that we’ve been very successful.

SkrillaKing:

So in terms of the roadmap where are you now like what are your main focus right now?

Mike Davie:

Yes the main focus right now is to get our MainNet set up for the stamp because our stamping is already taking place right now or just we’ll be releasing a video on that shortly. The TestNet that we released it back on May. So our next step is to basically go live with our MainNet or so that people can continue to use those services like stamping service- that authenticity is like. Like I said it’s a foundation it’s the first thing we need to do. And so our work on right now our work right now is to get that ready so we can go live with that and then our main Next step is the data smart contracts and how we’re going to be investing these smart contracts to basically allow for the visibility in the supply chain and then the people can purchase via that.

SkrillaKing:

So MCE Hoddle ask Do you have a bounty program?

Mike Davie:

We do have a bounty program, go into a telegram group and ask for it.

SkrillaKing:

All right. So we got a question here from babyKrypto which I think is also super relevant. And that is concerning the token cell itself about these tokens. Are you close to surpassing the hard cap. Is that correct?

Mike Davie:

Yes. So are hosting our public sale right now is open. There’s still a lot of room in the public crowdsale, we just opened last week. It’s going to be open for 30 days right now. And so new people can still come in now if if we don’t reach that cap then we’ll just be locking those tokens for two years since it’s.

SkrillaKing:

Because he was a bit concerned with that. Why will you just don’t burn the unsold tokens?

Mike Davie:

We are an utility token, we’re not a security. And so we have to make our decisions based on what’s best for the network and best for our users of this . So for us it’s important that we have these and we’ll keep them for the next couple of years. And then if in the future if we if that’s correct then we’ll sell it at that point. But the key thing is that we out the use for the usage of the network burning anywhere burning I know a lot people will say do it so the price goes up. Unfortunately, we can’t speculate on pricing in those things like that. And burning is it’s more of a tactic to try to do that part. So we’re more focused on the utility aspect of the token. We’ve already discussed and is in the white paper clearly that if they’re not sold it would just be held.

SkrillaKing:

Yeah. So RippleDude asks “Will this staking work like that with master node or just normal proof of stake?”

Mike Davie:

So it’s actually a little bit different so it’s not we’re not staying for a master node. So staking for few years if you want a massive, then basically you stake X amount and then you’re running and know what a night no then produces the blocks and then you get a payment for that. That’s not the staking we’re discussing here the staking that we’re doing is to get access to the data. So a company would then have to stake the token in a smart contract which then would enable them to get access to the data feeds in that. And so this is a little bit different mechanism is not to basically be producing blocks as like a staking consensus mechanism works. It’s to get access to data. And this is how they say the data economy works and how companies transact in that. Like if you’re a hedge fund and you’re also you go to something say I want to have your million dollars’ worth of data.You know that the companies just don’t want to randomly give their entire data assets even today even. Doesn’t matter how many trillions of dollars in assets they have. They want to make sure they’re going to get something out of it. They’re not wasting time. So the staking mechanism will facilitate companies who are really genuine are looking for data to solve their problems to actually stake and get access to them. So that’s how our staking mechanism works is on an access mechanism not a block creation.

SkrillaKing:

So we have come to a question which was inevitable to be asked during the live stream and that was the case of exchanges. So do you have any plans there or

Mike Davie:

Unforeseen, we are not able to comment about secondary markets.

SkrillaKing:

If you were to make a projection in your head where would you see Quadrant in three years from now.

Mike Davie:

So in three years from now it’s basically we’re developing the use cases right. We already know the location space and we are ready. And then the alternative data spaces. I’ll try to see data more and more like hedge funds taking in like satellite feeds and so we see the growth of the use cases where we see like 3-4 years from now is actually, we see the healthcare side on the IoT side, where as more and more this day comes available we’re busy bigger and better solutions being made. We’re really seeing governments and large organizations making better services for people and Quadrant protocol facilitating all these with Quadrant protocol are all but often just improvidence showing the supply chain and building an ecosystem of trust where people know where the day is coming from and where it’s going to. And while we build this ecosystem we’re going to see more and more companies entrust the data and be able to actually create better solutions from it. So it’s three years from now hopefully we’ll be even. Be changing the world even more with with data power solutions .

SkrillaKing:

Right. So if someone wants to get some more information regarding Quadrant what is the best way to get that information?

Mike Davie:

So please jump in our Telegram group. We really love technical questions. If you have any of those please come in. I’m more than happy to answer them there. You can also check out media if you want to start seeing about our partners. So the task that and so forth are going to meet young and go to quadrantprotocol.com and find more information.

SkrillaKing:

Right. So I want to run it up with another question here from babyKrypto asking. So you don’t store the data yourself but do you have any kind of protection in place to protect it from hackers and all these malicious people who want to steal all kinds of data?

Mike Davie:

Yeah so the data itself wouldn’t actually be stored with us so when companies are storing it at a depth that is use a regular access mechanism is right good in terms that if you’re using the U.S. good key management and so forth encryption at rest. All these things are on the company’s side. Things that they need to do that. Yeah whatever access mechanism we’re using, using relational database if you’re using an API if you’re getting access to an S3 bucket on Amazon that each one of those has their own security measures that people will have to make sure that they use Bluzelle for example. Great examples of the distributed. So in terms of the Bluzelle, like one of their nodes gets hacked it’s easy to say you’re using the blues and network with us. Then it falls on. Yeah the one no gets hacked and their own security. You can check out Bluzelle’s whitepaper on that.

SkrillaKing:

So Joe Afik asks: “Do you have any competitors in this industry. And what separates Quadrant from these kind ?”

Mike Davie:

Yeah. So in this space there’s a lot of different definitions of what a competitor can be. So Quadrant itself is a protocol to enable the data transactions. And so we are not a data marketplace. DataStreamX acts as a data marketplace and there’s a lot of different data marketplaces there. Quadrant is just the underlying tact that can power these type of solutions. So whenever we look at like marketplaces or Monetize your data these are actually all partners for us. So companies like Fysical and Airblock these are all potential people who can basically supply data through our network. The closest competitor that we would say is Ocean Protocol, we get compared to a lot. So Ocean would be our closest competitors in this space, but they also give you a partner to know we know the guys there that there is also areas of cooperation. We’ve been in this data space for years and like even in the data marketplace space I know all the guys who and the CEOs are all friends or on Skype and that over the years we’ve created a marketplace some sold some got acquired. Others are still running. We all know each other. And when you look at it like I mentioned that there’s all these middlemen in between. They all actually can work together. Your competitor can also be your partner you might both try to sell the same customer or you might actually like partner and then sell the different customers. So it’s a very interesting space where it’s not like you’re butting heads with people and it’s a winner. One winner takes all. It doesn’t work that way in this space.

SkrillaKing:

Right. So I think that’s super interactive and great e-mail here. Is there anything you want around this one up with the kind of final notes something you want to add to the conversation.

Mike Davie:

So if there’s anybody who is listening on data supply space you’re projecting your time of data monetization. Please talk to us and see if there’s areas of cooperation and if you’re an AI company and you’re looking for data sources your very data driven if you’re working with Oracle’s and so forth any data feeds power please contact us and get in touch and we can see if we can work together. And for anybody else check out quadrantprotocol.com for more information.

SkrillaKing:

Yeah definitely. And Mike I want to thank you so much for joining us here today. I wish you all the success. I’m sure that we are going to be able to cover this in the future as well we will have our eyes on it definitely within our community. Thank you so much and have a good day Mike and everyone else in the live stream.

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