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Computer America. Hello, and welcome everyone into the Computer America Show. We
are the nation's longest running nationally syndicated radio talk show on computers and technology term
podcasts. Everyone, welcome into the program. I hope that you're doing well
and you are ready for today's program, because we have a very special show
where we're going to be talking about the classics aimachine learning but applied in a
new way. And I'm really looking forward to talking with our guests about how
you can use AI and machine learning to really help with marketing. And of
course we're going to throw in a little bit of QR code system in there,
and ladies and gentlemen, this is just it really feels like a natural
evolution to all these technologies and kind of how to apply them a little bit
differently than what you've heard before. So we'll be joined by reloads here in
just a moment. But before we get into that, computer America america dot
com. That's where real find everything, including past shows, future shows,
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that at Computer America, find us on social media, and of course anything
that we talk about today if you want a link to our guest website if
you want, you know, just anything that may come up on the show.
Everything will be included in the show notes. So of course I'll be
in the descriptions, but of course at computer America dot com. So with
all that being said, that's our introduction. Let's go ahead and bring on
our guests and have some fun. So, as I said before, relotus
dot com, r e l otis dot com if you want to check them
out, we are joined by the founder and CEO, mister Alani Kue.
He is the founder CEO. There we go, but yeah, he's joining
us here and to talk all about the system, what it does, how
it works, and ladies and gentlemen, let's go ahead and get started.
So Alannie, welcome onto the program. Yeah, thank you for having me.
It's a pleasure. It's a pleasure being hideou you know, load to
everyone. And I'm very happy to be you know. I made your show,
right, that's awesome. I made it. Yeah, happy to have
you. Happy to have you. So I think with you know the way
these things go, let's get some background. Let's you know, what is
your past. Have you always been in technology or is this or have you
just been an entrepreneur? What is your background before you got into RELOADUS.
So I spent twenty one plus years in the enterprise technology space. I actually
started as an engineer and then went into more executive roles over the last ten
fifteen years. So we think about supply chain management systems, logistics platforms,
dealing with the US government on a global scale, predominantly with disaster recovery,
and data storage, high performance computing clusters. And over the last few years
in more executive roles, I've been the founder. I've done a few really
interesting projects and now technically for the machine learning and also on blockchain actually kind
of blockchain um technology and showing transparency, inclusion, ubiquity and really technically complex
programs. Um, my expertise really is in simplification and scale. So you
think about RAID application deployment, M rapid application development and scale deployments. So
you know, and and uh, very very very nice sistory. And it's
a natural fit for you know, kind of how we got to RELOADUS.
I wanted to you know, kind of address the because you mentioned blockchain.
There was a there was a time on computer America where when the blockchain was
really really going, everyone was rushing to get a new uh, you know,
a new coin out there. They were rushing to do a new application.
They had a new blockchain that was going to fix everything from you know,
shipping and managing to the medical field to you know, there was a
blockchain for everything. I think a lot of the a lot of the hype,
a lot of the excitement kind of died down. But from your opinion,
and we're going to also tie this into a on machine learning back then,
blockchain is like a buzzword. Did the blockchain when you know, when
all the deaths settled, it's kind of a known technology for people they need
to know about it. Did it have an impact on the technology field?
And then let's say AI machine learning. Is it just a buzzword or are
these technologies going to have an impact on you know, technology at large or
specific fields. So first, I think you know blockchain as a whole,
you have to think about the history and why it came to be right,
So the goal was inclusion, transparency, ubiquity, right, and consensus.
So obviously would any new technology stack. There's an excitement around it, and
the bastardization of any new thing is why everybody was launching a token. It's
actually because there's a lot of projects at the time. They know a lot
more about their tokenomics than their actual products. Many of them didn't even have
a product. You know, they had a coin, right, but it
did nothing. They can only trade it or stake it. They can only
tell you how to defy it. You know, how to earn more coins
from doing complex financial transactions with those coins. But when you ask them what's
the use case? Nine of them had no use case. They had a
white paper, but when you read it, it had no gravitas. So
when you now fast forward, right, that rapid adoption meant a lot of
capital moved predominantly from the retail sector because most people naturally wants the easier out.
So it's oh, man, I can just buy this coin and wait
forward to thousand X and then sell it. Well, they took in a
lot of capital, but there was really no liquidity. There's a lot of
their capital just evaporated or ended up in other projects. So people will start,
for example X token, sell it so that they can take that money
to go buy bitcoin. So the ultimate beneficiary was you know, the bitcoins,
the ethereums of the world, the stable original you know, cryptocurrency projects.
Because many of those quote unquote scam projects was just another avenue to pull
liquidity so they can go buy more bitcoin, you know. So when you
take that yeah, so when you fast forward, now regulators are now saying,
wait a minute, you guys have the opportunity to self government. You
didn't do it, so here we will come and do it for you.
Hence the issue with Secretary Gainsler and the gang at the SEC. You know,
as much as I have my own opinions on what they're doing, quite
frankly, the blocks in industry had an opportunity to self government and they never
did it. Okay, So it's like the child who had many opportunities to
clean up his room do it, And here comes mom and dad saying,
okay, you know what, We're gonna take away your video game. We're
gonna take away your cell phone, and then we're gonna teach you how to
clean your room, not the way you want to, how to win through
and what tools to use, and you go practice that. When you come
back, you'll earn your video gaming, your cell phone, and your car
keys back. And now the kids throwing a tantrum, saying, my parents,
parents just don't understand right, like the old Will Smith Will Smith song,
all these all these dumb rules that don't you know that shouldn't apply to
us. But yeah, yeah, yeah, I got your good, good
analogy exactly. So if you act like children, we will treat you like
children. So they need to be adults in the room. So now AI
comes behind that. So can you imagine if the blocks and industry adopted you
know, rules of engagement and then AI comes on top of that. Imagine
how much value would have been unlocked through that exercise. But they fail at
that. Now Air a machine learning its hair, and everyone's trying to pivot
to amail, right, okay, but aimail yet to have a use case
you have to have a use case. You have to solve simple problems that
anybody understands, not vanity problems, not vanity metrics, not cool things.
Unfortunately, in a lot of blockchain you have folks who build cool tools so
they can go brag on Twitter about the cool thing they just built, maybe
for them and their friends. And the question I always asking them is did
you build this for humans or you built it for you and your bodies so
you can go get Twitter likes? Right? Nine times out of ten the
vanity tools. You know, no one needs another wallet, did you know
wallet? No one needs another block Explorer, right, No one needs another
you know, fancy tool that only people who live in you know, the
Western world with certain infrastruar. You know, vanity problems. You know,
they are people out there who are starving. There are people who have real
problems they're trying to solve every day. You know, cool things don't matter
to them. So and you know we've seen that with AI and machine learning
when it came too like chatbots. You know, everyone a lot of big
companies we're trying to create chatbots, and you know there might have been a
use case down the road, but when they created them. They were just
kind of like, oh, we'll train it, and you know, it'll
do a thing, and you know, maybe it'll be cool and maybe we'll
do something with it later. You're and you know, all of the conversation
we just had, you're saying that AI machine learning needs to be like,
it's a very cool technology, but it needs to be targeted to solve a
problem. And you chose, I guess uh, you know, reloadus too,
you know as your use case. I guess correct. So two rules
in any industry, you cannot scale what you can simplify. And secondly,
if your key value proposition isn't obvious, that means even you don't know it
well enough. Right. So if you take Google, for example, you
know, twenty five or so years ago and this very day, the homepage
looks the same. We all know there's a lot of technology behind it,
right, But when you go to Google, it's one search bard low cognitive
load. Anybody can go there and they know what's going on. Love or
hate the company. They nail that to the point where the company name is
now used as a verb. Yeah, that's simplicity at scale. It's Yahoo.
On the other hand, older than Google, once one of the largest
companies in the world. Right has had an identity crisis for thirty plus years.
The homepage has always been busy. You don't know which one is a
Yahoo find. Too much going on today. And as a matter of fact,
they have the opportunity to acquire Google. They have the opportunity to acquire
Google pennies on the dollar at twenty million or something like that. Yeah,
today Google is one of, if not the largest company on the planet non
financial, if you exclude Black Rook in Citadelle and you know those guys,
Yeah, who is a department of the Horizon? Okay, Yeah, you
can't simplify, you can't scale it so so and and and then of course
to um that's of course a very famous story in technology. I'm sure someone
at Yahoo has been kicking themselves for a long time. Um. But when
it comes to UM, so simplifying and what you're saying is we need to
simplify when it comes to AI machine learning, we need to make it simple
for the customer because right now, like whenever we have talked about in the
past, creating these things, you either copy and paste when someone else has
done, or you go out and hire some people and a lot of money,
a lot of effort goes into this thing called like a black box that
no one really knows how it's done. You want people to use AI machine
learning for you know, for reloss case. You want to be very simple.
I guess it's the point you're getting at. You want end users to
be able to harness this and they just go somewhere and it just does what
they needed to do. That's correct. Correct, So what reality is?
This is basically AI that streamlines enterprise data insights for you know, specialty controlled
items, which humanizes information, reduces compliance risks, and increases sufficiencies. Whether
you're a manufacturer or directed directed constrom, a brand or a distributor. What
that means is whether you're a marketing genius, or you're a warehouse worker or
you're an intern. Right wherever you are across the value chain, you can
interact with the system in humanized like human language. It's so simple you have
to want to not use it, do not know how to use it?
Onboarding time in fifteen seconds or less. Quite frankly, how how was that
accomplished? Did you get a bunch of people that didn't know you know really
anything or was that constant iteration and just finding pain points? Um? I
mean that simplification that that could not have been a quick process. How long
have you been kind of working on on relotus? It took about a year
and a half actually, and it was there were moments where we're thinking,
oh, man, why is this a stealth exercise? Because as a matter
of fact, you know, and and and part of folks who participated in
that, you know exercise. You know, we had someone who spent you
know, fourteen years with Central Intelligence, um and you know you will find
out at some point, you know, and about ten years at the Federal
Bureau of Investigation, we had you know three you know AI blockchain, very
brilliant devs who pretty much built entirely chains from scratch, and also non technical
users. Right, so you have a very healthy mix of Okay, if
I'm coming from a certain world and a multimath thiss what what am I looking
for? What am I seeing? Right? And you have folks who have
nothing to do, so you have both experts from different perspectives looking at it
and providing direct feedback. So what then happens is you look at how do
we unlock value using aimail, you know, in a way that analyze millions
of personas and data points right share the insights to improve performance, creating and
deploying that those data sets with authenticity using deep learning, natural language processing,
and email insights to automate this processor talking about you know, how do we
take human learning model and optimize it right to use customer interaction and product delivery
using this technology in a submission less low cognitive load matter. Yeah, so,
so some cares when a company wants to start using this product. Are
you pulling data from data points that are already being you know, kind of
captured because I know that you know, there's a lot of on the back
end that kind of uh, you know, tracks what the customer does and
you know, kind of other points that may deter them things like that.
Like what I'm saying is is there can this just use the data that is
already captured by most companies or do you have to kind of onboard onto the
system, Let the system run for six months in the background, capture new
different, you know, very specific data points, and then you can train
your model and do it. Or can anyone just jump in and you can
start using reloadists right off the bat. So first things first is we have
to you're using controlled data sets, right, and that for us is a
couple of days because we're not using public information. We're using information that's protected,
got walls around it. Unlike consumer GPT technology that says, oh we're
just going to Google to open source intelligence, you know, and script Wikipedia,
script whatever. In many cases it just gives your false information. Right.
So for you know, when you take that enterprise perspective and say we're
looking at control data sets, right, data that's non public. Right,
So if you have say four petabytes or ten terabytes of data that's been sitting
in an SAP server for a company, you know that I've accumulated over years.
So the realities goes in and just force through that data. And we're
talking a few days. And it's a continuous process, right, So whether
you start on day one or six months, it's a continuous process is constantly
looking and refining. Know that that data set and it as it refines it,
right, he's able to finesse. So you have increased accuracy right just
by looking at you know, so the data itself is proprietary, you know,
the data sets you're looking at. It's not public, so I have
data accuracy I mean anybody, and from my perspective, and feel free to
correct anything I'm saying because you're you're definitely you know, ahead above me when
it comes to all this. But from from my understanding, like that,
that's where you really want to be, because when it comes to machine learning,
when you use those public data sets and like those much much bigger data
sets, um, everything just kind of comes out, you know, the
same flavor, and everything's just kind of I guess, like a muted version
of what AI and machine learning can be. But when you you know,
like you said, you use a custom data set, Uh, it's much
more I don't want to say, like active, much more like accurate or
you know, useful, I guess to the customer, right, yes,
yes, it's it's it's controlled and it's non public. It's more useful.
It's more accurate, right, more insightful. It's also familiar. So I'll
give you a quick example. We all know that vanity metrics are a scam.
Think about this. Many companies will spend one hundred thousand a million dollars
a month to go to social media marketing ads. Right, Yeah, they
get a million, like one hundred thousand shares, you know, maybe another
one hundred thousand new followers. Won't you ask them those million did you get
a million new customers or one hundred thousand new customers? Then they start giving
you the fancy answers. Well, we look at engagements. I don't need
all the fancy marketing mundo jumbo. At the end of the day, it's
all vanity metrics or okay, half those interactions our ball from the platform to
make you think you're getting new engagement. You don't really have any really meaningful
insights. It's a scam. So, well, you're you're really buying the
so and that's what you know. That's where you're on. You're buying the
social media's product, which is uh, the engagement. You're buying there,
and of course they want to sell you the best product they can, so
I guess they're selling you, uh, the engagement. They're selling you the
like the visibility. But you're right, you know that that's not a strict
customer that that is uh, that's actually you're you're paying money for a product
and that product is visibility. But you know what that really means to a
company. Yeah, correctly, and we've seen and we've seen the exposure on
that front where we've realized that half at least of those interactions are blots.
You know just what two years ago when Facebook or subpoena to provide even last
year during the one must Twitter fiasco where the world turned out, you know
what, fifty six percent you know of the Twitter user base or just box
and he put out that one intent, We're going to clean up the platform
and many of you might lose, you know, a chunk of your followers.
It's just because we're cleaning up a platform. So you start to look
at and you realize that, I mean, I boldly call it a scam
because for the longest time, it actually started way back during the geocds and
Yahoo days. You put up a banner at an HTML. You got to
coach, you pay for it for clicks, and people are going to India
click click click farms in India. You pay you know, a thousand dollars
and you get a bunch of kids in the room just clicking under you know,
to put your page rent value up to make it look like you get
a lot of the users. Right, So where AI know where realtives comes
in. It is gone away with all that. Okay, you look at
a control data set, right, and every unique data point about that customer,
which is history, brand association, timing, be hit everything, location
awareness, GEO, everything is embedded in their QR code. So if you
bought a pair of Nike sneakers, for example, right, the think about
it this week. The most the most exciting time that you love to hear
from your vendor is when you receive your product. I'm sure is that a
show on microphone? You have? H This is yes, yes, so
sure did you get it? Did you get it on Amazon? Um?
I think I was actually talking to the shore manufacturer themselves when I got it.
So yeah, that they've been on the show a few times. So
but yeah, okay, okay, that's okay, mini indulsement for sure.
No, no, they I was talking about you guy. But but no,
I uh, I see your point. You know, when let's say
my let's say my monitor. I have a big old monitor, um,
and I bought that off Amazon, and you know I've enjoyed it for a
long time. So please continue with your a You're good. There you go.
So when it arrived at your doorstep and you see that package. As
a matter of fact, when you look down your driveway and you see that
Amazon truck and you know you're expecting something, whether or not it's your stuff
being delivered, there's a dopamine rush in your head. My stuff is here.
When it's actually your stuff, you know, it just goes up.
You're at the door, you see your name on it. It feels great
because that's when you're most excited to hear from your vendor. Every other time
you don't care. You don't want to see ther spam emails. You don't
want to see any of that stuff. So imagine now you get your shot
microphone and they say, hey, we see you bought the shore and based
on what you bought in the past, you bought all the related brands for
this short microphone. However, right, you can get you know, a
you know, Cloud sound optimizer for it if you're in the next discount.
Oh, by the way, you know there's a pro tools component that goes
so all of that based on your unique behavior on the platform, and it's
incentivized. Right, So now, as a customer locause this is relevant I
was saying earlier, if you bought a pair of Nike sneakers. It looks
well, you've bought Nike, you bot reblock you but whatever, yes,
what there's a para of Nike socks that's your size that if you order the
next two weeks, whatever, hair, they're incentives. So oh, by
the way, it's in a warehouse. Now you say you can order the
same day before knowing them, get it by two o'clock today. So all
of those unique characteristics. And that's just a tip of the iceberg, because
now we're getting into other areas like pharmaceutical industries where if you are a diabetic,
for example, and you've been paying for a certain insulin product, right,
and we can look in the system and we know that based on what
you're buying, based on where you live, based on your age, you're
likely retired across to retirement, here is the equivalent, generic version with the
same characteristics to save you money on your healthcare costs, valuable data or insights.
Yeah, I and and that really um I wanted to you know,
touch on that a little bit because there's certainly, uh, it's almost like
scary the situation that you set up because of how much you know I'm sure
people have experienced it themselves, but it seems almost predatory that there's a machine
out there, there's a system out there that is you know, kind of
almost reading your mind. Like obviously it's just you know, predicting the next
thing and you know, kind of using conclusions to arrive that. You know,
hey, you may want those socks that like you said, um,
but there is a there's a positive influence for consumers out there. And I
really like your example for the diabetics that you know, there are generics,
there are cheaper things, there are things that you need that you don't even
think you know that you don't even think about that could really help you in
your situation. Like there's there's a positive aspect, Like obviously there's a positive
for companies that you know, you can get more conversions, get more you
get more customers. But for the customer there's a value there too, right,
excuse me, absolutely, And that's the point when we start to look
at all the areas where AIML is very valuable, you know, predominant relatives
because you look at and I use a healthcare you know example, you know
that's a very very very very easy one among many you know, but again,
as I said earlier, we have to look at technology from a use
case perspective. Is it solving relatable, tangible problems, not just vanity problems.
So the guy who wants to order a Nike, that's a convenience thing.
Okay, if the world's not going to end, if you don't have
any Parniki sneakers, I think you know the person you know who's ordering monitors,
again, that's a convenience you know, I call it a first world
problem, right. But when you start getting into healthcare, for example,
it's not just you know, there's all the elements like that. People today
who can't pay their rank, they have to choose between the your rent and
ther health. Okay, that's why you start to unlock value, right.
And then you get into other industries, you know, whether it's you know,
a manufacturing director, consumer brands being able to again optimize for certain product
lines based on unique behaviors, not the conventions say spray and pray. Right,
let's your offer every discount and hope some of them take it. That's
wrong, okay, And it's debatable you talk about the invasive nature. It's
because again you have to give people the choice if value is there, most
people are reasonable. Most people are reasonable if you demonstrate value, right,
it's a give or take. I always say that, you know, if
I was in the US Senate, for example, I will push to I
will push very hard to pass a law that says, every time you sign
up for a social media account, okay, then to tell you how much
they will make momentizing your data every year, and you should have the right
to ask for a piece of those spots I have. I've heard that argument
before. It's uh. And to a lot of people it's like it's like
what a company pay me like that that company would never would never work.
But at the same time, it's like company's making a lot of money off
here and you don't even know it, Like it's yeah, yeah, So
it's a it's a shared responsibility. You can't socialize the cost while privatizing the
games, right. So from a blockchain, that's part of what blockchain does.
You know, Platforms like mask Protocol, which you know I've worked very
closely with, do exactly that. Brave Browsing kind of tries to do that
where the revenue they shared across the user base so they get at loyal user
base obviously, right, but that's part of the promise of blockchain that to
your earlier observation, your point you ambassidized where people sold the Louhangen through the
of just lunching a coin, right, and they can and somehow they lost
you know that that that broadermission statement, right, So and and uh to
bring this back around to to reload us and you know, um here here
are my notes, and you've mentioned a couple of times with the QR code.
Uh, tell us about your product maybe go through Uh well, actually,
let's let's just focus on Uh. So there's a QR code that goes
onto a product and I guess that like does a customer scan that is that
just something that goes through um, you know, like the point of sale
and you know that's when you kind of know who buys it and what goes
in the payment information? Like how does reloadus kind of track all this or
how does the QR code work into your service? Okay, So, so
the platform itself just looks at historical data. So an API call an API
connection just okay, hey, we're gonna give you API access to our whether
it's your warehouse management system or your CRM system, whatever you use, it
doesn't matter what it's platform and SAP or cooled, g D Edwards or whatever
the platform is, it looks at it and it starts to peace and pass
through all of those data points. Because every customer normally has a customer ID
and no tough customer IDs are the same. So you get the primary key
and it's a tree like a pyramid, and they just bore down into you
start to build a narrative. So each whether it's five customers or five billion
customers, each one it's a unique entity. And as it passes through that,
all of those fine data points are embedded in that smart QR. It's
actually attached on the box. So when it's coming up with conveyor belts some
point, it's like to put inserts in, you know, it's just it's
just a time little sticker that goes on the box, right, Okay,
and what happens. Also remember I could be a guy in marketing or finance
or whatever, just to ask the system, you know, tell me my
most active customer in Charlotte, North Carolina, or my least active customers in
or my least five active regions in New England or Texas or whatever it is,
and editor you and recommend incentives or engagement programs or initiatives for those regions.
How do we increase sales in our least activity. It's just human language.
And what happens is since it's passed through all that data, it will
spit it out to you. Oh, the least active regions are New York
discounties, right, These are the products and brands they've interacted with in this
timeframe. And to reengage them take these actions, do you want to yes
or no? Yes, boom, it says to you know, and at
the point where products go out, it's already embedded. So the guys down
stream they just see a printed PR code on that box that's just going out.
They don't even put all that sort of the taking care of Yeah,
that's I hope that value. Yeah, and you kind of answer. The
next question I had was when you had that situation where you know, uh,
and for anyone out there watching the video portion, you can see,
you know, we can kind of showing the website in the background where you
get those real time, the real time recommendations to optimize each customer. Um.
So my next question was, you know is that is that also automated
to you know, put out you know, a ten percent sale or stuff
like that, or is that where the human steps in and goes, Okay,
I'll take these recommendations and apply them. And it sounds like your system
can also just you know, either say yes or no, and then your
system can take it away and start to do the recommendations that it recommends.
Correct. So once it's actually going to ask you do you should I do
this? Basically do you want these incentives activated? It's you just say if
you say no, field or nothing. If you say yes, everything's automated
and all you just see the spat out. So it's so again the point
being low cognitive load so that it's scalable makes makes perfect sense. So so
so tell me about your existing customers. I mean, what's the feedback then,
because uh, you know, development time and development in a lab is
one thing. Testing it in the real world. Has it been you know,
kind of like amazement. Has it been? Uh? Yeah, this
is really handy. How's the response to Actually it's been phenomenal because we started
with you know, two um two of the largest distributors of vaping products in
the US, and you know, it's a very highly regulated industry. They
cannot legally advertise on conventional channels, they can't give a way freebees, they
can do any of that, you know. So we were able to integrate
into their system and unlock by just reselling to their existing customers new new customers.
So now you're generating millions just going back you're existing customers who bought from
you by engaging them in a much more accurate, you know, decisive manner.
Because again that's what unlocks value. Okay, by engaging them in a
way they understand based on their preferences, not just a spray impress. Most
people would just go, oh, let's just block send an email blast to
all our twenty million. No, if you fact, this is again where
you unlock value. Because now we go into this industry, right, retarget
those who are bought either recently or so long ago based on their unique characteristics.
Right, and they start buying again. You can say, and we're
going to go tell, you know, give us at least performing regions and
how we can optimize based on brand, you know, brand loyalty purchasing patterns.
And you go in there and they go, okay, go to Charlotte,
go to you know, Miami, Florida, go to Philadelphia. Offer
these incentives because these brands that you carry are active in those regions, I
think, and you can have more incentives based on your distribution locations being closer
to those customers in those regions. Oh, by the way, these customers
live near metropolitan areas, and these are also related brands that are currently offering
X, Y Z the incentive. So you start and you hit go,
and all that's buried in there. So the customer, right, what happens
is they get the product, they go, Oh, not only do I
say on this product, there are all these all the related things that I
had done and they're in the past, I had in the record with in
the past, and I would have them in a while. And they're offering
so information, clarity, engagement, right, transparency that it don't need analysis
paralysis. Yeah, and I'm sure that there's a lot of marketing people out
there that are that are definitely because there's so many ways nowadays, so many
promises out there of how to market your product and the returns and all that
kind of thing. This really seems to take even more data points than you
know, one person can really take at once themselves. What product do you
think this really benefits from? Like, is this like a food soft drink
thing, Is this like a clothing thing or you know, we talked about
the healthcare in the medical field. What products do you think best would benefit
from a system like this the quite friends, I think healthcare and direct to
consumer brands. I think for me personally, I really do. I'm pushing
hard with healthcare. Part because healthcare is an ongoing issue in this part of
the world. Yeah, because the costs you know to individuals and families such
as astronomical, and that's a very right area for disruption. Yes, we
have companies who deliver you know, medication to different neighborhoods, individuals, retirement
homes, senior homes, all that, but I think there's a lot of
infrastructure built around it, but the cost either remains the same or goes up.
So they're inherent imail and on love value to make life easier. That's
where I really see it's going now, and I really appreciate that they can
answer, because you know, healthcare, we spend more per capita than any
other country, but we get you know, in some cases much inferior healthcare
out there. You're right, and you know, using the resources that we
obviously pour into it more effectively. I guess that's really at the heart of
of RELOADUS is you know, kind of efficiency when it comes down to it,
So make perfect fit exactly. And then secondary areas is the complete opposite,
which is director consumer branch, you know, especially toys, kids,
toys for example, you know, being able to leverage the tech to say,
hey, you know, here are the toys your kids like. By
the way, oh, you bought you know, a Voltron set or you
bought Legos for example, by the way, you know, here are related
items to this product, right, based on what you what you bought and
what you know, what you what you what your you're you're purchasing patterns look
like right, whether it's standard. Because when you get a Lego box,
for example, especially around the holidays, is because you're gonna get visitors,
they're gonna get family most of the time, so family kids. If you
have Lego boxes, I hope a whole bunch of grown up folks I aren't
sitting around playing with Legos. But back to your audience, Um, but
a bunch of kids and let's be frank, kids equals germs. You want
to get hand sanitizers. So my point is makes sense. There's there's ways
we can live. For example, you bought a show microphone, chances are
you're other building a studio. You know, you actually out of an office.
Right, So again you know AI and mL looks at that based on
your patterns. You know, if you bought that, then you have an
air on chair. We can build a whole narrative around that. But you
also control that because when you do stand that QR code, you can opt
out the future. Uh, you know communication. That being said, if
the engagement is useful and there's a key valley prop that's very obvious and you
benefited from it, ninety six percent of engagees don't all out simply because it
makes sense. It's the Sammy Stills these stuff that turns people off. Right.
Yeah, there's always a system where you know, opt in versus opt
out, and it's uh, you know, people are what is the old
role It's like ninety ten like opt in, Uh, ninety ninety percent people
will not ten percent if people will opt out, ninety percent people will not
opt out, and ten percent of people will but yeah, if you spam
them constantly with the same and you know, um, I uh to give
to give you an example that I have my personal life. There's UM like
clothing stores like you know, Dillard's, Belk, you know whatever. At
some point in the past ten years, I've signed up for you know,
a lot of their mailing stuff. Um, you know ai uh, I
use Gmail like everyone else. At some point they've all been filtered out,
you know, for spam, for not clicking their links. It was just
not effective. And at some point even Google was like, you know,
these are just getting annoying, Like we're not going to show you these anymore.
So you're saying that your system can you know, kind of do a
little bit better job than eventually getting caught by the spam filter exactly the person
is what I'm gonna saying out of emails. Yeah, it's just straight.
I mean that QR code as or starts. So think of something, you
know, we actually funny enough compare to conventional UM engagement models, which is
obviously pay for play, you know, price per click, you know,
cost for meal and all that. Right, Yeah, you just don't even
pay a dime unless someone actually uses a QR code. Yeah, and and
I was going to ask you a little bit about you know, kind of
where your business comes into the play, because you know your business and uh,
and the point is to uh, you know, provide a service and
get paid for it. That's always important. UM. When it comes to
the cost, We've had people on the show before that have said I have
revolutionized UM. We had a company on that did the satellites shipping lanes and
they're like, you know, we have redone the system for UM for redoing
the shipping lanes across the Indian Ocean in the Pacific Ocean. And I'm like
that's great. It's like, yeah, we just need to get everyone to
switch over to it. And I'm like, do you think they're going to
abandon everything, restructure everything, and you know, put in new hardware to
get this going. And it's like, well, you know maybe. So
when it comes to cost for businesses, UM, you know, how much
is there is there a high kind of paywall to get into this or tell
us about the pricing scheme that you've come up with. Yeah, So first
things first, you know, AIML is a four plus trillion dollar industry and
the potential you know, valley capture is simply astronomical. We're talking to five
percent KR, right, so for ross is on boarding is actually zero.
There you what tests of this model is worked? Okay? Convention as I
said earlier is you know, pay per click or legacy platforms, but the
relatives platform it's actually pay per engagement. So it costs a customer, our
customer zero to get onboarded, get activated. They pay only when that end
user saves that QR code scancing real engagement any quartfrent and it's very transparent.
It's twenty cents a click. There you sale sale or our customers it's about
eighty five dollars right, Some are up to three four hundred dollars per sale.
Would you pay eighty cents or one hundred dollars sale? I mean twenty
cents four hundred dollars? Would you pay twenty cents for an eighty hundred dollars
sale? Yeah? Yeah, would you pay? Would you pay one hundred
thousand dollars four one hundred thousand Facebook lights when half of them a box?
So when and then you know, it does kind of raise the question why
you felt this wasn't um no, that wasn't necessary, but um, clearly
you could have had where uh, you know, put a little algorithm in
there and be like, you know, your average sale. You know,
this customer's average sale was one hundred dollars, So we're going to take you
know, maybe a percentage or a sliding scale or something like that. Twenty
cents per click is pretty standard. Uh, do you think that's going to
change in the future, You know, the value that we give you is
going to be a percentage or a sliding scale that you give back to us,
or are you just looking for something that you know this is to grow
and you think at you know, at large, this is going to stay
pretty low. That number is going to remain. Um so long as I'm
at the hell all right right now? That's that's that's definitely great. And
and and tell us a little bit real quick about like the templates, because
you know, here just so everyone knows, and again you can find this
on your website. Clearly, give a custom project, you seem very open,
knowledgeable, and you will work with you know, a larger company that
needs a more custom option. Sure, but for other companies out there,
tell us about templates because I think this gets into the part where you're saying
low. You know that's all overhead. You just very simple. So tell
us about templates. So, templates are just mechanisms that users can use to
customize their own interface. Right, So if someone if if your customer scans
at QR code, where do you want them to go to? Right,
directly to a shopping cord, directly to a and they paid directly to a
branded version of the system. So we provide multiple templates again to give customers
a flexibility to taylor that last mile and user experience. You know, so
their industry right to whatever within the confines of templates of course, to whatever
end, extend ease or experience they want for because remember, once they scare
cure our code, we've brought that customer back in. It's still important,
you know, it's still incumbent on the customer to complete that conversion. We've
done our part at that point. So to help ease that transition. That's
why those templates exist and they continue to grow for them, How can we
make that last mile easier that journey? Help? Can we help you complete
that process? And in most cases, I mean a few cases we've had
so far, they just wanted their own templates and you know it's they have
to use it if you want to use it, right, they just mix
that journy easier. So it's the lower the cognitive load making easy. Yes,
our job very important. Uh. And and one more thing I want
to touch on because you you mentioned it a way at the beginning and I
wanted to raiterate because it's always a priority here on our show. Uh.
Security when it comes to handling data stuff like that. You know you mentioned
you have an you accept people's APIs on your end. Is security of consideration
or is this running on? You know, you go to Starbucks and you
kind of not knock out the project while you're a Starbucks. Like, how
important security to your company? Well? First things first, is a closed
loop system, so it's not available to an Intel decorhire. If you're not
a customer of ours you have, you just don't have access to the system.
And they every security protocol today. Remember, you can't work with you
know, a small company the same way you work with a large enterprise company.
The reason most large companies move slow, it's because they're mature and there
was process. Process means protocol means security means governances, transparency, accountability because
you have to report on those things, and that from an enterprise perspective,
is baked into the system. Again I said, it's not a public facing
system. It's not available to anybody unless you're a customer that has the unslayer
contract with us. You don't even get to see it. The same way
you just go to Yeah, the same way you're just gonna go to SAP
and say, hey, give me an SAP account or given an Oracle account.
You who are you? Right? Yeah? For sure? For sure?
So uh so so realists, you have launched, you have a website.
Obviously, people can contact you, you know if they want to get
you know, get things going. What stage area because we have a question
here about individual investors venture capitalists. Um, obviously you know you've you've started
it. Now is are you at the point of trying to scale the company
and you know, try to get more more money in there to hire people
and do more Like what stage of of of growth are are you in?
Yes? So with the two enterprise you know customers in the system, it's
been phenomenal, um and will continue to leverage those relationships and as you saw,
they've actually gone to baffle us very publicly UM and some of the you
know um items that we've seen on Yahoo plans and other areas. So where
it is right now is in the growth stage. I mean, we're in
market, we're in service. You know. Reals is one of the only
three omail platforms that actually has revenue and paying customers. And I challenge anybody
to dispute this every other Yeah, imal platform. It's still an experiment there
in the lab. Okay, there is a ton of money at hypervaluations.
They still perform an experience stability yea stability AI. They just got caught two
months ago who just ripped chat, GPT and rebranded and there is a quarter
of a billion dollars on top of that with your hand in the cookie jar,
very similar to to like you mentioned, with all the different tokens and
coins that were happening with with you know, everything was just a bit a
rip off of ethereum, you know. And yeah, anybody can go and
GitHub and fork a rebol and rebrand it and call it. I'm launching my
own chain. As a matter of fact, I did an experiment. I
launched the chain. You know, this was last year. That's part of
R and D exercise launched in all fifteen minutes, launched the chain. Okay,
put him and I'm going to mechanics. Even a high level justist that
they put about three hundred dollars into a initial liquidity and in about thirty minutes
when you looked, you know, on being you know, um Binance,
some of the advocators out there had the big exchanges in the company had a
forty five million dollar market cap in fifteen minutes. Yeah, welcome to crypto,
right, Yeah, that's the government. Yeah, there you go.
And I run valid I've build valido programs, I've run valido program for a
lot of really big change. Actually wrote a paper on valido governments and I'll
share that link with you and you can share out with your users as well.
You look at that, I should not be able to do that,
you know what I mean, I should not be able to do that.
But but but that, but that that's really the state that we're in.
And I said that that initial excitement about a technology, Um, you know,
there's there's of course going to be people excited lick you that are going
to start companies and you know, have an idea and you know, really
try to apply the technology in a new and you know, innovative and productive
way. But there's going to be others that are just going to be like,
oh, there's excitement here. That means there's money to be made here,
and that's what's going to ruin it for a lot of people. But
uh yeah, and I I just shared the link to the papers dot com.
It's an academic it's a good read. You can share that with your
audience world. It's why governments it's important because these chains become holygar keys at
best, scammers at worst. Okay, because anybody can lunk to chain and
get five of the buddies to set up you know, one hundred dollars computers
as validators and say hey, here's my chain, we have five validators,
here's a coin, go buy it, and people just flock to that stuff.
You know, there was a time similar to the click farms from back
in the day. You know, there were you know, farms where people
would just go to certain countries, pay a bunch of people, you know,
give them ten dollars each to pretend people are buying. There's a lot
of ten dollars transactions on the chain, and people think, oh, people
are buying this coin right, candy pylon and exponentially it's a snowball effect,
you know. So how do you implement governance? How do you put on
transparency and accountability? Yeah? Yeah, and and I would like to share
this set out there that you know, they say something like when it came
to cryptocurrency, and then and then I'll get off topic and we'll kind of
wrap it up here, but I could say, like cryptocurrency, they said,
like two percent of all transactions are you know, either fraud or not
fraudulent, but like through scammers and you know and other people like that.
Nine it was proven that like ninety percent of transactions are you know, cryptocurrency
one wallet to the other wallet where the two wallet owners are the same person,
you know, the same person transfers transfers it or launders it or do
something like that. So that means like eight percent of all transactions out there
are like legitimate transactions between two parties, two percent out there are scammers,
and ninety percent is all just fluff. It's all just you know, fake.
So yeah, you know, finding actual value and use case for you
know, crypt out there, Like that's a budding market even though it looks
big, it may not be as big, and AI can very much be
the same way. But finding good products that utilize the technology in a you
know, in a useful way. That's that's where we're at. And I'm
really happy that you know, you decided to come to us with three lotus
because it sounds like you're you know, that's what you're going for useful.
Yes, yes, again, we humanize it so we can scale it.
You can't scale what you can sim and that's what Realtist does. And going
back to your final question a few minutes ago, I think from an investment
perspective, we are in market. We're in service with contracts with customers,
okay, with revenues, so we are scaling. Okay, Well I'm not.
We're not interested in you know what I call glorified loan agencies. Right,
it's the right. We're calling partners, not even investors, with the
right mindset that scales. If you, if you, if you have no
experience with scaling, this is not the right opportunity with them. And as
astute partners with a sense of urgency that understand scale. Right, So U,
but before I start wrap it up here, um uh, is there
anything that we didn't touch on, We didn't talk about that. You feel
like we should get in here for our listeners or do you think we've touched
on a lot of what RELOADUS is. I think we've touched on on,
you know, most of what it is they are. But we could go,
we could keep going. I can tell you that there's a whole lot
that I can I mean, this is coming from experiences, is coming from
having done this a few times. So there's a lot of areas we can
get into, things like ecosystem, you know, the actual technology, you
know, what the competitive landscape looks like. You know, I always talk
about open AI, which is focused on the consumer space, and now we're
finding out the issue with you know being you know, us AT utilizes in
OSI open source intelligence you know, leads to false information as we're seeing chap
GEB just making things up, you know. And then we have Microsoft AI,
which Microsoft only builds products for their customers because they have about at least
thirty years thirty to forty years of data and customers. So when they build
anything, they build it going into their existing market, which is SharePoint,
office and all that. So again very different market segment and then cloud Minds,
which is trying to do the cloud computing basically optimize based on what you
know, glorified you know Amazon, you know Aws, um so relatives.
On the other hand, let's just say it earlier. It's specifically focused on
BTC, you know, interaction, simplification and just engagement. That almost pain
you, but that's actually a good should be easy Yeah, and and and
that's actually a good point that we should touch on a little bit when it
comes to your competitors. I mean, um, you know, let's say
Microsoft, and he said, you know, thirty forty years of customer data.
I mean when in your field, does like is data just king like,
is you know, the just the sheer amount of data either proprietary or
closed or I'm sorry, proprietary or open? Does is just whoever has the
most data wins? Or do you think maybe like these smaller custom ais really
have a place and that's where it's really going to matter. M Who are
your customers and who do you think is going to like really settle out.
Is it just going to be the people who are the most creative, or
is it going to be the Amazon the Microsoft's out there who have the most
data I think. I mean the smaller shops who are the most creative are
the ones who are ultimately going to win this. I remember, it's not
even a battle, it's not a game. They're going to win what I
call the market engagement in their market segment. So let me just clarify something
about that. Sure, not every company, even though every company wants to
be big, not every company needs to be a unicorn. They are companies
that do phenomenal business, sustainable and even the fifteen hundred million dollars range,
that's their sweet spot. Okay, they are companies who scale and go four
five billion dollars you know, hyper unicorns out there, and that's their market
segment. Right. So there's an old saying everybody wants to go to head
and nobody wants to die. Right, you get small shops, I want
to get big, But when they get big, they don't know how to
handle it, right, and somehow they disintegrate casing point yeah right, So
my point being, every market segment has a sweet spot. The big shops,
the awss Microsoft xps of the world, when they build tools, they
build full their existing customers because like Microsoft, they have forty plus years of
data that they're sitting on. Okay, so they're just squeezing value out of
an existing asset that they have. However, the smaller shops are able to
start a fresh right and deliver new value based on new realities. Hence the
legacy companies moving at a certain place and the small shops being creative. That's
why MNA transactions happen because the smaller shops demonstrate at Jill a team that the
big identities never have to worry about because they have existing sets in terms of
data going back decades. So what do they do. They acquire those smaller
shops to bring that agility and also that engenuity and creativity aimto the a recal
system and that's a continuous cycle. It's like a it's like a ferris wheel.
Because we absolve a small shop, there's a hundred other small shops,
you know, in line, so that innovation will always continue, you know,
in that regard, make no no makes perfect sense. So I think
that Annie, I'll be honest with you, this interview was supposed to be
about half an hour. I've kept you for way too long. I apologize,
but this has been a very fun conversation. Yeah, so so yeah,
no, no, this has been great and for everyone out there,
we're gonna start wrapping up here. But if they want to find out more
information, I'm guessing reloadus again. Our el otis dot com is the best
place to get us. That's correct. And email, just email support a
relatives dot com and you can actually email me directly A Lonnie at realtis dot
com. All right, well, we might not put you your actually email
in the show notes, but in the show notes, we're gonna have the
website. We're gonna have all that stuff in there. We're also going to
have the research paper that you sent over as well. We'll have a link
to that if anyone would like to check that out. And ladies and gentlemen
again computer America dot com for everything that you need to know about today.
But I want to thank I want to thank A Lonnie for coming here.
He is again the founder and CEO of the company, and A Loannie thank
you so much. You've been very knowledgeable and this has been a great interview.
Thank you sir very much. Appreciate it. All right, have a
great one everyone out there. We'll catch you next time. Until next time,
Bye, everyone,