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L1X Exclusive Interview With Insight Genesis (L1X | Hackathon 2025 Participant)
Recorded: March 19, 2025 Duration: 0:27:01Space Recording
Short Summary
Branson and Jay unveil Insight Genesis, a groundbreaking Web3 project focused on AI-powered data insights, during the L1X Hackathon AMA. With strategic partnerships and a target of 100,000 users, they aim to revolutionize data ownership and monetization in the blockchain space.
Full Transcription
Hello, everyone. Hello, Jay and Branson. Welcome to the L1X Hackathon AMA series. How are you
guys doing?
We are good. Thanks for inviting us here.
Awesome. Thanks for inviting us.
I know it's late in the night for you guys. It's 11 PM in Singapore. So yeah, really appreciate
you taking the time not only to apply for the hackathon, but also to be part of this AMA and volunteering to share your experience with the community.
So before we get to further down the line, JN Branson, do you just want to give a brief
introduction about yourself and about Genesis AI and what has it that you've been doing?
Yeah, sounds good. Maybe I'll go first. Yeah, so I'm Branson. So I've been in this industry since 2017. So started my blockchain journey when I first bought my, actually I bought two Bitcoins, you know, back in 2017 and down the rabbit hole I went.
And ever since then I've been in the industry,
did a couple of startups, launched an exchange in 2018,
got licensed by MAS, which is the central bank in Singapore.
And ever since then, you know,
I've been doing a lot of blockchain consultancies
on the site.
And myself and Jay, we finally met.
Actually, we knew each other for a long time since 2017.
We caught up again a few times and we sort of hit it off.
It was last year.
And then we were talking about doing a project together.
And that's how we went on this journey of starting this project called Insight Genesis.
Yeah.
Jay?
Sounds good.
Well, my name is Jay.
I'm part of the start in Web3 journey since also 2017,
that's some time ago.
Done numerous projects in the past,
of course, all along doing the blockchain Web3 advisory,
also builds a community in the association blockchain Asia
on the vice president.
So meet a lot of startup, do a lot of advising work,
consulting work, supporting works, community works,
KOL, numerous role, done many different roles in the Web3 industry,
CEO, COO, COMO, different roles,
until we started our own project, Insight Genesis.
I think it's very unique.
That's why we wanted to handle ourselves.
Maybe Branson can actually explain more
on the Insight Genesis, what we are doing later.
Sounds good. So Branson, do you want to? Yeah, so maybe I'll share a little bit. Yeah,
yeah, sure. Yeah, yeah. So Insight Genesis is a Web3 AI data, AI powered data data insights. And at the end of the day, what we want to do is to enable entities or users to be able to share and own
that data.
And what I mean by that is that at the end of the day,
you basically have a lot of data.
So all of us have a lot of data.
But the question is, how do we then monetize some
of this data, and at the same time retain ownership
as well as, you know, keep the high up information coming in. So based on all this data that we have, the question is how do you make sense of it?
So with our kind of technology, we're
able to use three types of data.
The first is your face.
So everyone has a mobile phone.
You can actually use a camera to scan your face.
That's one.
The second is from your voice.
And the third is from your social digital footprint.
So making use of all these three kinds of data,
we can actually provide insights into the specific things about this person.
So it could be things like, is this person hardworking? Is this person suited for a certain job?
Is this person under a some of this data from
from the entire gist of it. But I think more importantly, our technology is proven. In other words,
our parent company has been invested in by HSBC. So that is again a testament to you know the technology itself being tested and widely used within the financial institutions sector from FDA,
used by insurance companies, and approved or certified medical
to speak.
So I think all these things are sort of something
that we are very proud of. But more importantly, there are four ways that potentially some of our data insights
can be used.
The first is in the area, you know, the citizens may or may not have access to their identity.
So here, some of the financial institutions are making use of their face, their voice, and some of the social digital footprint to actually come up with a credit score.
And then from there, some of these users or consumers can actually get access to financial services sector. So by scanning your face, we're able to show you
a very comprehensive report, things like blood pressure
and so on and so forth.
There are tons of so-called biomarkers
that you can actually glean off this data.
And this is very useful, especially
for telemedicine companies.
So when you do telemedicine, the doctor
will definitely need a triage of some
of your initial vital signs, your biomarkers.
And this is where we are very strong.
And third area is actually in the academic space.
So if you're a student 17, 18 years old,
you have no idea what you want to go into.
That's where you can actually use our technology, So if you are a student 17, 18 years old, you have no idea what you want to go into.
That's where you can actually, you know, scan, use our technology, scan your face.
And then from there, we can actually show to you some of your inclination.
So for example, let's say if you're conscientious of your person who likes to be... Who is back out going?
Then perhaps, you know, business administration or some other causes of cheap. Most of the companies out there,
you know, for all the MNCs or even SMEs, people is their main, or hire the best people. The
question is how do you look well looked after, but wealth or even stress, the question is how do you
find out and read it, you know, nip it in the bud before it gets worse, right, and then that leads to attrition or dropout or
you know, resonations. So we have worked with a few companies and the accuracy is
up to 83%. In fact, in some cases 93%. So the question is, you know, how do we
then push this technology out to more of these companies
or industries out there?
So that's a long way of explaining what we do, but I hope that gives you an idea of what
we're doing.
Yeah.
Well, thank you, Branson.
That's very, very helpful.
And first off, my apologies for getting your name wrong to the community, but at least
I got part of it right.
I was calling in Genesis AI
which is inside Genesis. So I guess like a question Jay and Branson, so what stage is
your product in? Are you at ideation stage or is your product already built out?
So like I explained earlier, I think, yeah,... Teruskan.
Kerana teknologi ini sudah menjadi semakin berguna dalam industri Web2, kami telah menetapkan di Web3.
Jadi, ia bukan idea yang langsung kerana ia sudah digunakan dalam Web2 selama 3 tahun. Currently we are in the NPV stage, putting up all the project on the chain, putting on chain.
So we're in this stage. Yes. Got it. And which chain are you on right now?
We have not selected a chain yet, but most likely will be a multi-chain.
Got it. Okay, that's great. So I think that brings us right to the question. So,
you know, why L1X? How did you hear about us? What is it about L1X that sort of got you interested
to participate in the hackathon? Well, the hackathon, of course, we wanted to try to try out,
see whether we are using the chain,
whether it's suitable for us, for both party.
And we could also make use of the grant
if we are, if we manage to win the hackathon
to apply on our project to try it out.
Got it.
And so of course, when you looked at L1X,
of course L1X is a chain in itself
and it has its interoperability component. So as you mentioned that you will be going
multi-chain. Was that something that was of interest to you? Is that one of the areas
that attracted you about L1X?
What do you think?
Yeah. Yeah. So that's one of the key areas, right?
Because interoperability is obviously very important for us.
We want to make sure that the accessibility to most users out there is right up there.
And at the same time, I think we are also considering things
like the databases.
The question is, how do you store data?
Because when we scan faces as well as voice analysis,
I think there's tons of data out there.
The question is, how do we store this data? You know, strong is the. How about this, Branson? I think we have some internet issues. So how about we all put up our own...
I'll go next.
Branson and Jade, do you think it's okay if we switch off the video because it looks like Branson has...
...focus on databases like RockDB, Postgres and so on and so forth?
That could be one area that we're looking at. Of course, the next question is how do we keep them safe and secure?
So those are the things that we are looking at.
Sorry Branson, I think what I suggested, let's switch off a video because it looks
like you've got some bandwidth issues. So let's switch off our videos and then that
would help.
Yeah, sure.
Awesome.
Looks like we lost Branson. in. You're coming. I think he's a...
Yes, I think once he comes back in, let's switch off our videos and let's see how it goes.
Sorry, I got disconnected.
You hear me?
Yes, we can hear you.
So yeah, we've got our videos off.
Jay, maybe do you want to switch off your video as well,
just so that we can tell about Bram?
OK, perfect.
Yes, Bram said, so I think yes.
We lost you where you were talking a little bit about L1x
and what attracted you to it.
So if you don't mind just talking about it again
and repeating yourself on that, that would be great. Yeah, so I think there are a few areas that we
are interested in when we try to work with L1X. I think the first is interoperability.
As we have explained, I think we will go multi-chain. I think that's our strategy.
And LYX being one of the things out there that will support multi-chains, I think
that's one key area. And the second area is obviously, you know, data storage. I think when
you scan faces, you use cameras, as well as the question is, do we store them and I understand that L1X supports
multiple databases like Cassandra, Postgres, RockDB. So those are so-called potential databases that
we could be looking at. Of course the other consideration is how secure we can keep them
because at the end of the day we want them to be sufficiently decentralized and at the same time
Because at the end of the day, we
want them to be sufficiently decentralized,
and at the same time, secure enough for the users
to own this data.
Yeah.
Got it.
OK, yes, that's very helpful.
And I think that's a really good use case of L1x, where not only
you want to use L1x as your chain,
but you would also want to use it for interoperability.
So I guess this brings me to my next question, Jay and Branson.
Have you looked at other interoperability protocols
up there?
And if so, you don't have to talk about the ones
that you looked at.
But just out of curiosity, what is it
that you found good about them?
What is it that if you've done any analysis,
just to understand that?
What about them is something that you
feel is lacking,
if you will, that you're still not zeroed in
on an interoperability protocol,
and you're looking for something else.
Yeah, so I think we, when we, I mean,
most of the chains out there, it really depends, right?
hints out there, it really depends.
So if you're talking about EVMs, mostly rollups.
So if you're talking about EVMs, mostly rollups.
But when you talk about brand new layer one solutions,
I think most of them will essentially
as a form of solution. natively the users themselves would not
think of coming to the chain but in order to make it interoperable they will actually build bridges
to the EVM world. So I think that's the main solution that we have seen so far.
solution that we have seen so far. Yeah. Okay, got it. So I guess like the bridge-less
interoperability part of L1X is something that you're keen on exploring?
Yes, potentially, yes. Okay, that makes sense. And when you talk about like your applications
and when you talk about sort of the target base, what is it that's like your ideal target base, if you will?
When you talk about target base, what exactly do you mean?
I mean, like, are you looking at institutions?
Are you looking at retail?
So we basically were with both groups.
But of course, institutions would have access
to a lot more data because they themselves
would have their group of clientele,
which they already have been working with for a long time.
And then retail themselves, they can put up so much earlier.
All this data, the face, the voice,
for them to actually use as an extension
to gain access to other Web3 services.
So by using our services, I think what they can do
is to control all this data within
the single platform.
Yeah.
Yeah.
Got it.
Okay.
Yeah.
That, that makes a lot more sense.
So what are some typical use cases that you're thinking about?
What do you think would be some initial target use cases that you would want to go
you would want to go to market with if you will.
to market with, if you will?
So the main use case that we have sort of worked with
is actually enabling access to financial services.
But in the Web3 space, I think the main use case would be products and services available to a DAX,
for example, or extra services, because different people would have different epitaphs for risk.
So the question is, are we able to then tailor
some of these solutions to some of these audience?
So if I know that this particular person, based
on the face and the digital social footprint,
that he's of a more riser-verse kind of clientele,
then can I offer him other solutions besides just a normal
trading account?
So that's from the exchange point of view.
That could be sort of the low hanging fruit that we're talking about.
Okay, that makes sense.
And so if you could just double-click on that use case, Branson, what do you think is at
a high level? What would be your ideal go-to-market strategy,
if you will?
So right now, I think our main strategy
is to work with entities.
Because I think the businesses themselves
would have a lot of data.
It's not just data that is based on the consumer behavior.
But it could be other things, for example.
Let's say if I'm working with a telco, for example,
or let's say a telco, so they would have a lot of clients.
And these clients are just mobile phone users.
But the question is, based on the so-called time
that they use these services or the amount of data
that they use on their plans, can there
be insights being processed or analyzed
based on some of this data?
And then from there, can the telcos or other even entities or corporates make use of some of this data and then from there, and the telcos or other even entities or corporates,
you don't make use of some of this data to actually be more
so-called granular in terms of offering more services or helping the users to be
more targeted in terms of understanding their own behavior, for example.
Yeah, right. Okay, that is great.
And do you already have some existing partnerships
in place for this, or is that something that you
would be actively working on?
Yeah, so the solution itself, we are currently
being used by 22 financial institutions.
There are some telcos as well as government agencies in different countries using it.
And I would say that what we want to do is to expand the reach beyond just the FIs and
the telcos and the government agencies.
Yeah.
Okay.
That's...
And is this... When you look at the solution, is this something that you
think you're primarily looking at the ACON region for it right now?
I think it depends on the data that we are refining or we're analyzing.
I think so far, based on the types of services that we're offering,
I think predominantly in developing countries,
because they have a huge population, that's number one.
And secondly, they have a lot more access to mobile phones
or even some services out there that they've been using and they're
more willing to share data and whatnot. So therefore, I think a lot more insights can
be gleaned out of those data. And at the same time, there's a lot more low hanging fruits in terms of
offering new services. Yeah. Yeah. Okay. That is again, that makes sense. So I guess like Branson and Jay, if you had
to like talk a little bit about what your ideal journey would be over the next two months
as you participate in this hackathon, what would it be? How would you like to sort of
be supported during the hackathon? What do you expect at the end of it? And yeah. Yeah. So you want to?
Yeah.
The reason we participate in the hackathon, also part of the reason is so we hope to have
gaining through the hackathon, we can gain more traction to know more people knows about
our insight or Insight Genesis. So let people aware through your hackathon.
And also we hope to win the hackathon
will help us the development work on the A1 chain.
This is what we achieve, the objective what we want to achieve in this.
And hopefully we can actually on-board using our chain to actually roll out our different AI solution on chains.
This is what we achieved.
We wanted to hope to achieve that.
Thanks.
That sounds good.
And out of curiosity, Branson and Jay Havit looked at,
what's your target market and what could it be like?
As in what's your total addressable market? how many transactions you think we can get on the chain and so on
and so forth.
So for the number of users, of course, we often I think we want to target at least 100,000
offhand, right?
So I think, of course, the more the merrier.
But I think most of the time, I think,
because all this data eventually,
depending on the chain that we work with,
again, pointing back to the fact that
L1X work with three different databases,
I think the question is, do we store all this data?
And when all this data is stored,
then with the analysis that we can glean out of this data,
then I will presume that there will be tons
of transactions happening on chain,
as well as the entities or even the corporates
who want to make use of some of these insights. Yeah. Got it. Okay. That is, that's great. So, so I guess like then a very open-ended question,
while you go through the hackathon, how would you like to be supported through, supported from,
what's the support you would be looking at from us, both from L1X as an entity and the L1X community?
entity and the L1X community. Curious to see what your thoughts are on that.
Curious to see what your thoughts are on that.
So I think for me, I think overall, I think for L1X, well first of all, obviously the technical
implementation of how do we get our project on this chain. And secondly, in terms of the ecosystem, of course, the users, the community for L1X
can help to at least try some of the services
that we have or our project at least and get on board.
At least give it a try.
Do the face scan, try the voice analysis,
and see how amazing, how quickly you can get a report actually
in 40 seconds.
So those are the things that we are looking at.
Awesome.
That sounds good.
I think that's something which would be very interesting
for the community.
And I'm sure they would love to try this out with you
and see where that takes them.
All right, so I think, you know, like this has been great.
This is what I believe a community,
they'll definitely get a lot of insights
on the project through this.
Is there anything else that Jay and Branson,
you would like to share with the community before we sign off?
you would like to share with the community
before we sign off?
I think thanks for having us. I think at the end of the day we want to work with the community
and we're more than happy to have you, L1X as well as the L1X community to come and
join us on this journey, you know. Go and try out our app.
And let us know how you look at some of the feedback
that you have.
Perfect.
And I think the community would definitely
want to learn more about the app and want to try it out.
So I think as we progress along this hackathon,
we will definitely share more of that information
with the community and do what we
can to promote the adoption of the app
and the usage of the app.
Oh, sounds good.
All right, thank you so much.
Thank you, Jay and Branson for your time
and for working with you in the hackathon.
Thank you, Rani.
You're welcome.
