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Building the FUTR: Real AI Agents, Real Data, Real Utility
Recorded: Dec. 4, 2025 Duration: 0:36:12Space Recording
Short Summary
Future Corporation is set to launch a new token that rewards users for their data contributions, while also expanding its services in the auto finance sector. With strategic partnerships and a growing user base, the company is positioned for significant growth in the Web3 landscape.
Full Transcription
Thank you. Thank you. Hey guys.
Perfect. Hey Alex, I can hear you now.
Excellent.
All right, and Joshua just popped in as well.
GM, GM, Alex, good to hear from you.
Hey, how you doing, man?
Good. Good to see you.
Good to see you too.
All right, is there an echo on my end? No, we're good, eh?
Josh, how's everything with you?
What's keeping you busy these days?
Yep, I think I got muted there, but like I said, going to wait a second to let folks pop in. Продолжение следует... Alex, where are you based?
Or region-wise?
I'm based in Toronto.
Okay. Awesome. Yeah based in Toronto. Okay.
Awesome. Yeah, right downtown. Awesome. I'm at Art Basel now, so I was able to find a quiet spot.
Nice. But I've seen some interesting folks come in from Canada.
Totally. No, and the joy of Canadian crypto is that it's extremely strong and powerful.
Like Ethereum was founded here. We do absolutely nothing in Canada, but then at Art Basel,
you know, we pop up for consensus or any of these things. There's a huge Canadian crew all the time,
just individual people working in their basements for gigantic projects,
but it's a really strong crypto community here. Yeah, I think Miami is the only place where like a quarter zip is not the right
Like I'm hot out here
Yeah, you gotta go yeah full full sleeveless no almost topless
Zipper awesome. We'll give it just a second then we'll go and get started cool
give it just a second, then we'll go ahead and get started.
Cool.
I think the last spaces I did was during a stellar conference
that was at a palace in Italy.
It's always fun to do these from a quiet place
somewhere around the action.
That's fine. Awesome. Awesome. So folks pop in. Let's go ahead and get started. So Alex, I'll give a quick intro for myself and then we'll have you intro.
intro for myself and then we'll have you intro um so hey guys i'm joshua howard uh senior
associate red beard ventures red beard we started off as a syndicate on angel list it's grown one
of the largest so currently has about 5 000 lps um on angel list and about 3 800 on echo so
approaching 9 000 total across our community Raised our first fund in 2022,
City Get Started in 2021. Core Web3 thesis on the fund, 25 mil fund,
raising fund two now at 50. And third for us is
Denari Labs, which is our tokenomics accelerator and consulting arm.
We're fortunate to be working with Future Network,
where we are also working with ecosystems
across Web3,
currently taking applications now
for cohort four of the
accelerator. So if you're a builder
out there or know builders
that are looking for world-class
tokenomics-specific
work, we're able to
help. So go ahead and apply.
If you're raising now, I'm able to support.
Okay, Alex, we'll have you intro yourself. Rock and roll. Yeah, so I'm Alex McDougall. I'm the
president of Future Corporation, the rare publicly traded company that's dabbling in this Web3
digital asset space. Myself, I'm a reformed former investment banker on the M&A side, but I left there in 2018 to
start a venture fund focused around blockchain and AI.
That was obviously before LLMs, before agents, before a lot of the functionality that exists
in blockchain today.
So, you know, we were a little bit shouting at the wind in terms of how you actually break
people into a new data model as compared to the Web3 Colossus, or the Web 2 Colossus,
rather, the Googles and Metas of the world, particularly around that time.
I've been building in the space for a while.
I ended up founding one of the first Canadian stablecoin companies out of Canada, working
with 3iQ on that side.
Canada Stable Corp.
We actually just got our stablecoin approved by the Canadian Securities Commission the last couple of weeks. So a big time builder in the payment rail space,
has spent a lot of time in the AI and blockchain space, and have been working on the Future
Corporation for the last year or so. So we've gone public, raised a decent amount of capital.
We've just started to get our heads around launching this token through our partners, the Future Foundation out of the Bahamas.
And we're very excited to bring it all together and talk about it today.
Awesome. Awesome.
So you guys have built a really compelling ecosystem around AI as well as essentially bridging Web 3 and Web 2.
So help us understand, what is the vision for FutureCorp?
You all have multiple product lines, whether it's the studio and other tools.
So help us see what do you guys look and solve?
Yeah, absolutely.
And I think I'll start where I started this kind of journey back in 2018. And there's this huge discrepancy of the way our data is used
and leveraged today versus, you know, kind of the optimal model. And we started our data journey,
you know, back with Google in the early 2000s of kind of a barter system, effectively,
for lack of a better term. You know, you had Lycos and Webcrawler and Ask Jeeves
and all of those kind of early search engines. And they just were not that great. And then Google
was the first one to say, hey, give me a little bit of your data and I will give you a materially
better product than what's out there. We were like, yes, sign me up, away we go. And we've
kind of had this barter system ever since where you click one button and all of your data goes into this black box and you get, you know, what is increasingly commoditized web services back in return.
And then recently, you know, ever since kind of the advent of consumer facing large language models, that data model has really gone on steroids, right?
We were starting to get to the end of, you know, the Google model.
It was a bunch of search engines out there.
It was what you were getting back was sort of more and more commoditized. The privacy lobby was starting
up. There's a bunch of better technology. And we've really kind of just put that data model
on steroids now with LLMs and sort of these more frontier models. So what we're trying to do with
future is really put that model a little bit on its head. So a bunch of what we're working on at its core
is really pulling all of your consumer data
into one self-sovereign vault,
so one place, one thing that you have control over,
you have the ownership of,
and you have basically the ability
to create a data supply chain.
So a bunch of that stuff does not matter unless you can deliver better functionality out of
that.
You saw that with DuckDuckGo and Brave and a bunch of those early privacy browsers that
couldn't out-compete Google.
The privacy side of that doesn't really matter unless you can deliver better functionality.
So what we're working on with Future is really ways to leverage this self-sovereign AI vault in a way that something like a chat GPT can't necessarily do because it's not built for one, it's built for billions.
It's a large, large, large language model built for a large user base and a large intelligence source.
a large user base and a large intelligence source.
So when we think about what we're trying to accomplish with Future
is really taking that data, putting it all in one place,
and using that to drive better outcomes.
So, for example, a specific example of that,
ChatGPT will not be able to go and find you an insurance policy
that's perfectly tailored for your specific car.
It won't be able to go and make loan optimization payments on your
car loan for you. It won't be able to go and take the payment that you just made for your rent and
go and report it to an Equifax and generate credit for you. So it's not designed to sort of take those
actions. So when we bring it all together, and I think you talked about future network, future payments, future data, all of that stuff.
It really is creating an agent that actually does stuff for you, that keeps your data in one isolated place and gives you control of it.
So using sort of this customized AI technology in order to generate that single place of truth and single source of truth that allows you to create what we call high-fidelity AI.
And then ultimately, the biggest change in this model is for years and years and years,
we've sort of just given our data away.
Future actually rewards you for every piece of data that goes into this ecosystem.
So every piece of data that goes in gets allocated a token value.
We have a really cool data valuation model,
and you're earning those in tokens
right within a Web3 wallet
that's baked right into the app
and it's all connected in something
that looks cool, feels cool,
and is super seamless.
So to sum all that up,
we're trying to do three things.
One, actually make an agent
that can do stuff for you
in a way that ChatGPT
can more tell you things.
And there's a lot of functionality
in ChatGPT that's great.
We're looking to take that
all a layer further.
Second is using customized AI products built around one, not around billions.
So keeping your data safe, creating your data supply chain, and really helping you to create
that value.
And then three, we're rewarding you for every piece of data that goes into it in a way that
just the general frontier models and the more Web 2 world just absolutely
does not do.
So those are kind of the three key things that we're trying to tackle and solve for
people.
I love that.
I love that.
And that was a really clear explanation.
So I want to piggyback off of that.
So when you think about what agents need, right, there's been a ton of AI, there's been
an AI wave in Web 3 where folks have been looking at the problems of AI and agents and how to monetize them, how to enable them to make money, the whole nine.
When you guys think about agents at FutureCorp, you know, where are the problems you all see both in Web2 and Web3 that agents need help with?
Or how do you all think about improving agents and products you're building?
Yeah, absolutely.
And I think you're not going to solve this data problem
and you're not going to solve this agent problem
with kind of the focusing on privacy
and focusing on that self-sovereignty layer.
People just don't care.
You need to solve it based on utility.
And so when we have agents today, I always think about it as, I read a wonderful quote a couple
years ago that really helped to put in perspective kind of the current AI model. It's not having one
really smart person working for you. It's like having a hundred really dumb people working for
you. Great horsepower, a lot of cool stuff can come out of
it, you can do a ton of work with it. But in current world, you're relying on sort of these
subjective AI models that don't have this high fidelity, you're not going to trust it to make
your mortgage payments for you. Sometimes they can't even remember the name of a character from
the start of the story to the end of it. And so it's which is fine for, you know, squishy, broader research base, not, you know, doesn't need to be perfectly accurate. But it's
not fine when, you know, in our case for financial use cases, we just brought on an advisor, one of
the leading high reliability systems, AI designers in the world, Damien Fossard. So he was building
AI for Boeing and for NASA and Airbus.
And when you're having AI systems fly planes, that's an even higher fidelity.
Like there's 0.00000000 at infinitum level of hallucinations or challenges or mistakes that are able to be done through those types of structures.
types of structures. So when we think about kind of the current agents of the world,
a lot of them are based on these either way too large and broad data sets or incomplete data sets
or aggregated and anonymized data sets or only public markets data sets. They're not based on
this kind of zero party data that's fully validated and voluntarily contributed and held in a container that's designed for individualized AI.
So that's really, I think, what is missing from getting to that next wave of beyond novelty
function. I'll trust a chat GPT-based AI browser to order me food, but I won't trust it to make a
mortgage payment for me. I won't, and even more so won't trust it to fly a plane for me.
So I think really what we're trying to do is flip around that data model whereby people are
incentivized and trusting that the data is going into a container that they own and control.
And by doing that, we kind of unlock that supercharged value proposition of, oh shit,
okay, I will actually trust this thing to make my mortgage payments because I can audit the data that's going into it. I can audit the outcomes. And I have
trust in that in that comprehensive supply chain of data that's getting me to these places.
So but all of that needs to look cool, feel cool, be delivered in a cool, easy, simple way.
You know, it's almost like a AI mullet that we kind of think about it, you know, like the DeFi
mullet, but a little bit more modern version of it, where it's simple and easy at the front, but there's a ton of complex
transactions and a ton of complex technology that sort of sit behind it. And I think to get to that
real financial utility, which is where a lot of these agents today fall flat, you need to have
that better data model, you need to have that better technology, you need to have all that
flowing locks of goodness that are hidden behind the head there.
Love it. Love it. So I want to switch gears
here to something that's super exciting for you guys. You all just acquired Hank
Payments, and I can imagine that
creates a bunch of new capabilities for you all. So help us understand
what's exciting there,
how's it going, and how does it bring new capabilities and new strengths to the future?
Yeah, absolutely. So we did that acquisition actually back in February of this year.
So, and it's a key part of our strategy. And look, we've all been in Web3 long enough to know that Web3 is long, very long on unbelievable ideas and unbelievable
technology and short on adoption volume use cases and real financial value transacting
through it.
So within Web3, there's great examples of high throughput use case.
And we've started to see it really in stable coins.
And there's a bunch of obviously green shoots on that side. But one of the things that we were really passionate about
when we started building this project is let's build backwards. Let's find where people are,
what financial transactions people are doing, where money is flowing, where there's value that
we can really make that's tangible, and then work backwards to see where can we layer in Web3,
where can we really make crypto supercharge this
platform instead of the other way around and starting with the deep part of Web3 tech and
building out for use cases. And obviously, again, we have built a lot of the deep Web3 technology,
but we're really starting and trying to find from where people are today. So with that in mind,
when we did this transaction
for what was Hank Payments now Future Payments,
and we just announced Future Payments 2.0,
which has just a massive upgrade in technology,
it was really around, okay,
here's a great proto AI agent use case
that this existing public company Hank is doing.
You show up with your auto loan,
the agent or the engine reads it and says,
hey, here's how the bank wants the engine reads it and says, hey,
here's how the bank wants you to pay it, which is once a month over five years, you pay this
much in interest, don't think too hard about it. I've read your document. So the agent's reading
your actual loan document. Here's how you should be paying it, which is let's break up your payments
and move them a little bit earlier. And there's a prepayment clause in here that nobody reads
because nobody actually reads contracts.
And we should be scraping out a little bit and saving so you can hit that prepayment clause.
If you do all this, you'll save $2,000 in interest on your loan, and you can get out of your loan seven months faster than if you just paid it monthly.
So ChatGPT can tell you a lot of that stuff, although it's kind of bad at math, but it
can tell you a lot of that stuff.
The real difference here that is the real kind of value proposition, a lot of the stuff that we added to the Hank
Payments platform is a giant glowing red button that says, go and do this for me. So now with all
of these, you know, with all of this connective fabric that we've added, you know, AI and AI
agents to this existing payments rail, you know, we're working with 1,500 banks in the US.
We're paying off 900 lenders right now. We've run $3 billion of transactions through that
financial rail. We saved people $18 million in interest just over the last 12 months alone.
We're generating customers from 250 auto dealers as of today, and then we just signed a deal to
increase that by 400% as well. So we're bringing in a ton of real usage to what is a very simple prototype of an AI agent use case,
and then scaling and layering on a ton of technology to it. So when you think about
kind of the merger and what the strategic rationale and value for it is, we took a great
set of AI technology, and then we plugged in a use case by buying it. And it's worked out
unbelievably well.
So revenue's up. We just hit a record on revenue on that side. The tech advance that we just
announced has gone over really, really well. We're signing a bunch of new deals to grow at
that distribution footprint. And then that's a big part of our strategy going forward. There's
all kinds of single service or single utility. Hey, can you guys hear me?
Yeah. Yep. You good, Josh? Yes can you guys hear me yeah yep you good Josh yes
can you hear me yep yeah yeah okay okay oh go ahead no worries I'll keep going so
there's all kinds of these types of platforms out there that you know have a
couple million bucks in revenue a a couple hundred thousand users, have a single utility that they're focused on, that aren't really maximizing their data and
are ripe to be plugged into an AI agent driven ecosystem where you can optimize the tech,
cross sell to a whole bunch of different solutions, take all the data from that and put it back in the
hands of the user, reward them for it, and just totally modernize all of these functions. So that's a big part of our growth strategy going forward is looking at
what services and solutions can we deliver through this agent, find somebody who's doing that right
now, add them to the public company, totally revamp the tech stack, and just drive all of
that on steroids. And then all of that value kind of flows down to the token, which we can
talk about in a minute as well.
But it's a huge part of our growth strategy where we've been very happy with that transaction.
It's really sort of launched the company from an ideas-based company to a company with $8 million in revenue and a publicly traded company, which, again, is just not that commonly seen in Web3 land.
That's great.
That's great.
And I think to that token now, so you guys are developing sort of value prop on the token
and all that.
What are you guys thinking right now and how far along are you?
Extremely far along.
So I'd say the value prop of the token has been crystallized for a while.
But the way we're really thinking about it is the loan optimization that I talked about before.
We signed a rent reporting deal.
We signed some insurance deals.
There's a bunch of stuff that sort of generates core, simple cash revenue for us as a business.
Underlying all of that is this data model that we started out the conversation talking about, which is every time you engage with a service,
every time you make a payment, every time you ask a question, every time you upload a document,
all of that creates this incredibly rich and robust consumer profile that accrues to you.
And so you're getting paid for all of that data using the future token. So it accrues, again,
to your wallet that's baked right into the application. We have an awesome data valuation model. They lead data scientists from Manulife. We took a year to recruit him, but he's joined the team and helped us build that out.
And so there's a really good reward side of the house for this is how we're rewarding consumers for their data that comes in. On the flip side of that is the demand side. And this is where there's a really cool vein of conversation that's happening right now around intent monetization, where traditionally, if you are a brand, you're sponsoring keywords on Google, you're putting up banner ads, you're putting up billboards beside the gardener in Toronto. And you're trying all of these various
ways to go about and tell a story to find your users. What we're seeing, and so the Nier Protocol
is working on this, there's a few others that are as well. And what we're really operationalizing
here is this idea of intent monetization, where a really rich, robust, self-sovereign data set can actually
surface agentically intents of what's needed, what's going to happen. So an example back to
the insurance side for a minute, and I'll get back to the token in a sec as it relates to all of this.
The intent of, okay, I have put my data in. It knows when my insurance policy expires. It knows
what kind of car that I have currently.
It knows where I live, what my driving record is, the payments that I've made, all of that stuff.
And so there's an extremely valuable nugget of intent there.
And so an insurance company that's used to sort of spray and praying and making funny duck mascots to try and get some level of attention.
duck mascots to try and get some level of attention. Now what they can do instead is
work with us and develop a offer around specifically that intent and monetize on that and make their
offer able to be presented through our agent, make their offer able to be digested and sent
and totally personalized to the person that's behind that data set and go from a broad spray and pray approach into a hyper
personalized approach. And obviously, in the banner ad world, you're in cents per click and
you're in these tiny conversion rates and some customized lead generation is slightly better.
With intent monetization, you're in a completely different stratosphere of digital advertising.
So again, you're getting these hyper personalized,ized, high-intent, zero-party data leads that are, for premium financial services, worth hundreds of dollars instead of cents per click.
So when we turn that on the other side, and remember, we're rewarding all of our users with tokens for putting data into this.
On the other side, anybody who wants to work with these intents and monetize these intents needs to buy that advertising space or buy that
offer space with tokens. So obviously, we're doing as a publicly traded company, we're doing a lot of
the abstraction work. So we're not going to go to Geico and say, hey, go to Binance and buy a bunch
of tokens. But the fundamental economic model that sits behind it is brands are not paying for advertisements and for offers and lead generation in cash.
They are paying in token.
So we have this two sided marketplace where we're rewarding people for data on one side and then brands on the other side are paying in tokens to actually engage with that type of data.
And we as futures, the platform basically act as a market maker, as a marketplace in between.
We're able to collect
a commission on the publicly traded company side. So it's totally transparent how all of these
economics fit together and how both sides of that work. But that's kind of the value proposition of
the token in a nutshell. It's a fixed issuance. So there's $5 billion at launch. And then as brands
redeem in order to access these intents, 5% of that is burned.
So it'll end up with a $4 billion token supply.
And as there's more and more and more and more and more users on the platform, then there's more and more and more demand from brands for accessing those intents and those users.
So it creates some nice fundamentals for the token as well.
Awesome. Awesome.
Awesome.
Okay, guys, if there is a question popping up, go ahead and raise your hand.
I'll ask a final couple of questions. Josh, you're on mute if you're trying to dig in.
Okay.
Josh, can you all hear me?
Yep.
Great.
Okay.
So, as mentioned, if there are questions, go ahead and raise your hand.
I'll go ahead and ask a couple questions to end here, but if there's a question, go ahead and raise it.
We'll make some time to answer.
So, Alex, as mentioned, you guys are a public traded corporation.
So, I think what's most exciting about Future is sort of what's next for you guys.
So, we'd love to understand, one, being in that position, it probably makes it a
lot easier to go do BD, et cetera. But also you are being token forward and taking some of the
revenues and supporting the token. So we'd love to understand what's exciting next for you guys
on categories that you think this market or the marketplace
you all built can really apply so is it insurance or continuing in payments maybe
exploring stable coins what gets you all excited yeah absolutely I'll take that
question in two directions so we we currently have 45,000 users optimizing
their auto loans on the platform, which provides an incredibly rich set
of data to start for diversifying that. So when we think about intent monetization and the brand
side of the house, auto insurance is a wonderfully natural evolution of that. We have a lot of auto
details from that loan optimization use case. And so creating kind of an initial consumer profile
that forms an incredible insurance lead
is a bit of a no-brainer.
So, and expanding more into that,
auto refinancing as well.
You know, if you borrowed at 20%
and you've made 15 payments in a row,
you're likely eligible to refi at a lower rate.
And vice versa, if you've NSF'd on a couple in a row,
potentially there's an opportunity to add some term and reduce that payment. And so that type
of business logic is perfectly suited to the existing usage and the existing use cases that
we have. And auto is such a rich vein, especially in the US. We currently penetrate less than 1%.
We've just signed this distribution to grow that by 400%.
But with the tech that we've built,
we have actual data connectivity to about 70% of the U.S. auto market.
So the footprint is really, really robust
and somewhere that we can get a lot of penetration.
So we're very, very excited about just the growth in the auto space.
And then I'll switch gears a little bit
and sort of talk about the back of the house,
where we're doing a ton of work on this concept of high fidelity AI, which is really taking AI from this subjective, I hope this is right, to the Airbus use case of this is absolutely 100% correct.
And there's no margin for error.
And so a lot of that is around using the right type of technology.
We use a lot of Snowflake.
But also starting to add in more and more and more Web3 pieces to that.
So whether that's turning this data into an Oracle, whether that's working with ZKs
and really sort of doubling down or tripling down on the privacy side of that and the
zero-knowledge access.
There we go.
Can you guys hear me again?
Great.
So just doubling and tripling down
on kind of the web three native stuff around this.
And that includes on the functionality and use case side.
So I think we're looking to really drive home
the value proposition in the auto space.
And there's a lot of other places that we can take that,
but then really triple down on the Web3 side
and where can we generate tangible value
by leveraging existing Web3.
We're built on the base ecosystem right now
to playing a lot in that space as well.
Love it, love it.
Okay, I think we have a question from the cat.
Yeah. So I just wanted to know how long you guys have actually been around in building this?
Yeah, absolutely. Great question. So we did the merger that sort of kicked off the company in
February of this year. So we raised about 1111 million in equity financing through the capital market since then.
So we've been building out the AI components and building out the agent components roughly since then.
So the agent app itself right now is in closed beta.
You know, happy to reach out to me, ping me wherever.
We'll get you into the app.
The core underlying payments technology that's run $3 billion through it, that's been around since 2017, but really has been drastically revamped over the last nine months and culminating in the release of 2.0 that we did a couple of weeks ago.
So the bones of the company have been around for a little while.
The core of this version of the company has been around for about nine months.
And then we're just putting a lot of this stuff out into the world and getting it fully on the rails.
But the core of it's been around for a while.
Okay, so...
I think we lost you there.
Are you... The cat? Can you hear us?
Okay. He may have been, audio may have cut out. Okay. So Alex, final question here,
any updates or things on the horizon? Yeah, absolutely. So, you know, there's,
or things on the horizon?
Yeah, absolutely.
So, you know, there is, as a public company,
we're a little bit more limited in what we could sort of guide towards
or say on that side.
But the Web3 roadmap is going to get a lot more light shone on it
and some of the deeper tech and some of the deeper infrastructure
around this kind of high-fidelity AI structure
is going to get a lot more airtime and a lot more discussion.
The deeper part of this intent monetization and sort of how we're leveraging this data,
how we're accruing it to the user, how we're rewarding the user,
and then how we're creating the infrastructure for brands to engage with those intents
is going to get a lot more airtime as well.
And we're constantly bringing in new partnerships, new deals, new brands,
new potential acquisitions that all kind of grow and accrue to the user count,
the amount of volume that's transacted on the platform, the revenue side,
and then ultimately a lot of that accrues back down to the token.
So stay tuned for a lot of those strategic announcements coming up through those veins.
But really, you can start, you'll be able to start monitoring us and see it on chain
in the not too distant future, as well as the closed beta grows and the token starts
to get more broadly distributed.
Okay, awesome. And where can folks keep up with, uh, future?
Yes. So the future corp.com, uh, you can follow me on Twitter.
You can follow me on LinkedIn. I can follow at the future corp, um,
Twitter as well. Uh, and you follow us on, on LinkedIn.
Okay. Awesome. Alex, this was great. Good hearing from you, my man.
Awesome. Thanks, guys.
Bye.
Okay. Thank you.
