August 7, 2025 • 30 mins
KraneShares’ Derek Yan joins me on Lead-Lag Live to break down the only U.S.-listed ETF that owns equity in private AI giants like X.AI and Anthropic — in partnership with REX Shares.
This isn't just another tech fund. $AGIX is built for the AI age — giving investors rare exposure to the companies powering artificial general intelligence (AGI), including OpenAI rivals that may never hit public markets.
We dive into:
- Why KraneShares is betting on AGI as the next major tech supercycle
- What sets X.AI and Anthropic apart from other AI players
- How KraneShares built a structure to hold private equity inside a 40 Act ETF
- What the AI Score reveals about the next winners in public markets
- Why the next AI boom might happen in applications — not just chips
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
We're planning to really launch an ETF that
captures the company that'sgoing to take the world to
artificial general intelligence.
We think that's AGI.
So that's why we launched AGI X.
We truly value our partnershipwith Ethna Capital because they
are early investors to a lot ofthose AI companies.
Speaker 2 (00:34):
Hello and welcome back to another episode of
LeadLeg Live.
I'm your host, melanie Schaefer, head of Media Strategy and
Business Development at LeadLagMedia, and your host.
As some of you know, I recentlytook over from Michael Guyad,
the founder of LeadLag, and I'mexcited to keep bringing you the
kind of bold, insightfulconversations that matter to
(00:55):
investors right now, especiallyin fast-moving spaces like AI.
Joining me today is Derek Yan,head of Strategy at CraneShares,
where we're going to dive deepinto AGI-X, the first US-listed
ETF to give direct exposure tomajor private AI players like
XAI and Anthropic.
(01:15):
Derek, thanks so much for beinghere today.
Thank you for having me.
Gix is getting a lot ofattention.
It's the first ETF in the US toinvest directly in private AI
giants.
I mean like it's a bold move,but what gave your team the
confidence to build somethingthat's this different?
Speaker 1 (01:33):
Yeah, sure, I mean like looking like back two years
ago, when AI is really liketaking a storm, right, Like
everybody's like shocked on howgood like ChatGPT is really
changing the way people likecommunicate or generating
content.
So we're thinking about likewe're planning to really launch
(01:55):
an ETF that capture the companythat's going to take the world
to artificial generalintelligence.
We think that's AGI.
So that's why we launched AGI-X.
But a challenge we face is,back then there's so many
companies that is critical forAGI are still in the private
(02:18):
stage Talking about like OpenAI,Anthropic and later I mean XAI.
So those foundational modelcompanies are really driving
this round of innovation in thegenerative AI.
So without adding thosecompanies, you end up have kind
(02:40):
of like quite a similar exposurecompared to, say, NASDAQ 100 or
just technology sector ETF,right.
So we're thinking about why notcreate a fund that captures the
whole ecosystem, regardless oftheir liquidity profile?
So that's the ideal we had.
(03:01):
But like then like it'sdifficult, right.
So then we ask the lawyer whatwe can do.
The lawyer is like yeah,actually, ETF, end of day, is a
40-act fund.
So in the 40-act fund actuallyyou can include up to 15% of the
private assets.
So that's OK.
(03:22):
That's interesting.
Assets so that's okay, that'sinteresting.
15% is not a lot, but itactually is decent when it comes
to a portfolio of AI company.
Think about there's so many AIopportunity in the public space
and also in the private space,so 15% actually is a decent
allocation that we can allocateto those private AI companies.
(03:44):
So fast forward to today.
We actually really completethis portfolio by adding XAI and
Anthropic into the AGIX ETF.
So those two companies now arein the top 10 holdings of the
ETF, together with other publicAI companies.
(04:05):
So this is one interestingsolution now just offering the
old AI companies, regardlessthey're public or private, and
have a solution to reallyachieve that goal.
Speaker 2 (04:17):
Yeah, so I wanted to dig into that just a little bit
deeper and follow up on that,Like talking just about sort of
maybe XAI and Anthropic inparticular, what are these
companies that were?
And the other private companieswithin the fund?
What are they doing and why dothey matter so much in the AI
race?
Speaker 1 (04:32):
Yeah, if you think about like how this round of AI
is really changing the world wehave, I mean like think about AI
is really.
Think about like there'sseveral rounds of technology
breakthrough right.
There's like the old days, likethis PC, then internet was
thing, the mobile internet right.
(04:53):
Then I think like cloud, becomelike all those apps and it's
now going to cloud and startingfrom like two or three years ago
, we think generative AI isreally changing the technology
sector, changing the innovation.
That's going to create asimilar opportunity like the
previous generations oftechnology breakthrough or
(05:17):
innovation breakthrough, andthis round of really development
is really driven by the AIlarge language model companies.
So those large language modelcompanies they train like tons
of data and they can generatecontent, they can have
intelligence, that power, theability for those models to do a
(05:41):
lot of work right, like contentgeneration.
There's calculation, codegeneration, so anything like
related to code or in thedigital world can be automated.
That's really come to clientservices, come to a lot of like
I think, white collar jobs inthe enterprise world.
(06:02):
So that is a game changer for alot of enterprises and
consumers to really automate thewhole digital world.
So that's a big opportunity andthe company is critical.
I would think about it in theconsumer side, it's OpenAI,
which is probably the mostfamous one.
That's what everybody's nowusing, but actually in the
(06:25):
enterprise world, anthropic is abig player that many
enterprises is actually usingAnthropic's API.
Anthropic also has aconsumer-facing app called Cloud
AI.
It's famous for its cloud model, mostly on the, say, legal side
or coding side, not engineeringside.
(06:48):
So that is something I think,like many insiders in the tech
world or engineering world orlaw firm, is usually like using
cloud.
But I think, most importantly,the coding is a big thing,
vertical for the AI adoption andAnthropics really leading in
(07:12):
that section by partnering witha lot of application companies.
So I mean there's a lot of likeautonomous coding right now
using the Anthropix API.
Xai is another large-slang modelcompany founded by Elon Musk
right With its unique access tothe data from the social media
(07:35):
platform X.
So XAI is actually like a verypowerful model with, I think,
access right Because Elon Muskhas bought a lot of the GPU and
built a large data center.
That's powering the modelbehind XAI and XAI becoming the
(07:56):
most, currently the mostintelligent large-dash model so
far.
That gives them the edge bothin the consumer side and the
enterprise side.
So if you think about like thiscompetition right of AGI, like
everybody's now trying toachieve artificial general
(08:16):
intelligence in 10 years, 20years, it's still at an early
stage.
We don't know if OpenAI,anthropical, xai, which one's
going to be probably the AGIcompanies in the future, we were
thinking about just adding moreof those, like in the future.
So we were thinking about likejust adding more of those names
in the portfolio.
(08:36):
It's really like you don't wantto miss any of them.
What if, like, anthropi becomethe solution where XAI become
the solution?
So adding those companies,those foundational model
companies, in the portfolio ispretty critical.
If you think about Asia iscoming in a decade or two
decades.
Speaker 2 (08:57):
And I guess to follow that up as well.
I wanted to talk a little bitmore about the future of your
allocation strategy.
I mean, do you expect that themix between private and public
companies is going to change asthe more public companies mature
, and I mean especially with somany of them trading at
multiples?
Speaker 1 (09:15):
Yeah, exactly, I mean , when we added those private
companies, so we added theirprimary round, right, so
Anthropic, we entered theirfinancing round of Series E.
So that's like they're going todo multiple financing going
forward.
They may IPO in the future.
So once they IPO, they becomelike public companies.
(09:39):
So there's, I think, eventuallya lot of those private AI
companies going to be public.
So then we're going to see likehow this portfolio going to
evolve right in the future.
Because, yeah, then I thinklike currently a lot of the.
Then we're going to see likehow this portfolio is going to
evolve right in the futurebecause, yeah, then I think like
currently a lot of the thoselike high valuation companies
(10:01):
are really the foundationalmodel companies or
large-net-share model company,like OpenAI, like Anthropic,
like XAI, with like a hundredbillions or 300 billions
valuation.
So it's already like a latestage for them to really become
IPO in a stage.
(10:22):
Then I think at that time whenthose companies IPO, our focus
in the private side is probablygoing to more on the application
side.
So we actually, on our phone,we want to capture the three
layers of the AI opportunities.
One is the hardware right, likethose chip company or data
(10:44):
center related company tobuilding the hardware for the
large selection models.
And then there's infrastructurelayer.
You have cloud, you have datasecurity, data preparation,
model preparation and then themodel company themselves in the
private side.
So they are private side now.
Then when they become public, Ithink a lot of opportunities now
(11:08):
in the third layer, theapplication side.
We currently we do have a lotof application side company that
is public.
But I think like when thecomputing power of the
large-next model, when thecapability of large-next model
becomes so powerful, there willbe like tons of new application
(11:31):
companies coming up.
There will be like tons of newapplication companies coming up.
So we see, currently there'sseveral like, I think, popular
one including, say, proplacity,or many in the content creation
or like digital media.
So there's so many applicationsright now.
Even the physical AI side,right when people are now using
(11:51):
the data in the physical worldto do automation in the factory,
automation of robotics, thoseare really like future
opportunities that we canconsider in the private side to
maintain a decent exposure intothe private application to the
CTF.
Speaker 2 (12:08):
What about the AI score?
Can you talk a little bit aboutthat?
How does it differ from atraditional tech index sort of
approach?
Speaker 1 (12:17):
Yeah, so I forgot to mention.
So for AGIX, we have a partnercalled Aetna Capital Management.
So they're a venture capitalfirm that they're an investor of
the company, like XAI Anthropic, that they are early investor
of the company like XAIAnthropic.
So with their early connectionwith the company, we are able to
(12:38):
access those deal.
So that's the kind of like howwe source the deal.
So also with them, we give backlike AI score together.
Because when we look at this,the traditional index
methodology to really capturethe AI companies is either based
(12:59):
on revenue or is based oncertain, say, keyword searching
or document searching.
We don't think that's a verygood way to really capture the
AI companies.
We don't think that's a verygood way to really play this
capture the AI companies.
(13:20):
Because we really need to lookat way that, how large-slash
model, how Gen AI is changingthe business model across all
those technology companies.
Think about it right now, everycompany claim to be an AI
company, even like AT&T or likeall the other companies now is
(13:40):
using AI.
So how do you really evaluatethe impact of AI?
So that's why we partner withAetna Capital Group.
They have a committee andtogether with their committee,
with our index provider.
We developed like anindex-based methodology to
(14:01):
incorporating those AI score toevaluate the readiness and
relevance of AI for each company.
So we look at current revenueexposure for that company that
is exposed to Gen AI and also welook at their business model,
how this business model is goingto be impacted positively by
(14:26):
the Gen AI.
So with those two angles wecaptured the I think, the right
company that's really going tobe AI beneficiaries.
Speaker 2 (14:37):
Now, Derek, I want to talk a little bit about the
performance of the fund.
I mean, as you said, a coupleof years old and AGX has already
outpaced some major techbenchmarks.
What do you think is drivingthe outperformance?
Speaker 1 (14:50):
Yeah.
So I mean, when we look at theperformance of AGX since
inception, it has largelyoutperformed the broader
technology or growth indexes,for example NASDAQ 100 or just
technology sector index orsemiconductor index, technology
(15:10):
sector index or semiconductorindex.
I think the AI score is reallycreating a comprehensive way to
evaluate the long-term AIbeneficiaries right.
So that framework is actuallyadding a lot of outperformance
since our inception Because whenwe look at like there's several
(15:31):
rotation happening right, likeI think at the early stage
there's a lot of value justreally creating in the AI
hardware space.
Like NVIDIA is definitely thebiggest beneficiary in that
there's a lot of data centersbeing built out, there's a lot
of energy cooling and water.
Those companies, as you said,it's going to be a benefit.
(15:53):
We do have those companies asthe AI scores were high at this
stage when we launched ETF andgradually we realized the value
is migrating to theinfrastructure and application
companies so along the time thescore for the infrastructure and
(16:16):
application company become muchhigher.
For example, we are the earlyinvestor of company, for example
, palantir and Duolingo.
That's a perfect example of howthe AI is used right in both
the enterprise world and theconsumer side.
For Palantir, they are a leaderin the, I would say like
(16:41):
creating an operating system forenterprises to use AI, and we
realized their AI score is veryhigh and we're including them
just before even NASDAQ index.
Including the Palantir andDuolingo is another interesting
example.
Most people know the firm forits language learning, but when
(17:05):
we look at how their businessmodel is going to benefit from
AI, they just have very goodpotential and we have validated
their technology to incorporateAI in the language learning and
the result is very impressive.
So with that framework werealized there's application
(17:25):
companies is actually adding alot of performance to the AGI-X
ETF as well.
Yeah, so that framework isreally creating a thing like
long-term framework to establisha portfolio that captured the
value, gradually migrating fromhardware to infrastructure and
(17:49):
application, and I would thinkprivate companies are going to
add in some performance goingforward.
Because those companies are notpublic, so they don't have a
daily price, so it's not tradedon any exchange right now.
(18:11):
So how do we really?
I think like it's interesting.
A lot of people ask us so if youhave, like Axia and Anthropic,
how are you going to value those?
So, because ETF is is a dailyoffer, daily liquidity for any
investors, anyone can buy AJAXETF with their brokerage account
(18:32):
.
So that means we have to offerdata liquidity and then we
actually value those privatecompanies at a daily basis based
on all the information,including their primary round
valuation, including theirsecondary market transactions.
So we just included the AXArecently and we included
(18:56):
Anthropic earlier this year.
I think both companies arereally growing very strong in
their revenue stage.
So I'm sure, like with the NASfinancing round coming or just
like going forward if the IPO,they're going to add a lot of
value to agx investors yeah,with the structure of the fund,
though, like I mean, the fundactually owns equity and xai and
(19:18):
anthropic correct yes, so, uh,actually we own where agx uh uh
sit on the cap table of both xaiand anthropic uh, so it's a
shareholder of the two companies.
So that's like direct ownershipcompared to owning them via
(19:38):
another structure.
So it's very simple.
We like that simplicity.
I think that's like mosttransparent way to invest in
those two companies and ourinvestor really loved that way,
compared to there's many other,I think, retail trading platform
or like a very complicatedstructure to invest in those
(20:01):
companies compared to AGX, whichis like simply directly owning
those shares.
Speaker 2 (20:07):
Yeah, it's quite rare and I know fair valuation is
something investors worry aboutquite a bit.
I know fair valuation issomething investors worry about
quite a bit, you know,especially with private equity
and with the liquidity in ETFs.
Can you explain how CraneShareshandles pricing for the private
side of the portfolio and whatsystems are in place to make
sure that it's accurate and hasthe investor money first?
Speaker 1 (20:28):
Yeah.
So first of all, thosecompanies are not really a
startup.
So for startup there's like awide range of what is the fair
value right for those companies.
But the company we invested aremostly the late stage large cap
technology companies, right.
(20:49):
So if you think about thevaluation of those foundational
model companies, they'rehundreds of billions and now the
companies are staying in theprivate longer.
So there's a decent number ofinvestors actually now trading
in the secondary market forthose companies.
So we actually use a lot ofthird-party data provider to
(21:15):
really gather those transactiondata happen in the secondary
market and there's a lot ofinformation we can use to really
have a best practice to have adaily fair value committee and
daily fair value process toincorporate all the available
information that deliver thedaily value for those private
(21:40):
companies.
So that's why AGX, as ETF canprovide daily liquidity to all
investors that want to invest inthose companies.
Speaker 2 (21:50):
I'm not sure I think you touched on it, but the fund
supports financing rounds forthese private companies as well,
which is a new dynamic for theETF world.
How does that relationship workin practice and what kind of
access does that give youcompared to traditional ETF
models?
Speaker 1 (22:06):
Yeah, it's really actually because those companies
are.
I mean, everybody's likechasing those companies right.
So it's really actually becausethose companies are I'm like
everybody's like chasing thosecompanies right.
So it's really hard.
That's why we truly value ourpartnership with Aetna Capital.
They have because they areearly investor to a lot of those
(22:28):
AI companies.
By the way, I forgot to mentionAtmar Capital was founded by AI
native engineers and earlyinvestors, so themselves have a
decent network among the AIresearchers and engineers across
those Gen AI companies and AIapplication companies.
(22:50):
So that's why I have a closerelationship with the company.
It's very important becauseusually now it's over-subscribed
for any round of financing,given how popular those
companies are at this stage.
So getting access through thisconnection and with the help of
(23:13):
theetna team is very important.
And we actually, when welaunched AGX, we invited both, I
think, anthropic and Proclacityteam to join our fair reigning
on the NASDAQ exchange and wedid a panel discussion with them
(23:33):
to talk about the future of GenAI.
So we're going to keep doingthat, with the close
relationship with the companyand with their engineering team,
research team, to really buildthis network and ecosystem for
the AGI.
I think that's kind of like theapproach we're going to do.
(23:55):
We're going to maintain a goodrelationship with the company
themselves.
So in the future, if there'sanother round of financing or
tender offer, we're able toreally participate.
Speaker 2 (24:06):
And so are there more private names coming in the
future.
Can you talk a bit about thatat all?
Speaker 1 (24:10):
Yeah, I mean like there's a lot of companies we're
engaging, that's in thepipeline.
There's a lot of like excitingopportunity, I think, both in
the financial model round sorry,foundational model round and
also a lot of applicationcompanies we're talking right
now.
But because this is still, Ithink, like when you have this
(24:33):
conversation, when you haven'treally made the deal, you cannot
announce that, unfortunately.
But I would say, like investors, please follow Cranesharescom,
slash AGIX for more announcementgoing forward.
So just stay in tune.
Speaker 2 (24:51):
Yeah, derek, and you have other funds as well.
Can you talk a little bit aboutthose just more in general, and
do you have any new products onthe horizon?
Speaker 1 (25:01):
Yeah, actually we recently launched a
humanoid-focused ETF calledK-O-I-D Koid.
We think, like when we launchedAGIX, we think like Gen AI is
really exciting and it'sphenomenal, so what could be
(25:22):
like kind of like nest Gen AI?
So when we also, like we werewatching, like the CEO of Nvidia
, jensen Huang, his keynote atthe GTC conference I think he
mentioned that the robotics,especially humanoid robotics,
can be, could be the next bigthing the traditional AI to
(25:43):
generative AI to AI agent, wherea lot of AI apps can really
autonomously get a lot of thingsdown, in the future it could be
happening in the physical world.
So physical AI is kind of thenext big opportunity.
(26:05):
So that's why we launchedKO-O-I-D recently to really
capture the humanoid opportunity.
Actually we bring a realhumanoid.
There's a company calledRoboStore based in Long Island,
new York.
They're a distributor of thehumanoid robotics.
(26:28):
I was there at their warehousein Long Island.
It's like a dream come true.
Like there's robotics, like therobots are everywhere that can
move and run like very smooth.
So seeing that, I mean sincebelieving the technology
breakthrough in the hardware isreally at a stage, I think like
(26:50):
making humanoid and that's bigpotential for a lot of
applications.
And AI is bringing theintelligence to those humanoid
robotics, so that's why wecreated a KOID to really capture
that opportunity.
Speaker 2 (27:07):
And there's a great picture of the humanoid robot
ringing the bell at the stockexchange on your website that
people can go and look at.
Derek, it's been so greathaving you here.
Speaker 1 (27:17):
Thank you very much.
Thank you for having me.
Speaker 2 (27:19):
I'm Melanie Schaefer and we'll see you next time on
Lead Leg.
Live Bye.
We're planning to really launch an ETF that
captures the company that'sgoing to take the world to
artificial general intelligence.
We think that's AGI.
So that's why we launched AGI X.
We truly value our partnershipwith Ethna Capital because they
are early investors to a lot ofthose AI companies.
Speaker 2 (00:34):
Hello and welcome back to another episode of
LeadLeg Live.
I'm your host, melanie Schaefer, head of Media Strategy and
Business Development at LeadLagMedia, and your host.
As some of you know, I recentlytook over from Michael Guyad,
the founder of LeadLag, and I'mexcited to keep bringing you the
kind of bold, insightfulconversations that matter to
(00:55):
investors right now, especiallyin fast-moving spaces like AI.
Joining me today is Derek Yan,head of Strategy at CraneShares,
where we're going to dive deepinto AGI-X, the first US-listed
ETF to give direct exposure tomajor private AI players like
XAI and Anthropic.
(01:15):
Derek, thanks so much for beinghere today.
Thank you for having me.
Gix is getting a lot ofattention.
It's the first ETF in the US toinvest directly in private AI
giants.
I mean like it's a bold move,but what gave your team the
confidence to build somethingthat's this different?
Speaker 1 (01:33):
Yeah, sure, I mean like looking like back two years
ago, when AI is really liketaking a storm, right, Like
everybody's like shocked on howgood like ChatGPT is really
changing the way people likecommunicate or generating
content.
So we're thinking about likewe're planning to really launch
(01:55):
an ETF that capture the companythat's going to take the world
to artificial generalintelligence.
We think that's AGI.
So that's why we launched AGI-X.
But a challenge we face is,back then there's so many
companies that is critical forAGI are still in the private
(02:18):
stage Talking about like OpenAI,Anthropic and later I mean XAI.
So those foundational modelcompanies are really driving
this round of innovation in thegenerative AI.
So without adding thosecompanies, you end up have kind
(02:40):
of like quite a similar exposurecompared to, say, NASDAQ 100 or
just technology sector ETF,right.
So we're thinking about why notcreate a fund that captures the
whole ecosystem, regardless oftheir liquidity profile?
So that's the ideal we had.
(03:01):
But like then like it'sdifficult, right.
So then we ask the lawyer whatwe can do.
The lawyer is like yeah,actually, ETF, end of day, is a
40-act fund.
So in the 40-act fund actuallyyou can include up to 15% of the
private assets.
So that's OK.
(03:22):
That's interesting.
Assets so that's okay, that'sinteresting.
15% is not a lot, but itactually is decent when it comes
to a portfolio of AI company.
Think about there's so many AIopportunity in the public space
and also in the private space,so 15% actually is a decent
allocation that we can allocateto those private AI companies.
(03:44):
So fast forward to today.
We actually really completethis portfolio by adding XAI and
Anthropic into the AGIX ETF.
So those two companies now arein the top 10 holdings of the
ETF, together with other publicAI companies.
(04:05):
So this is one interestingsolution now just offering the
old AI companies, regardlessthey're public or private, and
have a solution to reallyachieve that goal.
Speaker 2 (04:17):
Yeah, so I wanted to dig into that just a little bit
deeper and follow up on that,Like talking just about sort of
maybe XAI and Anthropic inparticular, what are these
companies that were?
And the other private companieswithin the fund?
What are they doing and why dothey matter so much in the AI
race?
Speaker 1 (04:32):
Yeah, if you think about like how this round of AI
is really changing the world wehave, I mean like think about AI
is really.
Think about like there'sseveral rounds of technology
breakthrough right.
There's like the old days, likethis PC, then internet was
thing, the mobile internet right.
(04:53):
Then I think like cloud, becomelike all those apps and it's
now going to cloud and startingfrom like two or three years ago
, we think generative AI isreally changing the technology
sector, changing the innovation.
That's going to create asimilar opportunity like the
previous generations oftechnology breakthrough or
(05:17):
innovation breakthrough, andthis round of really development
is really driven by the AIlarge language model companies.
So those large language modelcompanies they train like tons
of data and they can generatecontent, they can have
intelligence, that power, theability for those models to do a
(05:41):
lot of work right, like contentgeneration.
There's calculation, codegeneration, so anything like
related to code or in thedigital world can be automated.
That's really come to clientservices, come to a lot of like
I think, white collar jobs inthe enterprise world.
(06:02):
So that is a game changer for alot of enterprises and
consumers to really automate thewhole digital world.
So that's a big opportunity andthe company is critical.
I would think about it in theconsumer side, it's OpenAI,
which is probably the mostfamous one.
That's what everybody's nowusing, but actually in the
(06:25):
enterprise world, anthropic is abig player that many
enterprises is actually usingAnthropic's API.
Anthropic also has aconsumer-facing app called Cloud
AI.
It's famous for its cloud model, mostly on the, say, legal side
or coding side, not engineeringside.
(06:48):
So that is something I think,like many insiders in the tech
world or engineering world orlaw firm, is usually like using
cloud.
But I think, most importantly,the coding is a big thing,
vertical for the AI adoption andAnthropics really leading in
(07:12):
that section by partnering witha lot of application companies.
So I mean there's a lot of likeautonomous coding right now
using the Anthropix API.
Xai is another large-slang modelcompany founded by Elon Musk
right With its unique access tothe data from the social media
(07:35):
platform X.
So XAI is actually like a verypowerful model with, I think,
access right Because Elon Muskhas bought a lot of the GPU and
built a large data center.
That's powering the modelbehind XAI and XAI becoming the
(07:56):
most, currently the mostintelligent large-dash model so
far.
That gives them the edge bothin the consumer side and the
enterprise side.
So if you think about like thiscompetition right of AGI, like
everybody's now trying toachieve artificial general
(08:16):
intelligence in 10 years, 20years, it's still at an early
stage.
We don't know if OpenAI,anthropical, xai, which one's
going to be probably the AGIcompanies in the future, we were
thinking about just adding moreof those, like in the future.
So we were thinking about likejust adding more of those names
in the portfolio.
(08:36):
It's really like you don't wantto miss any of them.
What if, like, anthropi becomethe solution where XAI become
the solution?
So adding those companies,those foundational model
companies, in the portfolio ispretty critical.
If you think about Asia iscoming in a decade or two
decades.
Speaker 2 (08:57):
And I guess to follow that up as well.
I wanted to talk a little bitmore about the future of your
allocation strategy.
I mean, do you expect that themix between private and public
companies is going to change asthe more public companies mature
, and I mean especially with somany of them trading at
multiples?
Speaker 1 (09:15):
Yeah, exactly, I mean , when we added those private
companies, so we added theirprimary round, right, so
Anthropic, we entered theirfinancing round of Series E.
So that's like they're going todo multiple financing going
forward.
They may IPO in the future.
So once they IPO, they becomelike public companies.
(09:39):
So there's, I think, eventuallya lot of those private AI
companies going to be public.
So then we're going to see likehow this portfolio going to
evolve right in the future.
Because, yeah, then I thinklike currently a lot of the.
Then we're going to see likehow this portfolio is going to
evolve right in the futurebecause, yeah, then I think like
currently a lot of the thoselike high valuation companies
(10:01):
are really the foundationalmodel companies or
large-net-share model company,like OpenAI, like Anthropic,
like XAI, with like a hundredbillions or 300 billions
valuation.
So it's already like a latestage for them to really become
IPO in a stage.
(10:22):
Then I think at that time whenthose companies IPO, our focus
in the private side is probablygoing to more on the application
side.
So we actually, on our phone,we want to capture the three
layers of the AI opportunities.
One is the hardware right, likethose chip company or data
(10:44):
center related company tobuilding the hardware for the
large selection models.
And then there's infrastructurelayer.
You have cloud, you have datasecurity, data preparation,
model preparation and then themodel company themselves in the
private side.
So they are private side now.
Then when they become public, Ithink a lot of opportunities now
(11:08):
in the third layer, theapplication side.
We currently we do have a lotof application side company that
is public.
But I think like when thecomputing power of the
large-next model, when thecapability of large-next model
becomes so powerful, there willbe like tons of new application
(11:31):
companies coming up.
There will be like tons of newapplication companies coming up.
So we see, currently there'sseveral like, I think, popular
one including, say, proplacity,or many in the content creation
or like digital media.
So there's so many applicationsright now.
Even the physical AI side,right when people are now using
(11:51):
the data in the physical worldto do automation in the factory,
automation of robotics, thoseare really like future
opportunities that we canconsider in the private side to
maintain a decent exposure intothe private application to the
CTF.
Speaker 2 (12:08):
What about the AI score?
Can you talk a little bit aboutthat?
How does it differ from atraditional tech index sort of
approach?
Speaker 1 (12:17):
Yeah, so I forgot to mention.
So for AGIX, we have a partnercalled Aetna Capital Management.
So they're a venture capitalfirm that they're an investor of
the company, like XAI Anthropic, that they are early investor
of the company like XAIAnthropic.
So with their early connectionwith the company, we are able to
(12:38):
access those deal.
So that's the kind of like howwe source the deal.
So also with them, we give backlike AI score together.
Because when we look at this,the traditional index
methodology to really capturethe AI companies is either based
(12:59):
on revenue or is based oncertain, say, keyword searching
or document searching.
We don't think that's a verygood way to really capture the
AI companies.
We don't think that's a verygood way to really play this
capture the AI companies.
(13:20):
Because we really need to lookat way that, how large-slash
model, how Gen AI is changingthe business model across all
those technology companies.
Think about it right now, everycompany claim to be an AI
company, even like AT&T or likeall the other companies now is
(13:40):
using AI.
So how do you really evaluatethe impact of AI?
So that's why we partner withAetna Capital Group.
They have a committee andtogether with their committee,
with our index provider.
We developed like anindex-based methodology to
(14:01):
incorporating those AI score toevaluate the readiness and
relevance of AI for each company.
So we look at current revenueexposure for that company that
is exposed to Gen AI and also welook at their business model,
how this business model is goingto be impacted positively by
(14:26):
the Gen AI.
So with those two angles wecaptured the I think, the right
company that's really going tobe AI beneficiaries.
Speaker 2 (14:37):
Now, Derek, I want to talk a little bit about the
performance of the fund.
I mean, as you said, a coupleof years old and AGX has already
outpaced some major techbenchmarks.
What do you think is drivingthe outperformance?
Speaker 1 (14:50):
Yeah.
So I mean, when we look at theperformance of AGX since
inception, it has largelyoutperformed the broader
technology or growth indexes,for example NASDAQ 100 or just
technology sector index orsemiconductor index, technology
(15:10):
sector index or semiconductorindex.
I think the AI score is reallycreating a comprehensive way to
evaluate the long-term AIbeneficiaries right.
So that framework is actuallyadding a lot of outperformance
since our inception Because whenwe look at like there's several
(15:31):
rotation happening right, likeI think at the early stage
there's a lot of value justreally creating in the AI
hardware space.
Like NVIDIA is definitely thebiggest beneficiary in that
there's a lot of data centersbeing built out, there's a lot
of energy cooling and water.
Those companies, as you said,it's going to be a benefit.
(15:53):
We do have those companies asthe AI scores were high at this
stage when we launched ETF andgradually we realized the value
is migrating to theinfrastructure and application
companies so along the time thescore for the infrastructure and
(16:16):
application company become muchhigher.
For example, we are the earlyinvestor of company, for example
, palantir and Duolingo.
That's a perfect example of howthe AI is used right in both
the enterprise world and theconsumer side.
For Palantir, they are a leaderin the, I would say like
(16:41):
creating an operating system forenterprises to use AI, and we
realized their AI score is veryhigh and we're including them
just before even NASDAQ index.
Including the Palantir andDuolingo is another interesting
example.
Most people know the firm forits language learning, but when
(17:05):
we look at how their businessmodel is going to benefit from
AI, they just have very goodpotential and we have validated
their technology to incorporateAI in the language learning and
the result is very impressive.
So with that framework werealized there's application
(17:25):
companies is actually adding alot of performance to the AGI-X
ETF as well.
Yeah, so that framework isreally creating a thing like
long-term framework to establisha portfolio that captured the
value, gradually migrating fromhardware to infrastructure and
(17:49):
application, and I would thinkprivate companies are going to
add in some performance goingforward.
Because those companies are notpublic, so they don't have a
daily price, so it's not tradedon any exchange right now.
(18:11):
So how do we really?
I think like it's interesting.
A lot of people ask us so if youhave, like Axia and Anthropic,
how are you going to value those?
So, because ETF is is a dailyoffer, daily liquidity for any
investors, anyone can buy AJAXETF with their brokerage account
(18:32):
.
So that means we have to offerdata liquidity and then we
actually value those privatecompanies at a daily basis based
on all the information,including their primary round
valuation, including theirsecondary market transactions.
So we just included the AXArecently and we included
(18:56):
Anthropic earlier this year.
I think both companies arereally growing very strong in
their revenue stage.
So I'm sure, like with the NASfinancing round coming or just
like going forward if the IPO,they're going to add a lot of
value to agx investors yeah,with the structure of the fund,
though, like I mean, the fundactually owns equity and xai and
(19:18):
anthropic correct yes, so, uh,actually we own where agx uh uh
sit on the cap table of both xaiand anthropic uh, so it's a
shareholder of the two companies.
So that's like direct ownershipcompared to owning them via
(19:38):
another structure.
So it's very simple.
We like that simplicity.
I think that's like mosttransparent way to invest in
those two companies and ourinvestor really loved that way,
compared to there's many other,I think, retail trading platform
or like a very complicatedstructure to invest in those
(20:01):
companies compared to AGX, whichis like simply directly owning
those shares.
Speaker 2 (20:07):
Yeah, it's quite rare and I know fair valuation is
something investors worry aboutquite a bit.
I know fair valuation issomething investors worry about
quite a bit, you know,especially with private equity
and with the liquidity in ETFs.
Can you explain how CraneShareshandles pricing for the private
side of the portfolio and whatsystems are in place to make
sure that it's accurate and hasthe investor money first?
Speaker 1 (20:28):
Yeah.
So first of all, thosecompanies are not really a
startup.
So for startup there's like awide range of what is the fair
value right for those companies.
But the company we invested aremostly the late stage large cap
technology companies, right.
(20:49):
So if you think about thevaluation of those foundational
model companies, they'rehundreds of billions and now the
companies are staying in theprivate longer.
So there's a decent number ofinvestors actually now trading
in the secondary market forthose companies.
So we actually use a lot ofthird-party data provider to
(21:15):
really gather those transactiondata happen in the secondary
market and there's a lot ofinformation we can use to really
have a best practice to have adaily fair value committee and
daily fair value process toincorporate all the available
information that deliver thedaily value for those private
(21:40):
companies.
So that's why AGX, as ETF canprovide daily liquidity to all
investors that want to invest inthose companies.
Speaker 2 (21:50):
I'm not sure I think you touched on it, but the fund
supports financing rounds forthese private companies as well,
which is a new dynamic for theETF world.
How does that relationship workin practice and what kind of
access does that give youcompared to traditional ETF
models?
Speaker 1 (22:06):
Yeah, it's really actually because those companies
are.
I mean, everybody's likechasing those companies right.
So it's really actually becausethose companies are I'm like
everybody's like chasing thosecompanies right.
So it's really hard.
That's why we truly value ourpartnership with Aetna Capital.
They have because they areearly investor to a lot of those
(22:28):
AI companies.
By the way, I forgot to mentionAtmar Capital was founded by AI
native engineers and earlyinvestors, so themselves have a
decent network among the AIresearchers and engineers across
those Gen AI companies and AIapplication companies.
(22:50):
So that's why I have a closerelationship with the company.
It's very important becauseusually now it's over-subscribed
for any round of financing,given how popular those
companies are at this stage.
So getting access through thisconnection and with the help of
(23:13):
theetna team is very important.
And we actually, when welaunched AGX, we invited both, I
think, anthropic and Proclacityteam to join our fair reigning
on the NASDAQ exchange and wedid a panel discussion with them
(23:33):
to talk about the future of GenAI.
So we're going to keep doingthat, with the close
relationship with the companyand with their engineering team,
research team, to really buildthis network and ecosystem for
the AGI.
I think that's kind of like theapproach we're going to do.
(23:55):
We're going to maintain a goodrelationship with the company
themselves.
So in the future, if there'sanother round of financing or
tender offer, we're able toreally participate.
Speaker 2 (24:06):
And so are there more private names coming in the
future.
Can you talk a bit about thatat all?
Speaker 1 (24:10):
Yeah, I mean like there's a lot of companies we're
engaging, that's in thepipeline.
There's a lot of like excitingopportunity, I think, both in
the financial model round sorry,foundational model round and
also a lot of applicationcompanies we're talking right
now.
But because this is still, Ithink, like when you have this
(24:33):
conversation, when you haven'treally made the deal, you cannot
announce that, unfortunately.
But I would say, like investors, please follow Cranesharescom,
slash AGIX for more announcementgoing forward.
So just stay in tune.
Speaker 2 (24:51):
Yeah, derek, and you have other funds as well.
Can you talk a little bit aboutthose just more in general, and
do you have any new products onthe horizon?
Speaker 1 (25:01):
Yeah, actually we recently launched a
humanoid-focused ETF calledK-O-I-D Koid.
We think, like when we launchedAGIX, we think like Gen AI is
really exciting and it'sphenomenal, so what could be
(25:22):
like kind of like nest Gen AI?
So when we also, like we werewatching, like the CEO of Nvidia
, jensen Huang, his keynote atthe GTC conference I think he
mentioned that the robotics,especially humanoid robotics,
can be, could be the next bigthing the traditional AI to
(25:43):
generative AI to AI agent, wherea lot of AI apps can really
autonomously get a lot of thingsdown, in the future it could be
happening in the physical world.
So physical AI is kind of thenext big opportunity.
(26:05):
So that's why we launchedKO-O-I-D recently to really
capture the humanoid opportunity.
Actually we bring a realhumanoid.
There's a company calledRoboStore based in Long Island,
new York.
They're a distributor of thehumanoid robotics.
(26:28):
I was there at their warehousein Long Island.
It's like a dream come true.
Like there's robotics, like therobots are everywhere that can
move and run like very smooth.
So seeing that, I mean sincebelieving the technology
breakthrough in the hardware isreally at a stage, I think like
(26:50):
making humanoid and that's bigpotential for a lot of
applications.
And AI is bringing theintelligence to those humanoid
robotics, so that's why wecreated a KOID to really capture
that opportunity.
Speaker 2 (27:07):
And there's a great picture of the humanoid robot
ringing the bell at the stockexchange on your website that
people can go and look at.
Derek, it's been so greathaving you here.
Speaker 1 (27:17):
Thank you very much.
Thank you for having me.
Speaker 2 (27:19):
I'm Melanie Schaefer and we'll see you next time on
Lead Leg.
Live Bye.
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