Ep. #56: Paul Singer, CEO & Cofounder of FleetWorks

Episode Transcript
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Speaker 1 (00:00):
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(01:30):
Welcome back to another episodeof FreightPod.
I'm your host, andrew Silver.
I am joined today.
We are in the deep dive of AI.
I've got another tech startupin the space, this one founded
by a gentleman who has someindustry experience, some very
interesting experience.
My guest today is Mr PaulSinger, the CEO and co-founder

(01:54):
of Fleetworks.
Paul, welcome to the show.
How are you doing?
I'm doing well, man.
Thank you for having me.
Of course, you're in aninteresting space.
This voice AI stuff.
It's seemingly every week welearn something new.
That's I don't know, maybe gamechanging.
Let's start with the deep seekstuff.

(02:14):
As somebody who actuallyunderstands what's going on with
all this, give me your kind ofunderstanding of what the world
just went through with DeepSeek,announcing that it had created
what it did on such minimalfunding.
Whether that's true or false,I'm just curious your thoughts
there before we get into yourstory.

Speaker 2 (02:34):
Yeah, I don't know if people have actually looked
into how verified those claimsare.
It seems to be true.
Yeah, I mean for context onfolks who haven't seen this so a
Chinese hedge fund that hadsort of an AI research
department basically created areally high-end what we call a

(02:54):
reasoning model with far fewerresources than OpenAI Anthropic
or any of the sort of bigfoundational AI companies.
So typically it costs, you know, hundreds of millions of
dollars to train these models.
Deepseek claims to have done itwith, I think they said, $6
million.
So super impactful for NVIDIA,because every investor assumed

(03:17):
that NVIDIA is just going tohave infinite demand with sort
of these AI companies trainingtheir models, with sort of these
AI companies training theirmodels.
Turns out, you know, deepseatdid it basically with just a few
sort of lower-end chips and sothe implications for kind of the
whole infrastructure of AIs ishuge.
Obviously Implication forOpenAI Anthropic is really big.

(03:38):
I have friends who work at allthose companies and you know
there's certainly a kind of amoment of reckoning for all
these companies.
They're like wow, wow, wearen't as protected as we
thought.
For companies like us, we arethe application layer on top of
AI.
It's really exciting.
Typically for us, we need toassess what is the right model

(04:04):
to use for any given task, andso we'll use, you know, we'll
use open source models that wekind of fine tune for our own
use cases.
We'll use sort of foundationalmodels for some parts of our
product.
We haven't yet used thesereasoning models because, number
one, they're a little bit slow.
They're designed to be a littlebit slower, but they're also

(04:27):
really expensive, and soDeepSeek basically takes that
whole expensive thing out of theequation.
I think the numbers I've seenis it's 97% cheaper than using
OpenAI's reasoning model.

Speaker 1 (04:40):
Can you explain the difference between?
You mentioned slowness, but thedifference between what you get
from a reasoning model versuswhat you're using.

Speaker 2 (04:50):
Yeah, absolutely so.
A reasoning model basically hasbuilt in what we call or what's
called chain of thoughtreasoning, and so basically when
you submit a prompt or yousubmit a request for an AI and a
lot of folks who are listeninghave already used ChatGPT so you
see, chatgpt kind of thinkingout loud how it works and so a

(05:16):
reasoning model kind of justdoes that 10x.
So it's going to really spend alot of time going through every
possible avenue before itoutputs a result.
So the results tend to be a lotof time going through every
possible avenue before itoutputs a result.
So the results tend to be a lotmore accurate.
But the downside is that it canA cost a lot of time and since
we do a lot of things on phone,email, text message, real-time

(05:38):
communication, it's not a greatapplication for what we do today
.
I think, given the way thatthis tech is advancing, maybe in
a year or two we'll be able touse reasoning models in these
sort of dynamic use cases.

Speaker 1 (05:56):
Got it Okay, and what do you see as the overarching
impact?
Is this a foundational moment?
Is this deep seek announcementa foundational moment in AI?
And I know you're going to besomewhat guessing, or at least
it's an educated expectation orguess but is this a foundational

(06:16):
moment long?
What do you see as thelong-term impact to the open ais
of the world who have investedbillions um and and maybe
disrupted by a much cheaperalternative?

Speaker 2 (06:34):
yeah, it's a good question.
So I kind of view this morelike a covid moment for ai,
where I think COVID reallyaccelerated digital adoption for
a lot of things.
Every digital platform didreally well in COVID, so the

(06:54):
rate of growth reallyaccelerated and then it sort of
normalized back to what it waspre-COVID.
But COVID kind of acceleratedadoption of digital things,
whether it be like a, you know,like a toast terminal at like a
local restaurant that you go to,or like using Airbnb versus
like calling a hotel to book abooking, for example so just

(07:15):
accelerated digital adoption.
I don't think this is anythingnew, though.
Like frankly, what we do seeevery year in foundational AI
models is we do see step changeimprovements.
So I think this is more of aCOVID moment, where the step
change was quicker than peopleanticipated, but the way that
we're all modeling theseimprovements is that it's just

(07:38):
going to continue to really ifnot linearly, maybe even
exponentially improve thesemodels.

Speaker 1 (07:47):
And last question here before we're going to get
into your background and thenwe'll go through the whole
linear story how, as a CEO of aup-and-coming AI business, do
you factor in these types ofstep change improvements that
can even be exponential?
How do you factor that intoyour own product development and

(08:07):
kind of company evolution?
How do you take that intoaccount?

Speaker 2 (08:12):
yeah, it's a good question I we think about in a
couple of ways.
So, um, with these foundationalmodels, I would kind of think
about them on three differentaxes basically.
So there's speed, there's powerand there's cost and with all

(08:34):
these models, and probably inperpetuity, there's some
trade-off to be made betweenspeed, power and cost.
Like we talked about reasoningmodels being really powerful and
more expensive and DeepSeeksort of changes, that dynamic
but for sure they're slower.
Right Versus you have thesemini models that are cheaper,
faster and way less powerful.

(09:05):
Evolving space.
I would say we're prettyconsistently evaluating what's
the right trade-off to make atany given time, given the
advances in those foundationaltechnologies.
Ultimately, I think we've foundthe right balance for now.
But essentially what?
Basically what's going tohappen is we're going to keep
upgrading our foundationalmodels and they're going to be
more powerful.
For example, as you think aboutcarrier negotiation, today we

(09:30):
do a lot of guiding of the AI tomake sure that's really
successful, but in the futurethe AI might be able to do that
more autonomously for the sameor even cheaper cost today.
So basically we just assumethat all the foundational models
will get cheaper, more powerfuland faster.
I would say every nine monthsis probably the right cadence.

Speaker 1 (09:53):
And is it easy to sorry, I'm going to stay on this
for a second but is it easy to,let's say you are using, you're
using Model X, and Model Ycomes out it's a different
company, whole different thingand you just look at it and say
this is better than what we'reusing today?
How easy is it to just pick upyour product off of Model X and

(10:17):
dump it on Model Y and thenyou're just off and running.

Speaker 2 (10:22):
On a high level.
It's super easy.
It's basically just changing anAPI key.
I think this is getting alittle bit more detailed about
what we do, but customers trustFleetworks to be their front of
house.
Freight brokers, when they useFleetworks, are saying I'm going
to trust Fleetworks to talk tomy carriers, which is one of the

(10:43):
most important things that wedo as a brokerage.
So it would be, I think,foolish of us if we were to just
say we're going to swap fromOpenAI to Anthropic or OpenAI to
DeepSeek, because whileswitching is super easy, there
might be some unintendedconsequences because all these
models perform slightlydifferently.

(11:03):
So if we were to do that, wehave rigorous testing in place
to make sure that when we make amodel change, that it's passing
all the criteria that we wouldexpect, so we're not like
creating bad experiences forcarriers and brokers.

Speaker 1 (11:17):
What's an example of an unintended consequence that
could come up.

Speaker 2 (11:22):
If you didn't do it right.

Speaker 1 (11:23):
I'm not saying this has happened to you.
I'm just curious Totally.

Speaker 2 (11:26):
There's probably dozens.
One really easy example wouldbe, I think, around what we call
hallucination rate, so the AI'spropensity to make up answers
to things.
We've done a lot of things onour side to reduce and eliminate
hallucination rate.
But one great example would beKara calls you about an

(11:47):
available load.
Let's say they're a dedicatedcarrier.
They say, hey, I run this laneregularly for you.
Can you just send this over?
Do you still have that load forMonday?
Dallas to Chattanooga, I'll doit for $1,000, like usual.
And the AI says, instead ofsaying yes, I'll send over right
now it says, oh, no, we need$900 on this one.

(12:11):
That could be an unintendedconsequence where you want to
honor that rate on file with thecarrier, but because you
swapped the model and becauseyou don't know how it's going to
perform, maybe it's going to dosome weird things for you.
So those are the kinds ofthings that we test for whenever
we think about a change.

Speaker 1 (12:27):
And that's an example of a hallucination rate where
the history and guidanceprovided in the model is for.
It should know that Dallas toChattanooga has been run by this
carrier eight times for $1,000.
It's an approved rate in ourprocess and it will just
hallucinate the idea that itshould try to get cheaper and

(12:48):
then go for 900.

Speaker 2 (12:49):
That's one great example.
I think another one could beappointment times.
So Kara says, hey, this load'ssupposed to pick up at noon.
Any chance we could shift itover to 2 pm.
Sometimes we know we can,sometimes we don't know.
The last thing we want to do istell the carrier yes, we can
when we're not sure.
So that's just another exampleof how we prevent hallucinations

(13:10):
, so something that we're prettycareful about.

Speaker 1 (13:14):
Interesting.
How do you catch thehallucinations happening?
Because that's not a supercrazy situation.
If I look at a brokeragewithout Fleetworks or any tool
like this, that type ofconversation whether it's a
mistake or the right answer ishappening all day, where the
carrier is asking for a rate orthe broker is responding with an

(13:37):
approval or not enough.
And how do you even notice thatthose are hallucinations?

Speaker 2 (13:43):
Yeah, we could kind of get really deep into this,
but I think AI totally changeshow you build companies.
So typically when you buildtechnology, you have really
rigid what's called test cases,like basically like a source of

(14:03):
truth, Like if we expect if Xhappens, it should always end up
as Y, and so the cool thingthat AI enables you to do is
actually have your test cases bea lot more fluid, which means
you can create like you cancreate hundreds of thousands of
test cases.
So we're constantly on everysingle call that we're running

(14:28):
and every single email, everysingle piece of communication,
we run test cases against those,and so we have basically AI
evaluating AI.
So we'll run the call or runthe email through another AI and
says this was good for one, two, three reasons, or this was bad
for X, Y, Z reasons.
Therefore, you should go andchange the original model.

(14:52):
That's how we think about kindof the AI self-learning and the
AI self-evaluating.

Speaker 1 (14:58):
But even in those examples, is there not a person
who has to tell the AI this isgood or the AI is capable of?
At some point?
There's a person who's got tobe giving the input of yes or no
, good or bad, right.

Speaker 2 (15:12):
Yeah, we build the test cases.
So we build the test cases andthen we let the AI run at it.

Speaker 1 (15:17):
Okay, Got it Understood.
All right, Now let's go back.
So I appreciate you kind of.
I don't know this conversationcould go deep into AI for a
number of reasons.

Speaker 2 (15:27):
I'm down.
When did you first?
When I left Uber I think it wasGPT-3 had just come out, or

(15:54):
basically ChatGPT had justlaunched, and the technology was
super simple, or at least theoutcomes were simple.
You could give it an email andyou would tell it hey, make this
more professional or make thisfunnier, write me a joke.
There was none of theinfrastructure built to be able
to build what we have today.

(16:14):
I started playing around with it.
I would be lying if I said thatwe had this idea at the time.
We were just playing aroundwith AI.
At the time, I was building acarrier-facing product.
We thought that there could bea better driver workforce
management product for carriers,because drivers are churning

(16:35):
all the time.
They don't have good visibilityon what their pay looks like.
We were building in that space.
It was a total flop.
It was a really bad idea.
That space it was a total flop.
Uh, it was like a really badidea.
Um, frankly, like after talkingwith probably 300 drivers over
the course of three months,we're like this is, drivers
don't actually care and they'refine with with how things are.
Um, so we went back to thedrawing board and I would say it

(16:59):
was about a year and a half ago, year and a half ago where you
could build a viable voice AIagent Barely viable, I would say
.
My co-founder and I, we wereplaying around with various
ideas.
I remembered back in my time atUber that, despite our app we

(17:20):
had built this app, carrierswere using it, we were getting a
ton of bookings through it, butstill about a quarter of our
bookings were done off ofCollins, gatt Collins, and so I
was like, hey, like, if we couldbuild a voice AI agent to at
least like, screen the carrierand share the details of the
load, that could be prettyhelpful for a lot of brokerages.

(17:41):
So we built a pretty scrappyprototype.
We found a load board that letanybody sign up and post loads,
and we signed up for that loadboard and posted just one load
that we knew would generate abunch of interest.
And this was straight up one ofthe worst I think one of the

(18:02):
worst products we'd ever built.
It was janky, the lag was bad,the voice quality was bad, it
was nothing like what we havetoday, and I remember we got
three carrier calls and on twoof them the carrier knew they
were talking to an AI and theystill went through the whole
call and on one of them thecarrier didn't even know they're

(18:24):
talking to an AI and negotiated.
And after that, those threecalls, we kind of looked at each
other.
We're like this is real Withthis product that we built, that
is bad on every dimension.
It's working Because we werefirst in the space.
It was such a big arc toconvince people that, hey, like

(18:48):
this thing actually works, likecarriers are are down for this,
um and and I remember we we hada conversation a while back like
hey, do you care?
Like what do carriers eventhink about this?
Um, and I mean I think wewouldn't even have a company if
carriers didn't mind the process.
I think ever since those threecalls, we've really just been

(19:08):
off to the races, and what'sbeen cool, as we've kind of
talked about, is the underlyingtechnology has just gotten
better faster than anyonethought, and so what we can do
for our customers has justcontinued to expand over the
last year and change since welaunched the product.
Who's we?
We is an ever-changingdefinition.

(19:35):
My co-founder and I met throughmutual friends in New York.
His name is Kwong.
He used to lead theexperimental engineering team at
Airbnb.
It's been a great partnership.
I feel very blessed, first ofall, just to be working with him
, and then I think it's just awell-known secret that good
talent attracts good talent, andso we've got eight more people

(20:00):
in San Francisco, a few morepeople remote.
Every technical person on theteam is either a current founder
or a former founder, soeveryone on the team is a former
CTO.
You've got myself, you have acouple of other markets.

Speaker 1 (20:16):
Everyone on the team is a former CTO of a business.
Yes, that's wild, of 10 people,10 people are all former CTOs,
essentially.

Speaker 2 (20:24):
Yeah, we have seven technical people and seven CTOs.

Speaker 1 (20:28):
Wow, very cool, yeah.
And so what was the timeline ofwhen you built this product and
made three calls on a loadboard?

Speaker 2 (20:36):
How long did it take us to do those first three?
Well, when was that?

Speaker 1 (20:41):
This was when was this?

Speaker 2 (20:43):
This was, would have been summer 2023, so call it
like, uh, like a year and a halfago okay, yeah, and interesting
anecdote.

Speaker 1 (20:54):
You mentioned that.
So you went, you worked at uberfor five years.
We should talk a little bitabout that and maybe let's do
that now to get that out of theway.
Um, how did you get to Uber?
What was the?
You were trying to work infreight or you just saw the cool
Uber name?
What was the story there?

Speaker 2 (21:12):
I knew literally nothing about freight Seven
years ago.
I was like, well, kind ofintroduced me, so I started my
career in management consulting,which was great training ground
, but generally I would notrecommend it.
I think, if you're someone thatwants to start in management
consulting, if was greattraining ground, but generally I
would not recommend it.
I think if you're someone thatwants to start a management
consulting, if you're someonewho's like, let's say, 20, 21,
22, listening to this podcast, Iwould recommend that.

(21:35):
If you're someone who thinksyou're a hustler and you want to
be analytical, go learn alittle bit of SQL, go learn a
little bit of data analysis.
A little bit of data analysis.
And cold email 30 startup CEOsand say, hey, I will do anything
for you and I bet you like 20out of 30 are going to respond
and you'll probably get aninterview with at least half of

(21:55):
them.
So I'd really recommend thatcareer path as an aside.
So I did consulting for acouple years, met some really
smart people, learned a lot ofstuff, but did two things that
kind of elevated me to UberFreight.
So first was I did a consultingcase on industrial metal doors.
This was back in 2017.

(22:17):
Turns out, the industrial metaldoors industry is fascinating.
There's like three companies.
Two of them are private equityowned, one of them every PE
company wants to own but the guyrefuses to sell.
So it's like a funny, like alittle little dynamic in this,
in this niche space.

(22:38):
And, unsurprisingly, thebiggest part of the industrial
doors market is warehousing.
Right, like every warehouseneeds whatever dozens of doors.
And so I was like this is kindof kind of this is interesting.
Like I I grew up in suburbanconnecticut like I've never,
I've never, I don't hadn't seena warehouse at that point.
Um, and then a couple months,so I was like okay, like so
trucking is big, warehousing isbig, that's cool.
I didn't really think that muchabout it.
Um, then a couple months later,the partners of lek came to me

(23:02):
and said hey, we're writing awhite paper on Uber Freight.
Uber Freight had just launched,maybe six months earlier.
Do you want to help us doresearch for the white paper?
I was sort of between projectsat the time.
We call that being on the beachand you kind of just help the
partners with research anddevelopment.

Speaker 1 (23:21):
I thought it was called being on the bench.
It's being on the beach.

Speaker 2 (23:24):
Being on the beach, being on the beach yeah, I
thought it was on the bench no,it's being on the beach.
It's kind of a reward for, uh, alot of hard work, like once
you're like on a project forlike four months.
They're like you get to go tothe beach for like a week.
Right, um, got it.
So.
So I was beached and I wasdoing this research and I was
like this is crazy.
Uber rides was at the time,still exploding, growing double

(23:50):
digit percentage year over year,off of tens of billions of
dollars, and Uber Freight wasstarting from nothing.
At that point they were maybe100 loads a day, 200 loads a day
, and our thesis was that UberFreight would not grow as
quickly as Uber rides, which wegot right.
But the reason why we got wrong?

(24:11):
So we thought that because theindustry is slower to adopt
technology, which I think waswrong.
The industry's actually prettyquick at adopting technology if
it makes sense.

Speaker 1 (24:24):
If they want to, yeah Right, yeah if the ROI is there
.

Speaker 2 (24:29):
They were like oh, we thought that because the
industry's slow at adopting tech, uber rides or Uber Freight's
not going to grow as fast asUber rides, so it did not grow
as fast.
But the reason is because UberFreight ultimately was providing
a somewhat commoditized serviceto shippers and no shipper is

(24:51):
incentivized to give any singlebrokerage all or most of their
wallet share.
So Uber Freight's thesis washey, we can procure carriers for
less, therefore we're going towin more freight from shippers.
I don't think that thesisproved to be true and I think
Uber buying TransPlace was agreat move on their part,

(25:14):
because ultimately, that is kindof how you tap into that
shipper wallet share in adifferent way.
Ultimately, my experience atUber Freight was just amazing.
I mean super smart people,really passionate.
I think Uber did a great job ofbringing in talent who
otherwise might not have workedin logistics, and you've seen
now so many startups come out ofUber Freight, us being one of

(25:37):
them.
You've got Loop, you've gotTruckSmarter, you have a bunch
of others as well.
So really, really great groupof people and I wouldn't trade
that experience for anything.

Speaker 1 (25:49):
What would you say have been the best takeaways
you've had from that experience,or learnings from the four to
five years you spent at thatbusiness?

Speaker 2 (26:01):
I think there's some personal stuff and there's some
professional stuff.
So on the personal side ofthings, I very quickly was like
holy shit, this industry iscrazy.
I was just blown away by theamount of problems.
So my first project was the ELDmandate had kind of just gone
into effect.

(26:21):
That was my first project and Iwas supposed to come up with a
strategy for how we were goingto engage with the ELD providers
and the ELD aggregators.
So we built that strategy andwe executed on it.
We ended up partnering withSamsara, Keep Trucking, P44,
MacroPoint, like all the bigplayers.

(26:42):
I really loved building andworking with small carriers.
Like for me, that was.
That was that's what kept memotivated and that's what kept a
lot of people at Uber Freightreally motivated.
Um, I had, I had the personalphone numbers of probably a
dozen carriers.
We would talk regularly everysingle week.
Um, and it was really becauseof that experience that, that

(27:05):
experience that I got the chanceto go from operations to
strategy to product andultimately lead a big chunk of
the carrier product team.
I just love building productsfor carriers.
I think empowering those guyswho, as a tangent fraud, is a
really hot topic right now.
Everyone is really concernedabout fraud, as a tangent, fraud
is a really hot topic right now.

(27:25):
Everyone is really concernedabout fraud, as they should be.
I really personally think it'sstill important to remember that
, hey, 99% of carriers out thereare pretty honest, hardworking
people who just want to providegood service.
And so, for me, what gets meexcited, even today at
Fleetworks, is how do we helpthose people make more money,

(27:48):
how do we empower those people,how do we continue to be a
carrier-first company?
I think that's what UberFreight instilled really well.
Personally, for me, it justfelt like, you know, Uber gets a
lot of knocks, but internally,I will say that every decision
we made was through the lens ofhow can we create a great
carrier experience, Because thatwas our differentiator.

(28:08):
That's how we got so manycarriers was carriers liked the
Uber Freight app Like theyreally did.

Speaker 1 (28:13):
Yeah, that's great.
What would you say on the flipside were, like, the biggest
misses or biggest challengesthat you endured or noticed
while there, or why you think itdidn't maybe reach a level that
it might have wanted to yeah,um, we spent a lot of time
thinking about that and that'skind of some of the foundation

(28:34):
for, I think, why flea worksshould really exist.

Speaker 2 (28:36):
To be honest, um, I think it's really hard to
digitize freight through digitalchannels, and what I mean by
that is, like when you have anapplication, when you have like
a website or when you have amobile app, you can very quickly
get a lot of demand for that,as Uber does.

(28:59):
Right, like I mean, at thispoint, tens of thousands, if not
hundreds of thousands, ofdrivers are sessioning in the
Uber app every single month.
The problem is those guysaren't very sticky.
They tend to treat Uber Freightjust like they might any other
broker or just like they mightDAT.
Right, it's just atransactional place to get

(29:21):
freight.
I think where Uber kind ofmissed the ball is sort of two
pieces.
Number one is the carrierrelationship.
Like how do I understand at areally deep level who this
carrier is, where they like torun, like what makes that
carrier tick and like how can Imake that carrier successful?
I think a great carrier rep, agreat individual rep, can do

(29:43):
that, but they're sort oflimited by just the amount of
neurons in their brain and theamount of time that they have.
In a day Like me when I startedon the carrier floor and I was
only there very briefly you canmaybe keep 10 or 20
relationships in your mind or ina spreadsheet.
It's pretty hard to scalebeyond that.
So I think that was one miss isUber thought they could scale

(30:05):
that relationship and they neverreally invested in it.
And then number two was thatthis is a little
counterintuitive but it'sobvious if you've been at
brokerage.
Uber did really well on shorthaul freight your intrastate
Texas, intrastate California,regional Southeast.
Uber crushed those lanes andUber outper regional Southeast.

(30:28):
Uber crushed those lanes andUber outperformed a lot of
brokers on those lanes.
But, as you know, those are notgood paying loads.
You might get 200 bucks on thatload and Uber might beat out
some mom and pop brokerage beatthem by 10 bucks, but Uber's
making $30 of margin on these$200 loads and suddenly, when

(30:49):
you add any operations into thatgross margin equation, uber's
just losing money on thatfreight right.
And so where a lot of brokerstend to go is they build density
with short haul but then theyinvest a lot in this long haul
freight where it's high margin,high top line but a little bit
higher touch, higher service,really hard to cover through

(31:11):
what I'll call digital channels,and so they rely on phone and
email and text message andWhatsApp and Google chat and all
these ways to procure capacitythat Uber just wasn't going to
invest in.
And so Uber was really bad atlong haul freight and really
really good at short haulfreight, so they kind of started

(31:31):
to do a lot more short haulfreight and it was sort of this
weird negative selection problemwhere they weren't able to
really optimize that long haulfreight that's going to drive
most of the margin for thebusiness.

Speaker 1 (31:48):
So just an interesting thought.
I had listening to that.
There was a point when Convoywent under that I was, I guess,
arguing with my old co-founder,matt Bogrich, about Convoy and
what I was saying that I hadheard was that Convoy had
secured like exceptionalautomation and higher than

(32:15):
industry average margin percenton some of these dedicated lanes
.
Some of these dedicated lanesand the higher than industry
average margin percent wasthrowing me for a loop and
throwing both of us for a loopwhere he was just like I don't
believe it, I don't, I thinkthat's just a lie and I was like
I think it's actually true.
But the only way it makes senseis if they were really good and

(32:38):
really heavy on short haullanes that were like 200 a load
and you could be at 30 or 40,$40 a load in margin, which does
not cover your cost.
It's not enough money, but on amargin percent it looks really
good 15%, 17%, 18%, whatever itmay be.

Speaker 2 (32:57):
It sounds like Uber in some respects was in a
similar situation Exactly, andit makes total sense when you
think about Uber rides.
If you go to New York City andyou call an Uber, it's a
four-minute wait time.
The marketplace is really dense, it's really good and things
tend to be really efficient.
Let's say you go to I don'tknow Birmingham, Alabama, small

(33:22):
city.
You call an Uber, it could be20 minutes away.
Like, the marketplace just getsworse and worse the less dense
it is, and so it totally makessense why a mobile app-based
brokerage would suffer similarproblems as Uber rides.

Speaker 1 (33:40):
Yeah, I made this analogy, I think, talking to
another AI business and just theidea that the marketplace
freight matching concept.
It doesn't work if you thinkabout it like a Tinder, in that
Tinder's job would be to matchall of the people with all of

(34:01):
the people.
Tinder and Hinge or whateverthey're good at getting some
people matched and then thosepeople are gone.
But if your job, like your jobis as a brokerage, is to execute
every order I've taken from acustomer, which means that in
the Tinder analogy, tinder'sonly successful if they match
everybody.
And the reality is some peopledon't have a lot of matches and

(34:25):
whatever the reasons are, itdoesn't matter.
But there are reasons likeloads.
If a load is really ugly, it'snot getting matched easily.
No one's showing up and wantingto take it unless you start
offering to pay asinine amountsof money.
So I don't know.
I just think that's interesting.
We don't have to go muchfurther on that Other than, I

(35:08):
guess, to talk a little bitabout kind of your takeaway in
starting Fleetworks.
You know, one of the commentsyou made earlier was that Uber
still had something like up to aquarter of its loads being
covered by Collins from boardslike the DAT, which validates a
point that I've made before,which is nearly every brokerage
still has to use load boards,and shippers don't like to hear
that, but it's a reality.
And just because you use a loadboard doesn't mean that's a bad
thing.
I think that it's all aboutwhat you do with the carriers
that call you, and it's what isyour strategy.
If your strategy is to simplypost and pray and rely entirely

(35:28):
on the load board and hope youfind good carriers, that's not a
good strategy.
If you use it as one placewhere you are getting visibility
of your freight out to themasses and then, once the masses
call into you or email you oryou talk to them, however, you
get in touch with them once you,if you then vet them
appropriately and develop theright relationships with them

(35:50):
and set the right expectationswith them, you can have a very
successful partnership thatallows you to service your
customers.
But I just think it'sinteresting like the company
that's invested hundreds ofmillions of dollars into
creating a carrier marketplaceso they could not have to use
load boards still has to useload boards, which segues, I

(36:14):
think, nicely into the idea ofFleetworks, right.

Speaker 2 (36:18):
I agree.
Yeah, I think ultimately,freight is so interesting
because so far there is nosingle market clearing
marketplace.
Dat is probably the closestthat we have, but I don't think
it is.
It's obviously not the singlemarketplace, right?

(36:39):
There's a lot of freight notbooked on DAT.
It is a good segue into us andwhy we should exist.
So if folks haven't heard aboutus, so Fleetworks yeah, go
ahead, go ahead and explain whatI was going to ask and I just
didn't.

Speaker 1 (36:53):
I wanted to take a drink, but it's all good, tell
us what is Fleetworks, yeah.

Speaker 2 (36:59):
So we're a lot of things.
Fleetworks uses AI to connectcarriers and brokers.
What that means is when acarrier calls you off of DAT,
fleetworks can answer that call.
We can vet the carrier throughour partnerships, whether that
be Highway RMIS, my CarrierPacket or my Carrier Portal.
We can describe the load to thecarrier, including all the way

(37:22):
down to the special instructionsand the expectation setting of
the load, and then we cannegotiate on price and,
depending on what our customerwants, we can actually go all
the way to booking the carrieron the load.
That's our core product today.
That's where all of ourcustomers are finding no joke
10X ROI just from a operatingcost standpoint.

(37:44):
So there's 10X ROI withFleetworks just on that product.

Speaker 1 (37:49):
Because we've built this Can you clarify something?
Yeah, sorry, you mentioned atthe start of that answer, for
what Fleetworks is you mentionedwhen a carrier calls you in off
DAT.
I'm pretty sure, and just wantto confirm, you are not
connected to DAT, in that it hasto be a call in off DAT,
correct?
It can just be connected to DAT,in that it has to be a call-in
off DAT.
It can just be connected toyour company call line.
Anyone who calls into thecompany could be answered by a

(38:12):
Fleetworks AI agent, correct?
That's exactly right, yeah.

Speaker 2 (38:15):
So when a carrier calls you, whether it be DAT,
another load board or even justyour general line, we can answer
that call for you.
Customers also use us to makeoutbound calls to carriers,
whether it be to offer availableloads, like, hey, I've got this
carrier in my routing guide,let's go offer it to those
carriers first, before we put itout publicly on the load boards
.
How do we encourage morerelationship building?

(38:38):
And customers, of course, aregoing to be using us for track
and trace.
Carriers, for various reasons,don't use GPS services or might
turn them off, or there's someissues and you want to call the
carrier and you want to know isthis load on time?
Have you arrived?
Are you being loaded?
What's going on?
We take all that informationand we automatically update our

(39:16):
like.

Speaker 1 (39:16):
Your TMS is operating autonomously through the use of
Fleetworks voice agents, ouremail agents and our other sort
of communication agents liketext and WhatsApp.
What has been the biggestchallenge in building the
product itself?

Speaker 2 (39:23):
Yeah, On the product itself.
Yeah, on the technology side, Ithink one thing that we've done
well which has been hard hasbeen being very diligent with
our customers about offeringthem the customization whether
self-serve or whether we do itfor them the customization to

(39:46):
build AI agents in a way thatreally fits their business.
I think every brokerage hastheir own bit of secret sauce
and their own way of doingthings, and so it was really
hard upfront to build a productthat could support different
types of negotiation, differentphrasing, different ways of
doing business.
But I think we've gotten thatand I think we're continuing to

(40:10):
invest there.
But that's a really big thingfor us is not forcing brokers to
fit to our process, but ratherbringing a technology that lets
brokers adapt it to how theywant to do business, which is
kind of a new way of technology.
I think that's the other thingthat AI sort of unlocks is you

(40:30):
don't have to build your team tofit what that tech provider
tells you to do.
We share best practices withour customers, but we let them
kind of customize things to howthey need to run the business.
And is that?

Speaker 1 (40:44):
customization work done by your team of seven
technical people, or is theirteam that can go into the system
and change things however theysee fit?

Speaker 2 (40:53):
It's both.
It's both yeah.
It really depends, and also, itdepends on their level of
sophistication.
Some of our customers arereally sophisticated.
Their developers are directlyconnected to our developers on
Slack and we're talking everysingle day.
Sometimes we offer that as aservice to our customers too.

Speaker 1 (41:12):
And why wouldn't a sophisticated brokerage or a
brokerage with a sophisticatedtechnology team?
Why wouldn't they just buildthis themselves?

Speaker 2 (41:21):
They could certainly try, they could try, could
certainly try, they could try.
What they will find is thatit's really easy to stand up a
proof of concept.
They could build a voice AIagent in.
I don't know, maybe if theywere really dedicated on it
let's say two months, I thinkwhat they'll find is that the

(41:44):
amount of UI that operators needto understand what the AI is
doing, but then also actuallyall of the detailed nuances of
how all these AI agents worktogether to actually complete a
call it's actually really,really hard to pull off, really,
really hard to pull off.
When you think aboutnegotiation, when you think

(42:05):
about sharing details of theload, when you communicate
appointment time flexibility,all that infrastructure we've
built.
So could a CH Robinson buildthis?
Absolutely, it would probablytake them a couple of years to
catch up to where we are, and atthat point I'm like, why not
just get ROI today?

Speaker 1 (42:28):
Yeah, well, help me understand what you mean by the
AI.

Speaker 2 (42:29):
agents work together yeah, it's a great question.
This is like getting reallynuanced into how we run our
product without giving out toomuch of our secrets.

Speaker 1 (42:40):
Sorry, I don't want you to give up your secrets, but
I just I want to understandkind of what you mean, because
this is more me as a curious,non-technical person and I'm
sure my audience is curiousabout this stuff, certainly not
trying to give you a tradesecrets, but keep that in mind
as you answer.

Speaker 2 (42:57):
I'll share what I can , so.
So, basically, in order to dothe things that we need done
well, like whether it be a trackand trace call, making
decisions around what types ofquestions to ask in that call,
making decisions around how toroute calls, depending on the
type of negotiation, the type ofload it's not just one AI, it

(43:22):
actually could be dozens of AI,which, from a carrier
perspective, it doesn't soundlike that Carrier perspective,
it's just they're talking to oneAI the whole time.
On our end, we're actuallyhanding off between lots of
different agents who areevaluating the outcomes of prior
agents and making decisions onhow to move forward.
So that's not really liketotally secret sauce.

(43:43):
Our value is how we stitchthose agents together.
Um, our value is then how do we?
Also is actually reallyimportant for operators at
brokerages to really understandwhat the ai is doing on their
behalf and where they need tolean in as a, as an operator.
Right, because the ai can't doeverything for you, but it can

(44:06):
partner with you on negotiation,on vetting, and you can provide
input to it.
You can say, for example, agreat, great example of how our
customers partner with the AIlive.
So we're negotiating with thecarrier.
Let's say, a customer marks aload as a hot load.
Right, you're like I'm willingto take things above my max rate

(44:26):
because this load's reallyimportant to me, or this
shipper's really important to me.

Speaker 1 (44:30):
We'll send a Slack message or a Teams message to
our customer, to the rep on file, on that load, and we'll say
hey, Joey, when you say weyou're talking about an AI agent
is sending a Slack message, Yep, okay, keep going.

Speaker 2 (44:47):
If it was we man, I we'd have to hire a lot more
people to to send slack messagesjust trying to understand.

Speaker 1 (44:50):
Yeah, just trying to understand um, that's good.

Speaker 2 (44:53):
I was like, man, do we need to change our hiring
plans?
Um, no, so yeah.
So rai will send a slackmessage to the operator, say hey
, uh, you know.
Hey, joey, we've got thiscarrier on the line.
Here's the rate, here's whywe're sending you a message.
The load is hot.
Joey can then respond and saytake that rate.
Or hey, try to negotiate themdown.
Or hey, ask them when and wherethey're empty.

(45:13):
We can collect all thatinformation.
So that's kind of how we letindividual operators at our
companies kind of scale theirimpact a little bit more.

Speaker 1 (45:24):
Got it?
And when you're out selling tonew potential prospects or
customers, what are you sellingas the differentiator for why
Fleetworks is the answer to them?

Speaker 2 (45:40):
Yeah, so I think there's maybe two sales.
There's like, why should youjust use Fleetworks in general?
And then maybe why should youuse us over any other AI agent
company?
Right, so why Fleetworks ingeneral?
I think, first of all, thecarrier experience when talking

(46:01):
to a brokerage can be amazing,but it can also without AI.
It can be amazing, but it canalso without without AI.
It can be amazing, but it canalso be really bad.
I've, I've called some of ourcustomers, their general carrier
line, saying hey, press one forit to talk to the care sales
team, and I've been on hold forlike three minutes, right, me as
a carrier.
Like that's not a goodexperience, um, so why?

(46:22):
Why should you?

Speaker 1 (46:28):
why should you use Fleetworks?
Well, number one, one that's awildly that's a wildly low
number to use as an example,because there's definitely
examples where it's 30 minutesand no one ever picks up the
phone but keep going.

Speaker 2 (46:37):
You're right, maybe I'm being too generous.
I appreciate the modesty inthat answer.

Speaker 1 (46:40):
I mean I've talked on the show about abandonment rate
and how brokers have in somecases an abandonment rate of up
to 20%.

Speaker 2 (46:48):
That's super low In those cases 20% is good.

Speaker 1 (46:52):
Well, 20% is good.
20%, I mean, if we're talkingabout abandonment rate as the
percentage of phone calls wherea carrier hangs up because no
one ever answers, I would thinkthree minutes is pretty good
relative to 20, 30, 40% of thecalls just never being answered.

Speaker 2 (47:10):
Yes, we've seen as high as 75% calls being missed.
I'd say average wait time for acarrier, based on our data, is
two minutes of wait time beforethe carrier just hangs up and
just calls the next broker downthe line.
Got it Got it.
So we've certainly seen crazywait times.
Why should you use Fleetworks?

(47:31):
Number one we solve the waittime problem for you.
Number two we actually solve amassive data problem for you.
When you're calling out tocarriers or when you're taking
inbound calls from carriers,your reps are too busy to take
that call and in the same breathlog into their TMS and log that

(47:51):
offer or lack of offer in thesystem.
Right, like, everyone wants thereps to do that, but the reps
just like don't have time.
The reps are trying to do a lotwith their day and so you're
losing huge amounts of data.
So we help our customersincrease data captured per lane
anywhere from 2x to 10x on someof your hottest lanes.
So we help our customersincrease data captured per lane
anywhere from 2x to 10x on someof your hottest lanes.
We have customers who in agiven week, we might give them

(48:12):
100 offers on a lane and that'sactually a signal for them.
We say, hey, go to a customerand get more freight there.
And also, you might want tothink about what your carrier
pay actually looks like on thatlane, because there's clearly a
lot of demand that you're justlike not tapping into.
So that's so.

(48:33):
We kind of help the carrierexperience, we help the data
piece, but the other thing islike we also just help our
customers become infinite in away that like was never really
possible.
So what could you do as abrokerage if you could call
every carrier and understandtheir preferences?
What could you do as abrokerage if you were not rate

(48:57):
limited by track and trace calls?
What could you do as abrokerage if documents were
automatically parsed?
What could you do if every sopthat you dreamed of was executed
on time and the data wasinputted back into the tms?
Um, and I think it's reallythat level of possibility.
That has been like that's beenthe most rewarding part for me

(49:18):
is like I, when I was in chicagotwo weeks ago, I was mostly
talking with with a lot of ourcurrent customers and I think
the common theme was likeFleetworks does carrier sales,
fleetworks does track and tracefor us.
How else can we deploy thetechnologies?
I think we're in just I feellike a very rare and, frankly, a

(49:41):
very humbling position whereyou know this, when your
customers are coming to you andasking how else can I use your
product, like that's a really, Ithink, great place to be
because the team works hard,right, and it's gratifying that
when we work hard, customerscome to us and say you've earned
our trust and let's go deeper.
But it's also a greatopportunity for the business,

(50:04):
right, because as we do more forour customers and the
relationship really up levels.
But it's also a greatopportunity for the business
Because as we do more for ourcustomers, the relationship
really up-levels.
The ROI from Fleaworks is soobvious that I don't even have
to necessarily go out and doanother business case.
For me it's just a no-brainerof.
I want to use Fleaworks as muchas I can.

Speaker 1 (50:22):
Basically, what does the customer base look like
today?
How many brokerages are you inwith?
How?
How big is it?

Speaker 2 (50:31):
yeah, um, we're we're millions of dollars in revenue.
Um, we have a few dozenbrokerages, some big logos that
I cannot share right now.
Um, but I would say thatbasically every brokerage of
meaningful scale is either usingus or considering using us, and

(50:56):
so it's been awesome, it's beenreally fun.

Speaker 1 (50:59):
That's impressive.
I mean millions is a big numberfor the time that you all have
been in business and certainlymust feel validating.

Speaker 2 (51:09):
For sure.

Speaker 1 (51:11):
Where do you see the product is fully baked and where
do you see there needs to be?
There's more room to develop.

Speaker 2 (51:19):
Yeah, the product is not fully baked anywhere, which
is a weird answer because we'rewe're selling this product.
I think the product worksreally well, but I there is it's
.
It's an insane problem to have,as like as a former product
person, um, the prioritizationthat that we have to do is is

(51:43):
really interesting and excitingbecause, like I just think
there's improvements everywhere.
For example, outbound calling,how to get just more accurate on
outbound calling, or looping inthe operators, or capturing
appointment time flexibility.
I just think what a broker cando or what a brokerage does is

(52:04):
so complex that I just stillfeel like we're we're in.
I feel like we're in the secondinning.
You know, I think the firstinning was does this thing work?
I think the second inning wascan you get more nuance?
I think we're in the bottom ofthe second.
We're maybe getting to thethird inning where I just think
there's vectors of improvement,um, on every possible channel.
Um, and I'm just really excitedparticularly about helping our

(52:27):
customers get smarter abouttheir networks.
Like that's really I think thebest brokerages are great at
network management and we wantto help all of our customers get
there.

Speaker 1 (52:42):
So I definitely see.
I mean the idea that yourcommentary around help you be
infinite.
I don't know why I started likeenvisioning Tony Stark and like
Marvel as you've said that.
Yeah, or Thanos, I don't know,but I see what you're talking
about and I see how much datayou can collect using this and

(53:06):
how much more reach you can haveusing tools like this.
And I guess what I'm curious isI'm curious of a number of
things.
Let's start with thecompetitive landscape.
So you know, I've asked prettymuch every AI company on here a
question of this nature, so I'msure you're not surprised to

(53:27):
hear it.
But how do you think about thecompetitive landscape?
You've got at least one majorcompetitor in Happy Robot that
just raised, I think, 15 millionbucks or something like that
and an $85 million valuation,which is huge.
Congrats to them.
You've got I just interviewedDave Bell has clone ops.

(53:47):
I think that might've been whatinspired you to message me like
yo, can I get on the show?
Like, and you know, in thatexample that's a brand new
company hasn't launched theirproduct.
I think they're launching theirproduct soon and it's, you know
, a guy with like 30 years ofindustry experience and a lot of
success, and then I'm surethere are more coming that I'm

(54:08):
not aware of.
So how do you think about thecompetitive landscape?
And like, how does, how doesthe competitive landscape impact
your decision-making for howyou approach the business and
how you approach growth,fundraising, hiring and such

(54:29):
You're absolutely right.

Speaker 2 (54:30):
I think any opportunity that is worth
chasing is going to bring, Ithink, great competition.
I wish I could share more onour fundraising, but we're not
public about that just yet, butmore to come soon.
The yeah, I think overallintense focus on the carrier

(55:15):
relationship and how that brokercan build, nurture and grow
that relationship with carriershas been critical for our
business.
So I mentioned this earlier.
But everything we do andeverything we did at Uber
Freight and everything we dohere at Fleetworks is really
carrier first and carriercentric.
That's kind of why customerstend to choose us is because

(55:38):
we're not just a voice AIcompany.
We don't believe in spammingcarriers.
We believe in helping ourcustomers actually grow
meaningful relationships andgrow meaningful networks.
So that's really our main goal.
There's a bunch of AI companiesI think there's only, to your
point, I think, two thatactually have real working
products publicly, and I thinkour speed of execution just

(56:03):
continues to be just absolutelykiller.
I mentioned this earlier.
We have seven technical folks.
They're all former founders,which means, yes, we have seven
people, but technically thoseare actually like 20 or 30
people worth of work, and so ourability to attract great talent
continues to be like my numberone priority as a CEO.

(56:24):
The reason we can attract thattalent is because we started
from a really high base and thenwe can pay well above market
because we only hire top 1%talent.
So instead of hiring two peoplewho are good, we're just going
to pay a top person like 50 to75% more, and so our salary
ranges are going to be competingwith, like the big tech

(56:46):
companies.
Because we can afford to dothat.
Folks are really attracted to usbecause we're already
profitable.
You know, in a really shortamount of time we've built up
enough customer trust and Ithink ultimately, the thing that
for me that really sticks outis again, all of our customers
come to us and say how else canI use Fleetworks?
It's that proactive outreachthat every single day and for

(57:11):
sure the competition is intensebut every single day the fact
that our current customers aresaying how can I use Fleetworks
more?
Why is this working the way itdoes?
And basically just saying, hey,we want to spend more with you,
we want to grow with you.
I feel really good about thatdirection.

Speaker 1 (57:32):
But it's early days, yeah, I mean I.
Yeah, good about that direction, but it's early days, yeah, I
mean I.
Yeah.
Yeah, no, I mean I commend anyany.
I'm a big believer in justfollowing the customer and if,
if the customer is giving youfeedback that your team's doing
a great job and that they wantto see more from you, then you
figure out how to give them more, and it's it's part of why I'm
curious.
I have two questions here, butone is around.

(57:53):
It's interesting that youtalked about the hiring process
and how you're able to pay morethan the average company would
be, how you know there'scertainty that more is coming.
Is there not a temptation to goraise a lot of capital and turn

(58:22):
seven really strong technicalpeople into 25 really strong
technical people and then youcan go faster and bigger and
more expansive and get your armsaround the industry faster?
So it's harder.
You have maybe a deeper moat atthat point, like how do you
think about the idea of you'sharder?
And you have a maybe a deepermoat at that point, like how do
you think about the idea of youknow what you're doing versus
something more aggressive?

Speaker 2 (58:39):
yeah, um more to share on fundraising soon okay
that's the whole answer.
That's the whole answer, okay,um.

Speaker 1 (58:53):
Okay, all right, then let me ask you a different
question then.
How do you contemplatenavigating pricing in an
environment where morecompetition is coming?
But whatever dollars per callor per minute you're charging,

(59:14):
or cents per minute or cents percall, someone may come in and
offer a cheaper number.
How do you navigate that kindof idea as you build out a
product like this?

Speaker 2 (59:28):
That is a great question.
We spend a lot of time thinkingabout that as a company.
So, first of all, we've alreadyheard that some folks are
trying to give away this productfor free I'm not exactly sure
who.
To me, that doesn't really makesense.
I think the folks that we tendto partner with they understand

(59:50):
that they're putting the trustof their business in our hands
right Like we are their front ofhouse and that inherently has
value to it.
And our customers, like the waythat we think about our revenue,
is our customers investing inus, like they're giving us the

(01:00:11):
resources to go out and hiremore people and support their
business and build, like reallydeep products that support the
business.
Um, as we kind of think aboutmoats, um, there are a few
things, um and I'm thinkingabout what I could, what I want
to share publicly versus not but, um, overall I I think there's

(01:00:34):
a bunch of moats in thisbusiness.
No one has switched away fromus and switched to our
competitors.
Now it's possible, comeyear-end renewal time, customers
might evaluate what we do withour customers is.
Our product is so deeplyintertwined with how they do

(01:00:55):
business and how they covertheir freight and how they think
about managing their freight,that to pull us out, um, it's
technically possible, like, like, people switch their TMSs.
Um, sometimes I don't thinkanyone has ever pulled out their
TMS and said, wow, that waslike a great experience and
incredibly easy and not painful,like pulling Fleetworks out is

(01:01:18):
painful because, like, we'redoing the job of some of your
people and so you know, gettingrid of us would be like pulling
out, you know, dozens of carrierreps, like, or, if you're a
large brokerage, hundreds ofcarrier reps.
And then saying, okay, I'mgoing to bring on a new provider
or I'm going to go hire peopleto fill that gap.

(01:01:41):
And as we find that ourcustomers build processes around
the data and the execution thatwe help them with, we find that
customers tend to just bereally happy.
And I think my promise alwaysto my customers is hey, we're
always going to price fairly.
We're going to price fairly.

(01:02:03):
If we actually feel likethere's an opportunity to lower
prices for you, we may do that.
And ultimately the ROI that wedemonstrate for customers is
kind of a no-brainer.
So if someone comes in for onepenny cheaper a minute or 10
cents per load cheaper, ourcompetition cannot provide a 10x

(01:02:24):
better product.
So that's kind of how we thinkabout it.
Yeah, that's fair.

Speaker 1 (01:02:30):
I'm curious if the product is able to do the job of
dozens or in some cases it'sscaled brokerages hundreds of
carrier reps.
What does the shift look likewithin the company when they
deploy Fleetworks?
If I'm a carrier rep, am Iworried for my job when
Fleetworks gets installed, or ismy job just fundamentally

(01:02:52):
changing into somethingcompletely different?
Help me understand what thatlooks like.

Speaker 2 (01:02:57):
Yeah, it's a good question and I think it's really
good timing given where themarket is.
So, no, secret market'sterrible.
Like everyone, I think everybrokerage had to make or a lot
of brokerages had to make prettydeep cuts.
A year or two ago Feels likeconsensus is we kind of hit the

(01:03:20):
rock bottom.
Things are coming back up.
I think this is a great time toinvest in a platform like ours,
because you bring us on andsuddenly your hiring plans
change.
It's not really about firingpeople.
It tends to be.
I mean, we have seen peoplechange workforces, but I think
those are companies who justfelt like they were really
overstaffed anyway.
For most of our customers, it'smore like, hey, we like our

(01:03:45):
people and we've trained them upreally well and we don't want
to go through the pain oftraining from scratch more
people.
So let's use our existingpeople.
Let's shift them to actuallydoing more meaningful work.
Instead of my carrier repsspending 25% of their day doing
track and trace, 25% handlingcall-ins off of postings, 25% of

(01:04:06):
their day shooting the shit and25% of their day doing outbound
calls and outbound emails andbuilding relationships, let's go
more 25% of the day shootingthe shit, 75% of the day
building relationships right,and so that's the calculus that
you know a lot of our customersare making.

Speaker 1 (01:04:27):
And how does, like you mentioned that you want to
be very carrier-centric and helpdevelop or evolve the
relationship between the brokerand the carrier.
It just naturally feels like aproduct like this detracts from

(01:04:48):
the relationship Right from therelationship right.
It theoretically removes a lotof the human conversation that
has to happen in a load bookingprocess.
So help me understand how therelationship can actually be
improved through a product likethis.

Speaker 2 (01:05:05):
I love this question because it's so foundational to
what we do.
I think when we started, like Isaid, there were doubts like
are carriers even okay with thisprocess right?
And I think when we started,like I said, there were doubts
like, are carriers even okaywith this process right?
And I think, fortunately, weproved that they are right and
if we didn't, we wouldn't evenhave a business.

(01:05:28):
When I built relationships withcarriers, it's a two-part,
three-part process.
I think number one is the datathat you collect about the
carrier where they like to run,what their equipment type is.
Number two is the execution onthat data.

(01:05:49):
And then number three and whatI mean by execution on the data
is like you, you you actuallytender the load to the carrier
when you have to give thembusiness.

Speaker 1 (01:05:59):
Yeah, you have to give them freight.
You understand.
You understand their needs andwants.
Yeah, that's step one.
Yeah, step two of therelationship is actually like
executing an order together,leveraging the information
they've given you.

Speaker 2 (01:06:11):
I'm with you, keep going and part three is what's
your dog's name, what's yourwife's name, what's your kid's
name, what's your favoritesports team?
Like?
I think ai can do number three.
My general approach is it, it,I think it's, I think it's funny
, but I don't really want toinvest in it.
Um, my approach is ai candefinitely do number two really

(01:06:32):
well, so we can definitely donumber two and we can definitely
do number two really well.
So we can definitely do numbertwo and we can definitely do
number one.
So we can help you collect data, or we can be a repository for
your data and we canconsistently be that execution
layer that helps you execute onthe data that you collect.
And so, andrew, if you're goingback to the brokerage floor and

(01:06:54):
you're working at Ally Logisticsor Capsule Logistics or any of
our customers, I think your rolechanges.
I think your job is to developcarriers and put that data into
Fleetworks to help you make moremoney, more money.
We're going to help you makemore money as a carrier rep
because we're going to help youbook a lot more consistently

(01:07:14):
with owned carriers.
And then what you tell thecarrier is hey, man, I'm going
to have an AI reach out to you,but you're in the routing guide.
You're number one in therouting guide, so you're always
going to get this load before weput it out on the open market,
and carriers appreciate that.
Me, as a carrier rep, I wouldsometimes forget to tender that
load to the carrier if it waslike an informal agreement,

(01:07:36):
right, because I had just a lotof things going on, and so we
consistently help our carriersdo that.
But if we free up the carrierreps time to say hey, joey, like
if you ever need me, I willalways be here and my time is
more available now because I'musing AI to help me book freight
.
So I'm using AI to help me bookfreight, so I'm always there
for you, but AI is going to bemy assistant and you can always

(01:07:57):
tell the AI connect me to Andrew, and we always will.

Speaker 1 (01:08:03):
So let me just say, hearing that kind of explanation
the three parts I am 100% soldthat, if the technology can do

(01:08:30):
as it's intended to, this is ahome run solution to evolve a
carrier rep's time and by evolveI mean make it more efficient
and allow you to do more.
I've spent years as a carrierrep and I've had some really
strong relationships withowner-operators and I still, to
this day, can call a number ofthem and I have their numbers
memorized and they would do whatI asked of them if I needed

(01:08:55):
them and I would do what theyasked of me and, and that was a
product of just relationshipsbuilt over time.
But that was like a gritrelationship.
That was me calling them allthe time, understanding their
lanes, memorizing it, a millionnote cards and I had as good a
tms as anything at bazooka, atcoyote, and and and I could have
logged it, but my process itwas just easier to do the notes,

(01:09:16):
as I think about this one theability to get seemingly
infinite information fromcarriers on where their trucks
are going to be, what lanes theyjust got from new customers
that they need backhauls for,whatever.
I mean.
There's clear value in beingable to call more carriers and

(01:09:38):
get more information, housingthat information as a repository
and then using it to make moredecisions.
I mean that's another big win.
And the ability to againinfinitize it.
That's not a word, but like tomake it infinite, to make it so
you'd never miss the calls.
There is so much data that ismissed from brokers because,

(01:10:02):
like you said, the abandonmentrate can be up to 70%.
I've seen 20, 25, 30, whateverit is.
It's a big number.
It's a meaningful number thatif you can replace a missed call
with an answered call,information provided and taken
in and then saved and used tomake better decisions, that's
another home run.

(01:10:23):
The third piece is thinkingabout the actual carrier rep.
And that's where I'm puttingmyself back in the shoes that I
sat in 15 years ago andrecognizing that there's so much
time I spent gathering theinformation.
And if I just had theinformation in front of me and I
could spend my whole daycalling the right people who I
already knew what theirinformation was, and my job was

(01:10:46):
solely to buoy them up or becometheir friend whether it was a
man or woman, it didn't matteror become their friend whether
it was a man or woman, it didn'tmatter and you know there's so
much value to that and I see howthere are certain things Like,
for example, you know I rememberone of my carriers, peter
Achukwu, and his wife Catherine.

(01:11:07):
They used to do a lot of localSoutheast Coca-Cola stuff for me
.
They were based in Marietta,georgia, and they would have to
go to the Coca-Cola Atlantafacility and I've talked about
this facility, for he hated thewoman who ran the facility.
He said she was an asshole andwas a real pain in the butt and
we used to always put them onloads that the appointment had
already been missed.

(01:11:27):
Like AI can get me to the pointof matching him to the load and
making me, letting me know thatI should call him and convince
him to take the load, becausethat's what it was at that point
was like I knew he didn't likethe load.
I had to lean on our friendshipto make that happen and I don't
want ai talking to him aboutlike, oh, the lady at the
facility, like he and I can havethat that's the personal

(01:11:49):
element to the conversation isaround the nuance of the load.
That's not exactly.
I mean you could call it a datapoint, but it's.
It's.
You know, it's something thatfeels a little bit different.
That AI wouldn't be involved inis like the idea that there's a
person there that's a pain inthe ass or that you're going to
be waiting a long time.
That's where I want to talk toa person who has compassion, so

(01:12:10):
I can have compassion for thefact that Peter would have to
wait six hours to get loaded andour conversation is going to be
a lot more productive if I'munderstanding what he needs for
that versus an AI.
I think I just don't thinkthat's where that plays.
So, yeah, this is my I guess mystamp of approval.

Speaker 2 (01:12:34):
I don't know.

Speaker 1 (01:12:34):
I was trying to think of the word yeah, whatever of
the idea, because my brother andI at one point were arguing
about this on Twitter orsomething, where he made the age
old argument of anytime I callan airline or the bank and you
know, a robot picks up.
I'm yelling agent agent wantingto talk to a person, and I've
been there, I've been thatperson.

(01:12:55):
I've frustratingly said agentover and over again until they
put an actual person on thephone.
But I think there's proof inthe pudding.
I mean, how many phone calls ona daily basis?
Or just give me a number ofphone calls that have
successfully been executedbetween Fleetworks and carriers,
even if it's not exact.
Give me a number of phone callsthat have successfully been
executed between Fleetworks andcarriers, even if it's not exact

(01:13:17):
, it's a number that representsthat, I believe, the market is
open to this.

Speaker 2 (01:13:21):
I mean millions.

Speaker 1 (01:13:23):
Exactly, it's millions.
So if millions of calls havetaken place where a driver was
okay with the voice AI on theother end, that's a large enough
sample size for us to say thatcarriers in general are going to
be open to this and therefore,with the type of return it has,
it's coming.
It's coming to every brokeragenear you.

(01:13:43):
So I guess I'll ask a questionnow, given I just kind of went
on a little rant there what doyou see as the long-term impact?
So let's say I'm Joe's Trucking, I've got 10 trucks, I'm based
in Nampa, idaho, and everySeptember my phone starts

(01:14:08):
ringing off the hook fromanybody who's taking onion or
potato loads, potato loads outof the Northwest and they're
seeing if I'll come help themwith my 10 reefers.
But once every broker haseither Fleetworks or your
competitors and they all haveset up this outbound data
collection process, am I notgetting a phone call 400 times a

(01:14:31):
day by people wanting to talkto me?

Speaker 2 (01:14:35):
It's a good question.
I think there is danger of that100% Couple thoughts there, I
do think.
Well, first of all, actually, Iwant to go back to something he
said before.
It sucks when I call because Iactually like doing things over
the phone.
I like calling support on thephone, and it's so frustrating

(01:14:57):
as someone who has built apretty successful voice AI
company that I still run intoold school like press one.
If you want to talk to bookings, I'm just like God.
Can you guys just use thistechnology so that I can get my
job done?
It sucks because I was likeanother startup needs to come in

(01:15:18):
and sell to Comcast and Unitedand all those guys.
So that's my rant.
But to get to your question, Ithink your phone could be
ringing off the hook.
This is our job at Fleaworks andwhy I'm really emphasizing
being carrier.
First, it's our job tounderstand number one how does

(01:15:41):
that carrier like to becontacted?
So they might not want a phonecall, they might want an email,
they might want a text message.
So we want to be wherever thatcarrier wants to be.
Beyond that, I do think wemight want to be wherever that
carrier wants to be.
Um, beyond that, I do think, um, we do.
We might move to a world ofcarriers being more platform,

(01:16:02):
more like I don't even know whatthe term is like platformized,
um, like, I think, like convoyhas obviously built like their
platform, uber freight's gottheir platform.
Um, I don't want to open thatcan of worms.
I think you had the LinkedInpost of the century last year
when Uber came out with that.
But there's all these carrierplatforms and I think because we

(01:16:27):
help our customers book so much, freight carriers may come to
us and we may help them bookfreight easier without a phone
call.

Speaker 1 (01:16:41):
So you're saying there's a world where your own
business drives away the phonecalls that are happening in the
business.
I mean, I don't mean to say itlike that, but there's a chance
that you have so many calls thatyou're creating for customers
that you now need to create anew solution to help carriers

(01:17:04):
get away from the calls.
Quite possible, yeah.
Or you have to create the sameagent to take the calls on
behalf of the carriers.

Speaker 2 (01:17:15):
Totally yeah.
The problem is that carriersare just, they don't have like
small carriers don't really havea platform today, and that's
why the phone calls are sopowerful is because that's the
only way to reach the carrier.
So I think more to come on that.
I also think that, frankly, thegovernment does need to catch
up to this in a way.

(01:17:35):
The laws that govern AI phonecalls were written in the 90s
when robocalling became aproblem.
I think those laws are prettyantiquated, obviously, because
those calls were literally spamcalls, but you could have AI
spam.
But I don't think we'respamming, I think we're trying

(01:17:57):
to do business and I think thegovernment needs to create
either industry frameworks oruniversal frameworks to regulate
this, because otherwise I thinkyou could certainly have bad
actors who are not carrier first, um, and who who are kind of
unscrupulous and who are goingto just be uh you know,

(01:18:18):
literally downloading the fmcsadatabase and just clicking call
on 300 000 active carriers,right yeah, I mean I like why
wouldn't someone do that?

Speaker 1 (01:18:31):
actually, you could create an interesting business
if you just created what you'vecreated with your voice AI agent
and then you just go collectall the data from the carriers.
I mean it'd be messy, but thatwould be interestingly valuable
data and I'll use that as asegue to a question.
Is there any avenue for you totake the data that you're

(01:19:07):
collecting and leverage?

Speaker 2 (01:19:08):
it in a way that is so.

Speaker 1 (01:19:09):
I interviewed.
Wait, let me make sure this ispublic.
Yeah, it is.
It is Part of the green screensstrategy is kind of helping all
the small brokers that theypartner with aggregate their

(01:19:29):
data so that they get a.
They have a small piece of abig pie, but the pie gets bigger
every time there's a newprovider who signs up and
therefore the data gets betterbecause they're all putting data
in and they're all being ableto leverage that data to get
better pricing.
Do you get what I'm saying?
Is there an avenue for if I'mAlly Logistics and I have call
it a thousand calls a day, thatFleetworks is doing for me, I'm

(01:19:49):
only as powerful as the datathat comes from a thousand calls
.
But if I'm Ally and I'm part ofa network of 30 Fleetworks
customers, that a thousand callsbecomes 100,000 calls a day.
Is there an avenue for all ofthat data to be leveraged by all
the customers?

Speaker 2 (01:20:08):
I think there are opportunities.
Yeah, how do you think about it?
Because I think data sharing inthis industry is both common
practice but also maybe a littletaboo.
So I'm curious how do you thinkabout that, and what data
should be shared versus shouldnot be shared.

Speaker 1 (01:20:28):
Yeah, I think it's an interesting question, which is
kind of why I asked it, but Idefinitely think that there are
two trains of thought, or maybethere's more than two trains of
thought.
I think that a lot of brokersthink their carrier capacity is
their differentiator and thedata on their carrier sourcing

(01:20:48):
is a differentiator.
And I get why your networkshould be a differentiator.
There's not a ton of otheroptions for differentiation.
There are a few, but not a ton.
How you run your business, therules you use to govern, how you
execute for customers thingslike that, how you engage your
employees but that's not thepoint of the conversation.

(01:21:09):
So I could see why a brokerwould say absolutely not, don't
share my data with anyone else.
That's not the point of theconversation.
So I could see why a brokerwould say absolutely not, don't
share my data with anyone else.
That's mine and I want to useit for myself.
But alternatively, especiallyon the smaller broker side, you
want to leverage whatever pieceof information you can get and
you can't compete with the CHRobinsons on the data front.

(01:21:31):
So I could see why they'd bemore open to it.

Speaker 2 (01:21:36):
Yeah, I think it's on us to come up with the right
rules of data sharing.
Certainly, we've got some megacustomers and they've expressed
concerns I think very valid,about hey, I don't want my data
being shared with a brokeragewho does 50 loads a day right,

(01:21:56):
because they're getting morevalue from the data than we're
getting from their data.
On the flip side, I think it'sa good point.
On the flip side, uber Freight,to your point, has spent
hundreds of millions and, if wecount TransPlace in the equation
, billions of dollars buildingthis business.
They still pay DAT a lot ofmoney for access to their data,

(01:22:17):
a lot of money.
And so, clearly, even UberFreight, who, despite all their
investment, has gotten to 1.5%of the brokerage market roughly,
despite all their investment,still not a market mover Could
they benefit from 40 otherbrokerages lumped together under

(01:22:40):
one tool?
I think, maybe.
I think maybe We'll have toprove it with them that when
they access our data, they canprice more accurately and better
.
That's kind of how I thinkabout it.
I certainly think there's a lotof openness from I would call
the more small, mid-size, likethe $100 to $300 million

(01:23:01):
brokerage.
They understand that, hey, oursecret sauce is kind of like our
sales team and how we serviceour customers.
And, at the end of the day, ourcarrier network is tiny
compared to the overall market,so if they can use Fleetworks to
tap into a broader data pool, Isee that as like a win-win.

Speaker 1 (01:23:21):
Is that an offering?
Today, though?
Are they able to tap into alarger pool?
Not yet.

Speaker 2 (01:23:26):
Not yet Okay.

Speaker 1 (01:23:27):
Yeah, still looking at it.
Okay, and when you think aboutthe product today, everything is
centered on voice, right?
I mean, are you thinking aboutdoing some of the other stuff to
compete with, like the you know, just to speak to my former
guests like the Vumas and thedrum kits of the world?

Speaker 2 (01:23:53):
outside of voice.
We're already executing on ourvision of meeting carriers where
they are.
Email is going to be a bigchannel, text, whatsapp those
are all really common channelsfor carrier communication.
Voice is obviously just like aslam dunk and it's going really
well and that's still why a lotof customers come to us.
But all those products arealive and well.

Speaker 1 (01:24:17):
But in terms of that's a good point.
But okay, so you mentioned allcarrier-facing, though Is some
of the stuff that the Vuma andDrumkit guys are doing are
focused more on the customerside of the house?
Are you dabbling in thecustomer side of the house or
everything is stillcarrier-centric and planning to
stay carrier centric?
Or tbd, maybe fundraising, whoknows?

Speaker 2 (01:24:38):
sure I love fundraising, as you know, as my
as my mysterious answer look, Imean I think I think here's the
thing that that I will say aboutit is like first of all, we see
our core mission as connectingcarriers and brokers.
If talking to customers orengaging with customers enables

(01:25:00):
better outcomes for coverage andcarriers and more economic
opportunity for carriers, we'llabsolutely go that direction.
Given how nimble and sort ofwell-executed our team is so far
, I could see us going into thatpath.
I guess what we're calling moreagentic workflows and building

(01:25:23):
operational processes orrebuilding processes using AI.
Absolutely, like I said, I thinkwe're in the bottom of the
second in terms of how dobrokers connect with carriers,
and so I would say, if acustomer wants us to do email

(01:25:45):
quoting automation for them inFebruary 2025, I would say you
should 100% go with Vuma, but ifyou want the best product that
enables you to cover yourfreight cheaper than a human,
both from an efficiencystandpoint and a gross margin
standpoint, you should go withus.
That's kind of a no-brainer Isit an or or?

(01:26:07):
It could be an and it can forsure be an, and we have many
customers that use Vuma for someof their core products and they
use us for our core products.

Speaker 1 (01:26:17):
Okay, got it.
What's been the mostchallenging element to selling
technology into freight brokers?

Speaker 2 (01:26:31):
probably the number one right now is just how tough
the market is.
I think you have a lot ofbrokers who are on tech pause,
as they're like we need to seewhen this market comes back and,
to your point, it's not aquestion of if, but rather a
question of when.
So I think it's a timing thing,but look, I'm still really

(01:26:52):
happy about the team's processand progress, despite the fact
we're in the worst freightrecession.
Coming out of the worst freightrecession in recent memory.
That's a tough part.
I think we're also veryfortunate that we're coming in.
If we were selling this product10 years ago, I think a lot of

(01:27:13):
the core technologies, likeparticularly the TMSs, were not
originally built to supportintegrations of this magnitude
and of this speed.
So we're very fortunate thatthe TMSs all have the capability
now to support a product likeours, and so I'll actually, as a
piggyback on that, I thinkpeople have been really burned

(01:27:37):
by bad technology in thisindustry.
We come to people and they'relike how do I know what you're
saying is true?
How do I know I'm going to getthe ROI?
I'm like, look, man, just tryit, we could integrate.
I love the story of LGI and, ifyou know Brandon Bay there he is
a true homie.
Brandon was very public that wefrom signing to when we handled

(01:28:01):
their first call from them, sowe did the whole integration and
operational process and launchin 22 hours, and so our goal is
to really elevate the bar onwhat a tech vendor can do in
this space.
So that's the hard part isactually we're selling against,
I think, the missteps of a lotof companies who came before us.
But I think that just comesdown to having a great team

(01:28:25):
building customer trust andcontinuing to just rebuild
customer trust over and over.

Speaker 1 (01:28:31):
Yeah, great answer.
All right last two questionsfor you, and they're kind of go
hand in hand, both sides of thesame coin.
What would you say is thenumber one thing a happy
customer is saying aboutFleetworks?
What are they raving about?
What do they love?

Speaker 2 (01:28:49):
Number one they're like God damn, this thing works.
That's the first thing.
Number two I're like goddamn,this thing works.
That's the first thing.
Number two, I think, is goingto be just communication and
support.
We set up Slack channels orteam channels with all of our
customers.
We're just continuing to win onhow we communicate with our
customers, how quickly we canprioritize their work and how we

(01:29:13):
can build around their processso the product works.
The support is great.
You have access to the wholeteam whenever you join with us.
And then, number three, I think, the speed of new product ads.
I think a lot of people goingback to prior vendors a vendor
does one thing for you, right,and their product doesn't evolve

(01:29:35):
.
To be honest, I'm stillcatching up on trying to.
I'm communicating to ourcustomers all the new things
that we're bringing to the tablefor them, and so I think a lot
of customers are like God damn,whether we onboarded with you
three months ago or we had ourfirst conversation three months
ago.
I need to tell them hey, I needto run a new demo with you,

(01:29:56):
because what I'm going to showyou now is different than when
you first talked to me back inSeptember, october.
So, yeah, it's going to be theproduct works, the customer
support and just the speed ofnew build.

Speaker 1 (01:30:12):
Smart way to ask for one thing give me three, because
it gives you a chance to bragabout the business a little bit.
Yeah, because now you got toanswer the hard question, which
is what's the number one thingthat customers are complaining
about or frustrated about?

Speaker 2 (01:30:27):
What is the number one thing?

Speaker 1 (01:30:28):
And you don't have to give me three here, you can
just pick one.

Speaker 2 (01:30:31):
I mean, thank you for limiting it.
I could probably give you a few, but I think we could do a
better job at exposing tocustomers the rules that they
have built in our system or thatwe're building in our system
for them.
So they might ask, hey, why isthe AI doing this?
The team jumps in and we'relike, oh, yeah, it's because you

(01:30:52):
asked us to do that two monthsago.
And they're like, oh, thatmakes sense.
Or they're like, oh, let'schange that.
We don't want that rule anymore.
So I think we need to continueto expose more of that whether
it be customization or whetherit be rulemaking to our
customers.
But it's great that we're now,frankly, at the point where I

(01:31:15):
would say, 95% of customeroutreach is the product is
working as expected.
We just didn't do a great jobat exposing that and
continuously communicating it toyou.

Speaker 1 (01:31:31):
It's a funny answer, but I actually understand it
wholeheartedly as someone who'srun a brokerage and understands
how quickly we change our mindsabout things and how fast-paced
things are and how easy it is toforget.
You made that rule a month agoand now you want to change it
because some new element hasshown up that's costing you
money or time or energy,whatever it may be.
So I actually understand that.

Speaker 2 (01:31:59):
Yeah, we go super deep with these guys right.

Speaker 1 (01:32:02):
So their process is our process Awesome.
Well, I'll give you one more.
You've been a founder now, orCEO, of this business for a year
and a half, which can be a longtime in freight CEO world.
It certainly can feel like along time For other budding

(01:32:28):
entrepreneurs wanting to getinto the freight tech space.

Speaker 2 (01:32:29):
What advice do you have?
Getting into freight tech?
Number one advice come workwith us.
I don't think you're going towork with smarter, kinder, more
hardworking people than thepeople at Fleetworks.
If you're not going to workwith us, then you should go work
for another freight techcompany, one that's really high

(01:32:51):
growth, one that's small.
I think there's so many peoplethat come into the business and
they think they understand itand then they build a product.
They maybe get to a few hundredK or a million ARR and they
just dead hit a wall becausethey don't understand how
complex this space is, hownuanced it is.
So I think, if you've neverbeen in the space, joining a

(01:33:16):
company in the space for a yearor two to actually really learn
it is powerful.
I think if you have been in thespace, the number one thing
that you should do is talk toyour prospective customers or
talk to the stakeholders thatyour business is going to affect
.
I think if you take that monthto do respectful, tailored

(01:33:40):
outreach on LinkedIn like if youDM someone on LinkedIn, not
like a blast, but you say, hey,man, I see, you do this, I'm
doing this, I would really loveto talk with you for 15 minutes,
or can I just shoot you anemail with two or three
questions?
I think something like that cango a long way.
That's why we, going back to us, we don't do cold outreach, we

(01:34:03):
do very tailored outreach, we dovery personalized approach,
because people in the space areblown up by technology and if
you're going to build technologyin the space, you have to be
very relationship oriented andbe very respectful.
Or join Fleetworks and we'lljust put you in front of 20
customers within the first threeweeks All right, all right,

(01:34:27):
I'll take that answer.

Speaker 1 (01:34:30):
Any final thoughts before we call it?
I appreciate how honest andtransparent you've been about
the business.
It's a cool story.
It's a cool business and umseems like one you've you've got
a lot of traction with no,thank you.

Speaker 2 (01:34:41):
Thank you for having me.
I mean, look I um, it's anexciting space.
I think it's cool to see peopleit's it's cool to really like
have been part of this journeyfrom the very beginning not just
this company, but also how thistechnology is impacting the
space, because we're seeingtheir narrative really evolve
over the last two years.
I really appreciate theopportunity and looking forward

(01:35:04):
to seeing you at some show atsome point.

Speaker 1 (01:35:07):
Yep, absolutely.
Thank you, man To our listeners.
That's all we got.
Have a nice week.
Thank you, man, cool man, toour listeners.
That's all we got.
Have a nice week.
Thank you everyone you.

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Ep. #56: Paul Singer, CEO & Cofounder of FleetWorks

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