December 9, 2025 • 44 mins
The advent of artificial intelligence and machine learning has opened a new era of productivity gains for freight brokers, capacity owners and shippers. Supply chains are still in the early stages of adopting these tools, creating significant opportunities over the next several years. In this episode of the Talking Transports podcast, Augment CEO and co-founder Harish Abbott joins Lee Klaskow, Bloomberg Intelligence senior transportation and logistics analyst, to discuss how AI is reshaping the freight industry. Abbott outlines how Augie, Augment’s AI teammate, automates end-to-end brokerage workflows — from order to cash — while improving service levels and reducing costs. He also reflects on the challenges of scaling AI talent, the importance of change management, and how his early career at Amazon sparked his passion for fixing logistics’ inefficiencies.
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Episode Transcript
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Speaker 1 (00:07):
Hi everyone, this is Lee Clascow when We're Talking Transports.
Welcome to Bloomberg Intelligence Talking Transports podcast. I'm your host,
Lee Clasgow, Senior Freight, transportation and logistics analysts at Bloomberg Intelligence,
Bloomberg's in house research arm of almost five hundred analysts
and strategists around the globe. A quick public service announcement
before we dive in. Your support is instrumental to keep
bringing great guests and conversations to you, our listeners, and
(00:30):
we need your support. So please, if you enjoy this podcast,
share it, like it, leave a comment. Also, if you've
got ideas, feedback, or just want to talk transports, I'm
always happy to connect. You can find me on the
Blueberg terminal, on LinkedIn, or on Twitter at logistics Late.
I'm very excited to have with us today. Harish Abbott,
the co founder and CEO of Augment and AI productivity
platform for logistics. Augment has raised about one hundred and
(00:53):
ten million from Red Point Ventures, eight VC and leading
logistics funds. Prior to launching Augment, Harish co founded Deliver,
an e commerce fulfillment platform acquired by Shopify for two
point one billion dollars in twenty twenty two. His career
includes pivot roles at Amazon, where he contributed to building
global fulfillment infrastructure. He holds degrees from Indian Institute of Technology, Rookie,
(01:21):
the University of Illinois, and an MBA from Stanford. Welcome
to talking Transports, Harish.
Speaker 2 (01:27):
Thank you for having me. I'm excited to speak with
you here.
Speaker 1 (01:31):
Yeah, it's great to have you. Can you talk a
little bit about what Augment does.
Speaker 2 (01:35):
Sure, So, Augment is, you know, an AI productivity platform
for the logistics businesses. Our first product is Augie Augie.
Think of Augie as a teammate that can work twenty
four to seven across all modes in a business emails
(01:56):
and phone calls and text and messaging and your systems
record like TMS or w m S and it goes
and does work that is given to Augie as s
OPS or standard operating procedures is getting deployed to lots
of freight businesses today, mostly large freight brokers, UH freight
(02:19):
fleets and now shippers. Yeah, that's what that's what we
do and and reach.
Speaker 1 (02:27):
Can you talk about how you know a broker might
use versus versus a shipper?
Speaker 2 (02:34):
Sure so well, Like if you think about what does
a broker and do is you know their their job
is to match demand to supply and then execute against it.
They get demands from shippers of the world and then
the supplies are from several fleets, large fleets and small fleets.
They try to match them and then execute a shipment
(02:57):
end to end. Now, in the execution of the shipment,
there are multiple multiple steps today extremely manual. Right, there's
steps like, hey, I get a shipment in an email,
I need to now put that load up in a
TMS manually maybe or correct some feels from a load
that came through an EDI to Now I've got a shipment,
(03:21):
I need to now go source capacity for it. I've
got preferred carriers, I've got data on who's run these
lanes before. Or sometimes I get a load where I'd
never run this lane before, so I need to post
it on a public loadboard like DAT or truck stop.
(03:42):
Then there is this work of like hey, I've posted
the load, I need to now negotiate the load, go
back and forth to figure out how am I going
to make my margin on it. Once you figured out
like hey, this person is going to do this load
to this company. Then there's a whole execution step off.
I'm going to dispatch the load. I want to make
sure the driver understands how to get in. I have
(04:04):
to set up appointments for a load right on the
pickup side, on the drop off side. Then I have
to track the load. I have to keep updating the
customer on where the load is at, if there's delays,
what to do in terms of those delays. And then
when the load gets delivered, then there is the whole
paperwork cycle begins of collecting the delivery documents, collecting the
(04:26):
invoicing documents, and making sure if there's excessorials, detention lumpers,
those are collected so that the billing can happen fast.
So if you look at this life cycle for a broker,
you can now deploy Augie in any or all of
these steps, almost like a worker and saying, hey, Augie,
(04:51):
now you can be looking for all my emails and
look for tenders, and if you get a tender, maybe
start building the load in the TM And if you're
missing information, maybe you can come in and ask somebody
and saying, hey, I'm missing this information. What does this
shipper really mean, or go back and ask the shipper
so you can completely build the load. Or once the
(05:13):
load is built, like hey, just start working on capacity sourcing.
So collaboratively, work with the rep, understand their preferred carriers,
reach out to them, maybe post a load on a
dat get the incoming calls, take those calls, negotiate the load.
Some businesses say like pass the final negotiation to the rep.
Some people say, like, you can book the load, and
(05:35):
then like, let's start working on tracking the load or
tracing the load end to end, so making the dispatch calls,
understanding you know, the eled events, making the scheduling appointments,
and then all the way towards the end is like, hey,
the load's got delivered. Now we need to go and
chase documents. And you and I know nobody likes chasing documents.
Like we put Augie to work and it can chase
(05:57):
documents or our ds source or days sales outstanding can shrink,
and we can start money can start moving in this
business again and faster and quicker. So those are like
some of the use cases that people are using Augie
for today. As a broker. People are also using Augie
for like coding, you know, like they get lots of
(06:18):
requests for course, like hey, could you respond to my code?
Speaker 1 (06:22):
Okay, so just a quick commercial. You know you mentioned
DAT and truck stop on the Bloomberg terminal. O. The
data is available and it can be found at BI
spaceed trc k Go on the Bloomberg terminal. So if
you're interested in that data, we have a spot contractual
struggle with market data from those two data providers you.
Speaker 2 (06:40):
Know you mentioned.
Speaker 1 (06:41):
So there's like three main customers that you guys are
going after, the shipper, the carrier and the broker. Right now,
kind of what is the mix and kind of because
I know you're in growth mode, what do you think
the optimal mix would be three years from now?
Speaker 2 (06:55):
Yeah, I mean today, I think I would say sixty
percent of our businesses are brokers, right and they tend
to be the largest brokers about thirty five percent our fleets.
And then we're just starting to work with shippers, so
we're not as deep with shippers yet. I think as
(07:19):
we go forward, you know, our vision is that it
is not about I think step one Lee is about
taking this tedious, repetitive work off humans plates so they
can focus on more important things, right, that's what we're doing.
But if you imagine, you know, Augie's on a broker
(07:41):
side and a fleet side, and the two Augies can
now synchronously collaborate, then we can eliminate the need for
the phone calls and the text and the emails. Right.
So our mission is to make logistics better, and we
think the way to make that better is to get
to more real time synchronous collaboration between shippers and brokers
(08:07):
and fleets so that people can act faster. Right. So,
if you know your question was like three years from now,
I would sing three years from now, most of our
businesses like were equal mix of you know, shippers and
brokers and fleets, and we are really moving towards getting
all of them the signals they need so they can
(08:28):
act in their business faster. Right. Like as example would be,
well today, if a truck's running late, what happens is
and it's a broker load, the maybe the offshore team
or the overnight team at the broker has to like
keep an eye on it. If they get an alert
(08:49):
the truck's running late, then they might decide, oh, I
need to reset the appointment. The resetting of the appointment
means sometimes you can log into a portal. Sometimes it
means you need to email. And let's say, if it's
an email scenario, you email somebody, and if the receiving
warehouse is not working at that time, well till nine
(09:11):
am next morning, you're not going to get a new appointment.
So now the labor that the warehouse had planned is
going to get wasted because the truck's not showing up
on time. The truck when it shows up late, doesn't
have an appointment, so it might need to wait for hours,
sometimes days to be unloaded. And in the meantime, the
(09:33):
shipper's inventory is unsellable. Right, So everybody's hurting. The shippers hurting,
the warehouse is hurting, the truck guy is hurting, and
the broker's performance is hurting too because the shipper holds
them accountable. But now, if you imagine a scenario where
an augie on the broker side detects that truck's running late,
(09:57):
calls or synchronously communicates with an all on the warehouse,
I said, let's do find me a new appointment. That
appointment is now booked. The new the labor that was
allocated for the first appointment is reallocated to somebthing else
more productive, and now when the truck shows up, it
gets unloaded and the inventory gets available. Right, So that's
(10:17):
sort of the future. We think like AI has the
potential to enable, and we are starting to build for that,
and and that's a bad Like that's a better future
because now you're you're making supply chains more efficient, that
you're you're taking waste out of supply chains, right.
Speaker 1 (10:34):
Sure, And so you know, AI obviously it's a very
sexy industry, especially if you're doing it for transportation. It's
becoming a credit space because there's a lot of competitors
out there. Are you differentiate what what augment is doing
versus maybe some of the other competitors out.
Speaker 2 (10:51):
There, Yeah, it is. It is a crowded space, partly
because it's so easy to build a prototype. You know,
you can vibe code of protein type, and if the
buyers are uninformed for them, it's very hard to tell
the difference. You know, the difference really comes in when
you actually take a product product to production at scale
and test to handle all these extenuating circumstances. And then
(11:14):
I think prototype starts to break the way we differentiate
is we have few core concepts or principles. The first
one is that you know you can really do mean
You can only do meaningful work when you have end
to end context. So point solutions of voice bots or
(11:34):
email or like a code solution, if they don't have
a full context of like here's my customer, this was
the customer's sop. This customer is an enterprise customer. This
has been my performance so far. If you don't have
that context when you're building the load, tracking a load,
when you have to make a decision if the truck's
running late, or you have to make a decision to
(11:55):
book a load at a negative mark, you can't do that.
And to bring true product activity you need to have
end to end context. So augment is building. I would
say an order to cash set of use cases for
all of our businesses, whether it's brokers or shippers or fleets,
and through those order to cash use cases, we can
(12:16):
now carry context and do a better job at each
step of the way. I think two is we believe
that you know, work is inherently multi modal, right, so
it's not just about calls or emails or tech, it
is about all of that like in some businesses, a
lot of work gets done on teams or Slack, and
(12:39):
there's a lot of discussion that is happening between people
on Slack, and it's extremely important for Augie to be
part of that conversations because there's a lot of context
in that. Right, somebody might say, hey, I just got
a call. This shipment has become an urgent shipment. We
need to now start tracking at fifteen minutes. Okay. If
Augie is part of that conversation on Slack, it now
(13:01):
knows that it can start adjusting its work. So the
shipment updates need to be sent every fifteen minutes, you know.
And so we believe that you have to meet where
people are and the work is not just any mode,
it's all modes all the time. And so we had
to build a teammate that almost looks and feels no
(13:21):
different than a remote employee. But it can be added
to any of these channels, you know. Third is we
are unlike many horizontal players like who are saying hey,
we have a AI platform, generic platform and you can
now implement it. We are purpose built for the logistics space. Right,
(13:42):
so we're saying we understand the ontology of freight and logistics.
We understand what a multi stop shipment is. We understand
what a flatbed truck is. We understand what does appointment
times mean. We understand sort of all the key players
that a highway fraud score or a you know, a
marker on dat or truck stop. What does that mean.
(14:04):
You don't need to teach Augie that it comes learned
about this space. So those are the three differences. One
is very holistic order to catch set of workflows. People
can pick and choose, of course, but our hope is
that they end up deploying Augie across a vast majority
of order to catch workflows and you get to see
(14:24):
more benefit. Very multimodal and you know, very purpose built
for logistics.
Speaker 1 (14:31):
So when you say multimodal when you talk about carriers,
so you will do not only chuckload but lesser chuckload
and intermodal and other things that brokers are you know broking.
Speaker 2 (14:46):
Yeah, I mean we today do all modes, right, all
modes across all channels of communication. Like that's what I
mean by multimodel. So LTL, FDL, flatbread auto, you know,
drage loads. So we do that and we build the
ontologies for all of those, But then the channels of
(15:06):
communication are also quite quite varied, right, Like, if you're
looking at LTL word one, in the LTL world, there's
really only twenty five thirty big LTL carriers in this space,
and the way you communicate to them is a lot
through their website actually, right, But in the FTL space,
(15:27):
it's a really fragmented industry, and the way you communicate
with them is maybe through emails and texts to the
dispatchers and calls sometimes to the drivers. And so allgie
needs to have sort of all of those channels of communication,
but needs to also understand the ontology of all of
these different modes.
Speaker 1 (15:46):
And you mentioned the truckle and market being very fragmented
and very large. What does success mean for you guys
in terms of market share? Like how much of the
market do you think you guys could actually control of.
I don't know if you would measure by the AI
spend or just how many the percentage of the industry
that you're working with.
Speaker 2 (16:07):
Yeah, great question. So I think, like, first, let me
the way we measure success is delivering ROI to our customers, right, Like, Hey,
by deploying Augie, what is the returnal investment? What is
the meaningful financial gain that you're able to get? Right,
And we actually measure that with every business we get into,
and I think if we do that, we hopefully acquire
(16:29):
more market But the way we see market share is
freight under management, Like how much freight inder management is
Augie assisted or Augie powered? You know, in this last year,
we've gone from almost nothing to now about forty billion
of freight under management that AUGI is getting deployed at.
Of course, you know, this market is close to you know,
(16:52):
eight hundred to nine hundred billion, and then if you
count the LTL market, you're getting closer to a trillion.
So we're still very early, right like we're maybe like
barely four percent of the market. There's so much to
go and build, Like, I don't know what the upper
limit is. You know, there are some players who are
going to try to build this in house. There's some
(17:14):
players who are going to try to buy it. You know,
we're just really obsessively focused on saying, hey, if you
deploy Augie, can we get you seven to ten x ROI?
And if he can, we think more people will use us,
you know, So that's.
Speaker 1 (17:28):
That's the goal of seven to ten ROI.
Speaker 2 (17:31):
For our businesses. That's right. Yeah, can you talk.
Speaker 1 (17:34):
About like some of the productivity gains that you have
generated for a broker, for a carrier, like any anecdotal
stories that you might have, or or if you have
some consolidated stats that'd be great too.
Speaker 2 (17:47):
Yeah, let's let's do that. So, I mean I like
to go specifics, I think because that's where the like
people get start to hopefully learn from the color hair. Right. So,
one of our customers is fairly large HELTL focused, you
know three pl They have about a billion dollar of
freight ender management. And their first sort of issue that
(18:10):
they came to us was that that they had a
forty percent team, mostly offshore, that was reliant on spreadsheets
and fragmented homegrown systems to do tracking for urgent shipments
HEALTL shipments. So what they were really doing was they
were logging into all these different LTL carriers websites maybe
(18:35):
calling them to get a pro number. And they had
done a fair bit of tech investments lee before, but
thirty percent of their shipment sort of still lacked pro numbers.
And then after if you don't have the pro number,
you can get the real tracking. And so they deployed
Augie and said like, hey we want Augie do now
(18:56):
go get the pro number, Go get the latest update,
posting those updates into our system of record, the TMS.
And and now they have sort of freed up twelve
out of the forty people and repurpose them for more
growth related activity. Right, So I mean, what is that
(19:19):
about twenty thirty percent you know, productivity improvement on a
forty percent team. And and now but that's now. Now
the team hasn't has gotten confidence that oh I can
hand over all these urgent shipment tracking to Augie. Now
they're like, okay, what is the next thing that keeps
(19:43):
my team busy? And how can I help them, you know,
focus on things that I really want them to relationships
and and margins. So that's like an example of that.
There's another example of you know, like a very large
customers of ours do about four billion in revenues. They
(20:04):
have a network of close to eighty thousand carriers, and
you know, they had spent a lot of time and
built fairly extensive automation. You know, like their their automation
budget is in tens of millions a year, right's almost
(20:25):
sixteen million, and they were you know, for a small
percentage of their lows, call it fifteen to twenty percent
that was being covered through the public loadboards like the
Ato truck stop. You know, they were getting about thirty
five hundred calls and five thousand emails on a daily basis,
(20:47):
and a vast majority of them were getting unanswered, right
because like just to imagine, like the workforce, you need
to answer five thousand emails or thirty five hundred calls.
So what they do They put Augie on it and
they say, hey, Agie, I want you to be the
first line of defense, you know, answer these calls and
(21:08):
then you know, follow up on emails as you need to.
And so now you know, sticking all of the inlong
calls today, right every single day, and negotiating and booking loads,
and that's freeing up people to do I think more
higher judgment things. Now. If everything in a call is passed,
(21:32):
like their fraud scores is cleared up, they're not on
the do not use list, they meet the criterias of
the business. They have a good price, you know, the
freight fleet company is a good price. Then Augie is
passing that. But now it has done all the heavy
lifting of qualifying, getting a good bid, and then passing
(21:53):
that bid and transferring their call to a rep. So
when the rep takes the call, they're now really making
use of their time well right, and the same thing
with email. So through this plus about eight or nine
other use cases like this business you know expects somewhere
between six to twelve million improvement in IBITA over twelve months,
(22:18):
twelve to eighteen months, you know. So we were working
with them on that. You know, one of our customers
is this one we ever think published case study with them.
So it's called Armstrong Transport Group. They you know, they
are a large threpl it's sort of mixed. They have
(22:42):
agents and then they have W two brokers, so they
have a bit of both. And they had also a
fairly fairly large team that was doing day to day
tracking and tracing of loads. And you know, they are
(23:02):
now putting Augie as the first sign of defense to
you know, track these loads and raise escalations and whatnot,
and and it's made a remarkable difference. Like I think
the last we touched now forty of all TMS updates
(23:23):
on track and Trace are now made by Augie from zero,
you know, and roughly it's in's like thousands of updates
that needs to happen on a daily weekly basis on
these so it's many meaningful numbers. The other thing the
you know atg or Armstrong did with us was put
Augie to work on document collection, right like that was
(23:46):
actually the first use case. They say, like, hey, truly
no one likes document collections, so I always want Augie
and they're they're keyb was like, hey, when how many?
Like what can I do to reduce my dso hours?
Because so every hour, as you know, like brokers can
only get paid after the invoice, they have to pay
(24:08):
in some ways to the fleets before the shippers pay
them because of the term. So almost every day count
because they are otherwise running on you know, a credit
facility with the bank to cover this gap. So we
actually brought down Augie starts to chase these these documents
through emails and phone calls and texts and was able
(24:29):
to and then verify these documents whether they're signed not signed,
that they're matching the load number so that the billing
can happen in a really good way. And they were
able to bring down you know, the dso from I
think fifty eight hours before Augie do now like less
than thirty six hours and it's still coming down there,
optimizing it so across the board, like we're starting to
(24:50):
see you know, meaningful impact in like true financial metrics
for these businesses.
Speaker 1 (24:57):
So given the focus in the trucking industry recently on
a non domicel CDL holders and English language proficiency, uh,
is Augie able to help brokers kind of like exclude
those that that I guess population of of the of
the driver market.
Speaker 2 (25:17):
Yeah, so you know, we are a law compliant now
and so if that's the law, then we followed the law.
And there's a couple of cases there. One is it
Auto Today actually works with the Highway real time so
as soon as we get an email or or call
AGI before we even take or pick up the call.
(25:40):
We work with Highwave if you know who they are,
to get a really great company do fraud detection. But
they've also added cd L verification for the carriers themselves,
so you can get that signal from them.
Speaker 1 (25:53):
We had one of their executives on the podcast earlier
this year. So if you're interested to hear more about
highway and D or preventing for success listeners to go
back and uh, take a take a listen to it.
Speaker 2 (26:07):
So it's a big company. We enjoy working with them,
great partner to us. But yeah, we we basically you know,
Auguie will like Augie in a highway will like ping
each other. Highest sense. Highway senses the information both on
fraud but also on c d L, and then if
it's failing the CDL test, you know, we will obviously
(26:29):
not take the call and politely declient saying so I
don't think we can work with you, right now? What's that?
Speaker 1 (26:34):
That's nice?
Speaker 2 (26:34):
That is polite? I like that. Yeah, you know, like, yeah,
I think AI has like yeah, it is more patient
than humans, you know, and so and and and then
and then on top of that, like we we have
conditions where let's say we are making a call to
a you know, a driver and and and we are
(26:56):
sensing that they're not not able to pick up the
language English on that very well, right, we can we
can analyze the call, and we can we can rate
the call for proficiency in English, and that's a pretty
good signal. We can at least mark that to the
business like and saying hey, this is this is the
(27:17):
proficiency of English according to us in this call, do
you want to do business with this company or not?
Ultimately it's you know, the broker or the fleets or
the shipper's decision, not art. But we can give them
the data much more real time then it would be
available anywhere else.
Speaker 1 (27:33):
Interesting stuff. And then so in addition to this, the
CDL and the English proficiency, So, as you mentioned, you're
in constant contact with Highway about fraud. Are there any
things that does by itself to detect fraud and make
sure that fraud is not happening?
Speaker 2 (27:53):
So a few things. So one is that it supplements
what we get from Highway and almost all all of
our businesses have their own do not use list for
a variety of different reasons. They could be fraud, but
they could also be for performance related reasons or pay
related reasons, you know. So it supplements the signals it
(28:13):
gets from Highway with you know, the businesses data and
does that. That's I think one thing. I think the
only other piece where we can help or help is
in track and trace. One of the frauds in this
business is that the truck starts to go off route,
(28:36):
and it's let's say it supposed to go from Atlanta
to Chicago, and there is a route for it, and
you know it starts there, but then it starts to
go off route. Now, typically you can try to set like,
you know, a geofense and saying hey, if it's within
this geofense, I'm good. But if it crosses the geofense,
(28:58):
I need to know. This is a fraud. Somebody is
literally stealing, right. It's like it's the worst kind of product.
They're just off. They know there's a high like high
valued goods in the container and they pick it up
and then they want to just steal or go to
a warehouse and replace the the trailer and then still
(29:18):
do a delivery, but but with like very different goods
or whatnot. You know. So in that case, you can
put ugue to say like, hey, I want you to
be like a watchman, right and say like, hey, watch
these signals and if it's on its way, we're good.
But if it's not, priests start to alert internally, whether
it's through calls or you know, teams or slack messages
(29:40):
to people and saying hey, I think there's a potential.
We you want me to call the driver, You call
the driver, or maybe you want to step in and saying, hey,
why are you going this route? I don't know we
can prevent the fraud, but we can like maybe by
this way we can at least alert the authorities faster.
You know, there's a little bit more like knowing that
(30:02):
this can happen also can prevent the fraud.
Speaker 1 (30:05):
So just changing gears a little bit. So like the
brokers industry is pretty fragmented. Obviously there's there's a bunch
of huge players, but there's also a lot of little players.
And you know, the broker industries was kind of an
industry where all you needed was a Rolodex and a
phone and you can be find success. You know, fast
forward today obviously do need technology and technology is becoming
(30:27):
more and more important. If I'm like a small broker
and I you know, understand that I start really need
to start using tools like augmented and algy Where are
like the first places that you suggest a broker to
start using AI and their workflow, you know, as they're
(30:47):
kind of dipping their toe in the water because they
but they might not just have the funds to go all.
Speaker 2 (30:52):
In, Yeah, it's a a good question. So I think
there's sort of two lenses to look at it, right,
especially for small brokers, delivering an incredible service level to
customers is how they grow their business. Right, So if
you signed up for you know, if you have some
(31:14):
business from a Target or a Walmart or you know,
you line like, Okay, how did you do on my
fifty loads? Really matters because that's how you earn your
next fifty and your next hundred, And a big part
of the service is that, hey, was there on time, pickup,
on time delivery and load detention, like okay, can you
always make sure those happens? So the brokers obsess about
(31:35):
that and they care about like delivering those services. So
I think one of the easiest and early places to
put AI on is just that it's like, hey, can
you like take over the whole track and trace type
of initiative for me and put me in in loop
or get me in and saying like if there is
(31:57):
an extenuating circumstances is an issue, me step in. But
but like having a pair of eyes that is like
twenty four to seven on it all the time is
because like most small brokers also don't have night shifts,
they don't have sometimes overseas resources and so and trucks
(32:19):
around twenty four seven. So having an augie as like
your night shift person at a minimum, or an AI
that can just monitor things all the time and alert
you when you need it to, I think it can
go a long way in earning trust of the shippers.
So's I would say, it's almost like less about costs
to serve for small shippers, but it's much more about
delivering an exceptional service level to the sorry for small brokers,
(32:44):
but delivering an exceptional service levels to their shipping customers.
You know.
Speaker 1 (32:48):
So has the current freight recession hindered growth for you
guys or is it kind of help growth? As I
guess people are trying to get more productive with the
you know, the low revenues that are coming in. Another
broker and carrier said.
Speaker 2 (33:04):
I think net net it has helped initiatives and companies
like ours and AI in general because there's just a
tremendous amount of cost pressure, right Like I think we
have what Lee, I think three and a half years
into now for a kind of a price recession. Definitely
in this industry. And so margins are raised thin across
the board, right, like whether you're a broker or you're
(33:25):
a fleet I think these are some of the lowest
margins maybe ever, certainly in the last five years that
you have seen. And so having AI ttarting to take
some cost out, you know, almost becomes impertative and a
nice hope in this in this environment that hey. And
(33:47):
then two, as it turns around, which it will, you know,
as a market, now now you have like you can
you can handle the sicklycality better, right right, because like
before this business was like it's so cyclical that as
market gets hard, you just need to hire so many
(34:08):
people to cover freight. Well, now you have AI all
theis of the world that can help you not go
so high and so low. It can be like this bridge.
You know that if the market gets hard, you can
just put AI to work to more use cases and
you don't need to hire that many people. So I
think there's like two benefits. But yeah, in that net,
(34:30):
if I were to take a guest, I think it's
it's it certainly helped.
Speaker 1 (34:34):
Yeah, great, And then you know what has been the
biggest challenge you face since founding Augment.
Speaker 2 (34:44):
The biggest challenge, Like I'll put it like in two terms.
One is for Augment, you know as building the company,
but then also working with our customers I think like
delivering value. I think working and building the company. It's talent,
you know, like very AI native talent is an extremely
(35:06):
high demand and there are companies in every layer, whether
it's the LM layers or the data center layers, and
we are in the application layer right every layer there
is just a tremendous demand of that talent. And it's
not a lot of talent, it's you know, that talent
is getting groomed, the AI native talent. So you've got
gone from I think like zero to like one hundred
(35:29):
engineers or so. But but you know, in short amount
of time I would say, like less than less than
a year's and but it wasn't easy, you know, to
get one hundred engineers. We probably looked at, you know,
close to five thousand engineers, you know, and then obviously
(35:49):
people trickle through the interview loop and then when you
make them an offer, a lot of people have several
offers and you have to compete on why they should
join Augment, you know, and not open AI.
Speaker 1 (36:03):
But it's to work, it's to work with you, of course,
I mean that's the number one.
Speaker 2 (36:08):
I hope that goes a little bit, but it is.
It is not easy, and we spend an enormate amount
of time to build a teams. So if we think
like talent comes first in this space, now working with
our customers, I think the biggest there are two challenges,
but the biggest challenges change management like AI. When AI
does something, somebody is not doing that thing, and AI
(36:32):
is taking on real work, like it is taking on
end to end work right, which means that the company
needs to go and repurpose and retrain employees that you
don't need to do this, but I need you to
retrain to do this right. And that requires a tremendous
amount of effort and fortitude and courage to do. And
(36:57):
there are leaders who are leaning in when they are
also leaders will like weight and see mode because it
is so much work and it is it's also courageous,
like oh, I'll have to go and take five hundred
people and retrain them on new set of skills, right,
And they were just so set of doing this one thing.
(37:17):
But now AI is doing that, and I don't need
them to do this thing, but I need them to
do this new thing, and so a natural instinct is
that maybe next quarter, maybe in two quarters, you know,
versus today. So what that does is for companies like ours,
is it pushes the ROI where you can show that
(37:42):
people need to do less. But those folks are not
repurposed and flowing through the books, it gets harder to show,
you know. And so I think there's just a lot
of work that needs to be done in this industry.
And maybe there are consulting firms and whatnot who can
help for folks who've done this, Like, how do you
(38:02):
take folks like we are technology providers and we have
some now some experience a bit now observing across several
of our customers, how what good looks like, whatnot. But
we're not the experts of change manager Like we need
folks who can take these very large three four to
five thousand people organizations and run them through change management.
(38:26):
But the reality is that every single organization in two
years time is going to look very different than what
it does look today. Right.
Speaker 1 (38:35):
It's interesting, you know, you keep on mentioning retraining people
versus reducing head count, So you think most of the
brokers and carriers that implement this are not going down
that road.
Speaker 2 (38:49):
So I think there's like there's offshore labor and near
shore we're seeing their reductions, right, They're not like there
we are seeing very clear like, hey, these teams I
need to reduce and they're usually not on the payroll
there contractors, right, But I think the folks on the
payroll most businesses are saying, like, can I the institutional
(39:14):
knowledge the culture, like can I actually see if I
can repurpose them for growth? Okay, Like they're they're they're
looking at it from that angle. They're saying, can I
deliver more superior? But they already know who I am,
they know how I work, you know, they know my systems,
they know my customers. Like that would be a waste
(39:34):
to say, like I can have this talent go out
of my door. Right, It's just the skills that they
were working on is now different and now so I
think most companies are thinking that way. I don't know
how much will end up on can sales or customer
relationships or new business expansion absorb all of that. I
think the jury is still out on it.
Speaker 1 (39:56):
Right, And so just again changing gears a little bit.
Can you talk about a little bit how you got
into transportation, you know, what made you kind of as
a technologist kind of gravitate towards the freight world.
Speaker 2 (40:11):
Yeah. So, like I started off my career at Amazon,
and I you know, wrote a lot of software which
now runs fulfillment by Amazon Service. There we were big
consumers of transportation, right, like trucks coming from hosts the
certainly are distributing all over the country. I mean now
Amazon maybe after Walmart or a couple other players, probably
(40:34):
one of the larger trucking consumers in in in in
in the US. And then several of my businesses, whether
it was delivered or even the one before, we were
either builders or consumers or both of the freight word.
And so you know, from that I understood both the
(40:56):
problems in this space, right, Hey, why does it you know,
why is it so tedious? Right? And like why there
are so many inefficiencies in this space. It's a large space.
It's so crucial and important too, you know for augmented
(41:17):
So that's how I got into it. But I think
the way become a sort of a computer science math
type of person, and I look at things as like
this node arc networks. You know, you have nodes and
you have arcs, and like arcs can be like ships
and trucks and planes, and and nodes are like distributor
warehouses or or you know, like small distribute like last
(41:44):
mile distribution warehouses or cross crosstocking depots or so there's
like different nodes, you know, and truck is a is
an ARC that connects almost all nodes in America, I say,
is the most common form of So like, okay, if
you want to go and change logistics in general or
supply chain broadly, let's start with the most important arc.
(42:04):
Through that we will learn the ecosystem, the warehousing, the
distribution ecosystem, and from that we can now branch out
to those verticals if you will. We were starting off
with trucking, but augments mission is broader, right. Our mission
is that can we make logistics better? And that requires
(42:24):
coordination with nodes and arcs or different types.
Speaker 1 (42:27):
All right, well, well good luck with that. With that
goal in mind, you know, before we go, I always
like to ask my guests if they have a favorite
book about transportation leadership or in your case, technology that's
kind of close to your heart that you might want
to recommend our listeners to take a look at.
Speaker 2 (42:45):
Okay, so I think I'll give you maybe two. I
think the first one is is a very technical book.
It's about how to optimize network is called network Flows.
The main author is Rabia Ahuja. It's like a seminal
book on how do you model physical networks into sort
(43:08):
of this computer science way of thinking graph theory, and
then now you can optimize. It's very dense, but it's
fascinating and you can start to see networks in everything,
like you know, like an airline is a network where
you know a airplane is going from one to the other.
Wheels or networks, ships are network and how do you
optimize it? And it's a you know, it's a it's
(43:29):
an interesting read. It might for you to sleep if
you if you read it on your bedstand. I think
in terms of leadership, I like this the hard things
about hard things, you know, it's a it's a great
book about grit that how leaders just need to lean
in on on the toughest the toughest calls, and and
(43:50):
the complexity of decisions that you need to make and
the discipline of execution to build anything of meaning. You know.
So I love that book. I re reiated every time
I have, you know, tough days building businesses, I go
back and read that book and say like, Okay, it's
not that bad. You know.
Speaker 1 (44:13):
Well, I really want to thank you for your time,
Harish and your insights today. This is definitely an interesting conversation.
Speaker 2 (44:19):
So thank you for having me. It was great chatting
with you, and I want to.
Speaker 1 (44:22):
Thank you for tuning in. If you'd liked the episode,
please subscribe and leave a review. We've lined up a
number of great guests for the podcast, so please check
back to your conversations with C suite executives, shippers, regulators,
and decision makers within the freight markets. Also, if you
want to learn more about the freight transportation markets, check
out our work on the Bloomberg Terminal at Bigo and
on social media. This is Lee Klaskal signing off and
(44:44):
thanks for talking transports with me. Bye.
Hi everyone, this is Lee Clascow when We're Talking Transports.
Welcome to Bloomberg Intelligence Talking Transports podcast. I'm your host,
Lee Clasgow, Senior Freight, transportation and logistics analysts at Bloomberg Intelligence,
Bloomberg's in house research arm of almost five hundred analysts
and strategists around the globe. A quick public service announcement
before we dive in. Your support is instrumental to keep
bringing great guests and conversations to you, our listeners, and
(00:30):
we need your support. So please, if you enjoy this podcast,
share it, like it, leave a comment. Also, if you've
got ideas, feedback, or just want to talk transports, I'm
always happy to connect. You can find me on the
Blueberg terminal, on LinkedIn, or on Twitter at logistics Late.
I'm very excited to have with us today. Harish Abbott,
the co founder and CEO of Augment and AI productivity
platform for logistics. Augment has raised about one hundred and
(00:53):
ten million from Red Point Ventures, eight VC and leading
logistics funds. Prior to launching Augment, Harish co founded Deliver,
an e commerce fulfillment platform acquired by Shopify for two
point one billion dollars in twenty twenty two. His career
includes pivot roles at Amazon, where he contributed to building
global fulfillment infrastructure. He holds degrees from Indian Institute of Technology, Rookie,
(01:21):
the University of Illinois, and an MBA from Stanford. Welcome
to talking Transports, Harish.
Speaker 2 (01:27):
Thank you for having me. I'm excited to speak with
you here.
Speaker 1 (01:31):
Yeah, it's great to have you. Can you talk a
little bit about what Augment does.
Speaker 2 (01:35):
Sure, So, Augment is, you know, an AI productivity platform
for the logistics businesses. Our first product is Augie Augie.
Think of Augie as a teammate that can work twenty
four to seven across all modes in a business emails
(01:56):
and phone calls and text and messaging and your systems
record like TMS or w m S and it goes
and does work that is given to Augie as s
OPS or standard operating procedures is getting deployed to lots
of freight businesses today, mostly large freight brokers, UH freight
(02:19):
fleets and now shippers. Yeah, that's what that's what we
do and and reach.
Speaker 1 (02:27):
Can you talk about how you know a broker might
use versus versus a shipper?
Speaker 2 (02:34):
Sure so well, Like if you think about what does
a broker and do is you know their their job
is to match demand to supply and then execute against it.
They get demands from shippers of the world and then
the supplies are from several fleets, large fleets and small fleets.
They try to match them and then execute a shipment
(02:57):
end to end. Now, in the execution of the shipment,
there are multiple multiple steps today extremely manual. Right, there's
steps like, hey, I get a shipment in an email,
I need to now put that load up in a
TMS manually maybe or correct some feels from a load
that came through an EDI to Now I've got a shipment,
(03:21):
I need to now go source capacity for it. I've
got preferred carriers, I've got data on who's run these
lanes before. Or sometimes I get a load where I'd
never run this lane before, so I need to post
it on a public loadboard like DAT or truck stop.
(03:42):
Then there is this work of like hey, I've posted
the load, I need to now negotiate the load, go
back and forth to figure out how am I going
to make my margin on it. Once you figured out
like hey, this person is going to do this load
to this company. Then there's a whole execution step off.
I'm going to dispatch the load. I want to make
sure the driver understands how to get in. I have
(04:04):
to set up appointments for a load right on the
pickup side, on the drop off side. Then I have
to track the load. I have to keep updating the
customer on where the load is at, if there's delays,
what to do in terms of those delays. And then
when the load gets delivered, then there is the whole
paperwork cycle begins of collecting the delivery documents, collecting the
(04:26):
invoicing documents, and making sure if there's excessorials, detention lumpers,
those are collected so that the billing can happen fast.
So if you look at this life cycle for a broker,
you can now deploy Augie in any or all of
these steps, almost like a worker and saying, hey, Augie,
(04:51):
now you can be looking for all my emails and
look for tenders, and if you get a tender, maybe
start building the load in the TM And if you're
missing information, maybe you can come in and ask somebody
and saying, hey, I'm missing this information. What does this
shipper really mean, or go back and ask the shipper
so you can completely build the load. Or once the
(05:13):
load is built, like hey, just start working on capacity sourcing.
So collaboratively, work with the rep, understand their preferred carriers,
reach out to them, maybe post a load on a
dat get the incoming calls, take those calls, negotiate the load.
Some businesses say like pass the final negotiation to the rep.
Some people say, like, you can book the load, and
(05:35):
then like, let's start working on tracking the load or
tracing the load end to end, so making the dispatch calls,
understanding you know, the eled events, making the scheduling appointments,
and then all the way towards the end is like, hey,
the load's got delivered. Now we need to go and
chase documents. And you and I know nobody likes chasing documents.
Like we put Augie to work and it can chase
(05:57):
documents or our ds source or days sales outstanding can shrink,
and we can start money can start moving in this
business again and faster and quicker. So those are like
some of the use cases that people are using Augie
for today. As a broker. People are also using Augie
for like coding, you know, like they get lots of
(06:18):
requests for course, like hey, could you respond to my code?
Speaker 1 (06:22):
Okay, so just a quick commercial. You know you mentioned
DAT and truck stop on the Bloomberg terminal. O. The
data is available and it can be found at BI
spaceed trc k Go on the Bloomberg terminal. So if
you're interested in that data, we have a spot contractual
struggle with market data from those two data providers you.
Speaker 2 (06:40):
Know you mentioned.
Speaker 1 (06:41):
So there's like three main customers that you guys are
going after, the shipper, the carrier and the broker. Right now,
kind of what is the mix and kind of because
I know you're in growth mode, what do you think
the optimal mix would be three years from now?
Speaker 2 (06:55):
Yeah, I mean today, I think I would say sixty
percent of our businesses are brokers, right and they tend
to be the largest brokers about thirty five percent our fleets.
And then we're just starting to work with shippers, so
we're not as deep with shippers yet. I think as
(07:19):
we go forward, you know, our vision is that it
is not about I think step one Lee is about
taking this tedious, repetitive work off humans plates so they
can focus on more important things, right, that's what we're doing.
But if you imagine, you know, Augie's on a broker
(07:41):
side and a fleet side, and the two Augies can
now synchronously collaborate, then we can eliminate the need for
the phone calls and the text and the emails. Right.
So our mission is to make logistics better, and we
think the way to make that better is to get
to more real time synchronous collaboration between shippers and brokers
(08:07):
and fleets so that people can act faster. Right. So,
if you know your question was like three years from now,
I would sing three years from now, most of our
businesses like were equal mix of you know, shippers and
brokers and fleets, and we are really moving towards getting
all of them the signals they need so they can
(08:28):
act in their business faster. Right. Like as example would be,
well today, if a truck's running late, what happens is
and it's a broker load, the maybe the offshore team
or the overnight team at the broker has to like
keep an eye on it. If they get an alert
(08:49):
the truck's running late, then they might decide, oh, I
need to reset the appointment. The resetting of the appointment
means sometimes you can log into a portal. Sometimes it
means you need to email. And let's say, if it's
an email scenario, you email somebody, and if the receiving
warehouse is not working at that time, well till nine
(09:11):
am next morning, you're not going to get a new appointment.
So now the labor that the warehouse had planned is
going to get wasted because the truck's not showing up
on time. The truck when it shows up late, doesn't
have an appointment, so it might need to wait for hours,
sometimes days to be unloaded. And in the meantime, the
(09:33):
shipper's inventory is unsellable. Right, So everybody's hurting. The shippers hurting,
the warehouse is hurting, the truck guy is hurting, and
the broker's performance is hurting too because the shipper holds
them accountable. But now, if you imagine a scenario where
an augie on the broker side detects that truck's running late,
(09:57):
calls or synchronously communicates with an all on the warehouse,
I said, let's do find me a new appointment. That
appointment is now booked. The new the labor that was
allocated for the first appointment is reallocated to somebthing else
more productive, and now when the truck shows up, it
gets unloaded and the inventory gets available. Right, So that's
(10:17):
sort of the future. We think like AI has the
potential to enable, and we are starting to build for that,
and and that's a bad Like that's a better future
because now you're you're making supply chains more efficient, that
you're you're taking waste out of supply chains, right.
Speaker 1 (10:34):
Sure, And so you know, AI obviously it's a very
sexy industry, especially if you're doing it for transportation. It's
becoming a credit space because there's a lot of competitors
out there. Are you differentiate what what augment is doing
versus maybe some of the other competitors out.
Speaker 2 (10:51):
There, Yeah, it is. It is a crowded space, partly
because it's so easy to build a prototype. You know,
you can vibe code of protein type, and if the
buyers are uninformed for them, it's very hard to tell
the difference. You know, the difference really comes in when
you actually take a product product to production at scale
and test to handle all these extenuating circumstances. And then
(11:14):
I think prototype starts to break the way we differentiate
is we have few core concepts or principles. The first
one is that you know you can really do mean
You can only do meaningful work when you have end
to end context. So point solutions of voice bots or
(11:34):
email or like a code solution, if they don't have
a full context of like here's my customer, this was
the customer's sop. This customer is an enterprise customer. This
has been my performance so far. If you don't have
that context when you're building the load, tracking a load,
when you have to make a decision if the truck's
running late, or you have to make a decision to
(11:55):
book a load at a negative mark, you can't do that.
And to bring true product activity you need to have
end to end context. So augment is building. I would
say an order to cash set of use cases for
all of our businesses, whether it's brokers or shippers or fleets,
and through those order to cash use cases, we can
(12:16):
now carry context and do a better job at each
step of the way. I think two is we believe
that you know, work is inherently multi modal, right, so
it's not just about calls or emails or tech, it
is about all of that like in some businesses, a
lot of work gets done on teams or Slack, and
(12:39):
there's a lot of discussion that is happening between people
on Slack, and it's extremely important for Augie to be
part of that conversations because there's a lot of context
in that. Right, somebody might say, hey, I just got
a call. This shipment has become an urgent shipment. We
need to now start tracking at fifteen minutes. Okay. If
Augie is part of that conversation on Slack, it now
(13:01):
knows that it can start adjusting its work. So the
shipment updates need to be sent every fifteen minutes, you know.
And so we believe that you have to meet where
people are and the work is not just any mode,
it's all modes all the time. And so we had
to build a teammate that almost looks and feels no
(13:21):
different than a remote employee. But it can be added
to any of these channels, you know. Third is we
are unlike many horizontal players like who are saying hey,
we have a AI platform, generic platform and you can
now implement it. We are purpose built for the logistics space. Right,
(13:42):
so we're saying we understand the ontology of freight and logistics.
We understand what a multi stop shipment is. We understand
what a flatbed truck is. We understand what does appointment
times mean. We understand sort of all the key players
that a highway fraud score or a you know, a
marker on dat or truck stop. What does that mean.
(14:04):
You don't need to teach Augie that it comes learned
about this space. So those are the three differences. One
is very holistic order to catch set of workflows. People
can pick and choose, of course, but our hope is
that they end up deploying Augie across a vast majority
of order to catch workflows and you get to see
(14:24):
more benefit. Very multimodal and you know, very purpose built
for logistics.
Speaker 1 (14:31):
So when you say multimodal when you talk about carriers,
so you will do not only chuckload but lesser chuckload
and intermodal and other things that brokers are you know broking.
Speaker 2 (14:46):
Yeah, I mean we today do all modes, right, all
modes across all channels of communication. Like that's what I
mean by multimodel. So LTL, FDL, flatbread auto, you know,
drage loads. So we do that and we build the
ontologies for all of those, But then the channels of
(15:06):
communication are also quite quite varied, right, Like, if you're
looking at LTL word one, in the LTL world, there's
really only twenty five thirty big LTL carriers in this space,
and the way you communicate to them is a lot
through their website actually, right, But in the FTL space,
(15:27):
it's a really fragmented industry, and the way you communicate
with them is maybe through emails and texts to the
dispatchers and calls sometimes to the drivers. And so allgie
needs to have sort of all of those channels of communication,
but needs to also understand the ontology of all of
these different modes.
Speaker 1 (15:46):
And you mentioned the truckle and market being very fragmented
and very large. What does success mean for you guys
in terms of market share? Like how much of the
market do you think you guys could actually control of.
I don't know if you would measure by the AI
spend or just how many the percentage of the industry
that you're working with.
Speaker 2 (16:07):
Yeah, great question. So I think, like, first, let me
the way we measure success is delivering ROI to our customers, right, Like, Hey,
by deploying Augie, what is the returnal investment? What is
the meaningful financial gain that you're able to get? Right,
And we actually measure that with every business we get into,
and I think if we do that, we hopefully acquire
(16:29):
more market But the way we see market share is
freight under management, Like how much freight inder management is
Augie assisted or Augie powered? You know, in this last year,
we've gone from almost nothing to now about forty billion
of freight under management that AUGI is getting deployed at.
Of course, you know, this market is close to you know,
(16:52):
eight hundred to nine hundred billion, and then if you
count the LTL market, you're getting closer to a trillion.
So we're still very early, right like we're maybe like
barely four percent of the market. There's so much to
go and build, Like, I don't know what the upper
limit is. You know, there are some players who are
going to try to build this in house. There's some
(17:14):
players who are going to try to buy it. You know,
we're just really obsessively focused on saying, hey, if you
deploy Augie, can we get you seven to ten x ROI?
And if he can, we think more people will use us,
you know, So that's.
Speaker 1 (17:28):
That's the goal of seven to ten ROI.
Speaker 2 (17:31):
For our businesses. That's right. Yeah, can you talk.
Speaker 1 (17:34):
About like some of the productivity gains that you have
generated for a broker, for a carrier, like any anecdotal
stories that you might have, or or if you have
some consolidated stats that'd be great too.
Speaker 2 (17:47):
Yeah, let's let's do that. So, I mean I like
to go specifics, I think because that's where the like
people get start to hopefully learn from the color hair. Right. So,
one of our customers is fairly large HELTL focused, you
know three pl They have about a billion dollar of
freight ender management. And their first sort of issue that
(18:10):
they came to us was that that they had a
forty percent team, mostly offshore, that was reliant on spreadsheets
and fragmented homegrown systems to do tracking for urgent shipments
HEALTL shipments. So what they were really doing was they
were logging into all these different LTL carriers websites maybe
(18:35):
calling them to get a pro number. And they had
done a fair bit of tech investments lee before, but
thirty percent of their shipment sort of still lacked pro numbers.
And then after if you don't have the pro number,
you can get the real tracking. And so they deployed
Augie and said like, hey we want Augie do now
(18:56):
go get the pro number, Go get the latest update,
posting those updates into our system of record, the TMS.
And and now they have sort of freed up twelve
out of the forty people and repurpose them for more
growth related activity. Right, So I mean, what is that
(19:19):
about twenty thirty percent you know, productivity improvement on a
forty percent team. And and now but that's now. Now
the team hasn't has gotten confidence that oh I can
hand over all these urgent shipment tracking to Augie. Now
they're like, okay, what is the next thing that keeps
(19:43):
my team busy? And how can I help them, you know,
focus on things that I really want them to relationships
and and margins. So that's like an example of that.
There's another example of you know, like a very large
customers of ours do about four billion in revenues. They
(20:04):
have a network of close to eighty thousand carriers, and
you know, they had spent a lot of time and
built fairly extensive automation. You know, like their their automation
budget is in tens of millions a year, right's almost
(20:25):
sixteen million, and they were you know, for a small
percentage of their lows, call it fifteen to twenty percent
that was being covered through the public loadboards like the
Ato truck stop. You know, they were getting about thirty
five hundred calls and five thousand emails on a daily basis,
(20:47):
and a vast majority of them were getting unanswered, right
because like just to imagine, like the workforce, you need
to answer five thousand emails or thirty five hundred calls.
So what they do They put Augie on it and
they say, hey, Agie, I want you to be the
first line of defense, you know, answer these calls and
(21:08):
then you know, follow up on emails as you need to.
And so now you know, sticking all of the inlong
calls today, right every single day, and negotiating and booking loads,
and that's freeing up people to do I think more
higher judgment things. Now. If everything in a call is passed,
(21:32):
like their fraud scores is cleared up, they're not on
the do not use list, they meet the criterias of
the business. They have a good price, you know, the
freight fleet company is a good price. Then Augie is
passing that. But now it has done all the heavy
lifting of qualifying, getting a good bid, and then passing
(21:53):
that bid and transferring their call to a rep. So
when the rep takes the call, they're now really making
use of their time well right, and the same thing
with email. So through this plus about eight or nine
other use cases like this business you know expects somewhere
between six to twelve million improvement in IBITA over twelve months,
(22:18):
twelve to eighteen months, you know. So we were working
with them on that. You know, one of our customers
is this one we ever think published case study with them.
So it's called Armstrong Transport Group. They you know, they
are a large threpl it's sort of mixed. They have
(22:42):
agents and then they have W two brokers, so they
have a bit of both. And they had also a
fairly fairly large team that was doing day to day
tracking and tracing of loads. And you know, they are
(23:02):
now putting Augie as the first sign of defense to
you know, track these loads and raise escalations and whatnot,
and and it's made a remarkable difference. Like I think
the last we touched now forty of all TMS updates
(23:23):
on track and Trace are now made by Augie from zero,
you know, and roughly it's in's like thousands of updates
that needs to happen on a daily weekly basis on
these so it's many meaningful numbers. The other thing the
you know atg or Armstrong did with us was put
Augie to work on document collection, right like that was
(23:46):
actually the first use case. They say, like, hey, truly
no one likes document collections, so I always want Augie
and they're they're keyb was like, hey, when how many?
Like what can I do to reduce my dso hours?
Because so every hour, as you know, like brokers can
only get paid after the invoice, they have to pay
(24:08):
in some ways to the fleets before the shippers pay
them because of the term. So almost every day count
because they are otherwise running on you know, a credit
facility with the bank to cover this gap. So we
actually brought down Augie starts to chase these these documents
through emails and phone calls and texts and was able
(24:29):
to and then verify these documents whether they're signed not signed,
that they're matching the load number so that the billing
can happen in a really good way. And they were
able to bring down you know, the dso from I
think fifty eight hours before Augie do now like less
than thirty six hours and it's still coming down there,
optimizing it so across the board, like we're starting to
(24:50):
see you know, meaningful impact in like true financial metrics
for these businesses.
Speaker 1 (24:57):
So given the focus in the trucking industry recently on
a non domicel CDL holders and English language proficiency, uh,
is Augie able to help brokers kind of like exclude
those that that I guess population of of the of
the driver market.
Speaker 2 (25:17):
Yeah, so you know, we are a law compliant now
and so if that's the law, then we followed the law.
And there's a couple of cases there. One is it
Auto Today actually works with the Highway real time so
as soon as we get an email or or call
AGI before we even take or pick up the call.
(25:40):
We work with Highwave if you know who they are,
to get a really great company do fraud detection. But
they've also added cd L verification for the carriers themselves,
so you can get that signal from them.
Speaker 1 (25:53):
We had one of their executives on the podcast earlier
this year. So if you're interested to hear more about
highway and D or preventing for success listeners to go
back and uh, take a take a listen to it.
Speaker 2 (26:07):
So it's a big company. We enjoy working with them,
great partner to us. But yeah, we we basically you know,
Auguie will like Augie in a highway will like ping
each other. Highest sense. Highway senses the information both on
fraud but also on c d L, and then if
it's failing the CDL test, you know, we will obviously
(26:29):
not take the call and politely declient saying so I
don't think we can work with you, right now? What's that?
Speaker 1 (26:34):
That's nice?
Speaker 2 (26:34):
That is polite? I like that. Yeah, you know, like, yeah,
I think AI has like yeah, it is more patient
than humans, you know, and so and and and then
and then on top of that, like we we have
conditions where let's say we are making a call to
a you know, a driver and and and we are
(26:56):
sensing that they're not not able to pick up the
language English on that very well, right, we can we
can analyze the call, and we can we can rate
the call for proficiency in English, and that's a pretty
good signal. We can at least mark that to the
business like and saying hey, this is this is the
(27:17):
proficiency of English according to us in this call, do
you want to do business with this company or not?
Ultimately it's you know, the broker or the fleets or
the shipper's decision, not art. But we can give them
the data much more real time then it would be
available anywhere else.
Speaker 1 (27:33):
Interesting stuff. And then so in addition to this, the
CDL and the English proficiency, So, as you mentioned, you're
in constant contact with Highway about fraud. Are there any
things that does by itself to detect fraud and make
sure that fraud is not happening?
Speaker 2 (27:53):
So a few things. So one is that it supplements
what we get from Highway and almost all all of
our businesses have their own do not use list for
a variety of different reasons. They could be fraud, but
they could also be for performance related reasons or pay
related reasons, you know. So it supplements the signals it
(28:13):
gets from Highway with you know, the businesses data and
does that. That's I think one thing. I think the
only other piece where we can help or help is
in track and trace. One of the frauds in this
business is that the truck starts to go off route,
(28:36):
and it's let's say it supposed to go from Atlanta
to Chicago, and there is a route for it, and
you know it starts there, but then it starts to
go off route. Now, typically you can try to set like,
you know, a geofense and saying hey, if it's within
this geofense, I'm good. But if it crosses the geofense,
(28:58):
I need to know. This is a fraud. Somebody is
literally stealing, right. It's like it's the worst kind of product.
They're just off. They know there's a high like high
valued goods in the container and they pick it up
and then they want to just steal or go to
a warehouse and replace the the trailer and then still
(29:18):
do a delivery, but but with like very different goods
or whatnot. You know. So in that case, you can
put ugue to say like, hey, I want you to
be like a watchman, right and say like, hey, watch
these signals and if it's on its way, we're good.
But if it's not, priests start to alert internally, whether
it's through calls or you know, teams or slack messages
(29:40):
to people and saying hey, I think there's a potential.
We you want me to call the driver, You call
the driver, or maybe you want to step in and saying, hey,
why are you going this route? I don't know we
can prevent the fraud, but we can like maybe by
this way we can at least alert the authorities faster.
You know, there's a little bit more like knowing that
(30:02):
this can happen also can prevent the fraud.
Speaker 1 (30:05):
So just changing gears a little bit. So like the
brokers industry is pretty fragmented. Obviously there's there's a bunch
of huge players, but there's also a lot of little players.
And you know, the broker industries was kind of an
industry where all you needed was a Rolodex and a
phone and you can be find success. You know, fast
forward today obviously do need technology and technology is becoming
(30:27):
more and more important. If I'm like a small broker
and I you know, understand that I start really need
to start using tools like augmented and algy Where are
like the first places that you suggest a broker to
start using AI and their workflow, you know, as they're
(30:47):
kind of dipping their toe in the water because they
but they might not just have the funds to go all.
Speaker 2 (30:52):
In, Yeah, it's a a good question. So I think
there's sort of two lenses to look at it, right,
especially for small brokers, delivering an incredible service level to
customers is how they grow their business. Right, So if
you signed up for you know, if you have some
(31:14):
business from a Target or a Walmart or you know,
you line like, Okay, how did you do on my
fifty loads? Really matters because that's how you earn your
next fifty and your next hundred, And a big part
of the service is that, hey, was there on time, pickup,
on time delivery and load detention, like okay, can you
always make sure those happens? So the brokers obsess about
(31:35):
that and they care about like delivering those services. So
I think one of the easiest and early places to
put AI on is just that it's like, hey, can
you like take over the whole track and trace type
of initiative for me and put me in in loop
or get me in and saying like if there is
(31:57):
an extenuating circumstances is an issue, me step in. But
but like having a pair of eyes that is like
twenty four to seven on it all the time is
because like most small brokers also don't have night shifts,
they don't have sometimes overseas resources and so and trucks
(32:19):
around twenty four seven. So having an augie as like
your night shift person at a minimum, or an AI
that can just monitor things all the time and alert
you when you need it to, I think it can
go a long way in earning trust of the shippers.
So's I would say, it's almost like less about costs
to serve for small shippers, but it's much more about
delivering an exceptional service level to the sorry for small brokers,
(32:44):
but delivering an exceptional service levels to their shipping customers.
You know.
Speaker 1 (32:48):
So has the current freight recession hindered growth for you
guys or is it kind of help growth? As I
guess people are trying to get more productive with the
you know, the low revenues that are coming in. Another
broker and carrier said.
Speaker 2 (33:04):
I think net net it has helped initiatives and companies
like ours and AI in general because there's just a
tremendous amount of cost pressure, right Like I think we
have what Lee, I think three and a half years
into now for a kind of a price recession. Definitely
in this industry. And so margins are raised thin across
the board, right, like whether you're a broker or you're
(33:25):
a fleet I think these are some of the lowest
margins maybe ever, certainly in the last five years that
you have seen. And so having AI ttarting to take
some cost out, you know, almost becomes impertative and a
nice hope in this in this environment that hey. And
(33:47):
then two, as it turns around, which it will, you know,
as a market, now now you have like you can
you can handle the sicklycality better, right right, because like
before this business was like it's so cyclical that as
market gets hard, you just need to hire so many
(34:08):
people to cover freight. Well, now you have AI all
theis of the world that can help you not go
so high and so low. It can be like this bridge.
You know that if the market gets hard, you can
just put AI to work to more use cases and
you don't need to hire that many people. So I
think there's like two benefits. But yeah, in that net,
(34:30):
if I were to take a guest, I think it's
it's it certainly helped.
Speaker 1 (34:34):
Yeah, great, And then you know what has been the
biggest challenge you face since founding Augment.
Speaker 2 (34:44):
The biggest challenge, Like I'll put it like in two terms.
One is for Augment, you know as building the company,
but then also working with our customers I think like
delivering value. I think working and building the company. It's talent,
you know, like very AI native talent is an extremely
(35:06):
high demand and there are companies in every layer, whether
it's the LM layers or the data center layers, and
we are in the application layer right every layer there
is just a tremendous demand of that talent. And it's
not a lot of talent, it's you know, that talent
is getting groomed, the AI native talent. So you've got
gone from I think like zero to like one hundred
(35:29):
engineers or so. But but you know, in short amount
of time I would say, like less than less than
a year's and but it wasn't easy, you know, to
get one hundred engineers. We probably looked at, you know,
close to five thousand engineers, you know, and then obviously
(35:49):
people trickle through the interview loop and then when you
make them an offer, a lot of people have several
offers and you have to compete on why they should
join Augment, you know, and not open AI.
Speaker 1 (36:03):
But it's to work, it's to work with you, of course,
I mean that's the number one.
Speaker 2 (36:08):
I hope that goes a little bit, but it is.
It is not easy, and we spend an enormate amount
of time to build a teams. So if we think
like talent comes first in this space, now working with
our customers, I think the biggest there are two challenges,
but the biggest challenges change management like AI. When AI
does something, somebody is not doing that thing, and AI
(36:32):
is taking on real work, like it is taking on
end to end work right, which means that the company
needs to go and repurpose and retrain employees that you
don't need to do this, but I need you to
retrain to do this right. And that requires a tremendous
amount of effort and fortitude and courage to do. And
(36:57):
there are leaders who are leaning in when they are
also leaders will like weight and see mode because it
is so much work and it is it's also courageous,
like oh, I'll have to go and take five hundred
people and retrain them on new set of skills, right,
And they were just so set of doing this one thing.
(37:17):
But now AI is doing that, and I don't need
them to do this thing, but I need them to
do this new thing, and so a natural instinct is
that maybe next quarter, maybe in two quarters, you know,
versus today. So what that does is for companies like ours,
is it pushes the ROI where you can show that
(37:42):
people need to do less. But those folks are not
repurposed and flowing through the books, it gets harder to show,
you know. And so I think there's just a lot
of work that needs to be done in this industry.
And maybe there are consulting firms and whatnot who can
help for folks who've done this, Like, how do you
(38:02):
take folks like we are technology providers and we have
some now some experience a bit now observing across several
of our customers, how what good looks like, whatnot. But
we're not the experts of change manager Like we need
folks who can take these very large three four to
five thousand people organizations and run them through change management.
(38:26):
But the reality is that every single organization in two
years time is going to look very different than what
it does look today. Right.
Speaker 1 (38:35):
It's interesting, you know, you keep on mentioning retraining people
versus reducing head count, So you think most of the
brokers and carriers that implement this are not going down
that road.
Speaker 2 (38:49):
So I think there's like there's offshore labor and near
shore we're seeing their reductions, right, They're not like there
we are seeing very clear like, hey, these teams I
need to reduce and they're usually not on the payroll
there contractors, right, But I think the folks on the
payroll most businesses are saying, like, can I the institutional
(39:14):
knowledge the culture, like can I actually see if I
can repurpose them for growth? Okay, Like they're they're they're
looking at it from that angle. They're saying, can I
deliver more superior? But they already know who I am,
they know how I work, you know, they know my systems,
they know my customers. Like that would be a waste
(39:34):
to say, like I can have this talent go out
of my door. Right, It's just the skills that they
were working on is now different and now so I
think most companies are thinking that way. I don't know
how much will end up on can sales or customer
relationships or new business expansion absorb all of that. I
think the jury is still out on it.
Speaker 1 (39:56):
Right, And so just again changing gears a little bit.
Can you talk about a little bit how you got
into transportation, you know, what made you kind of as
a technologist kind of gravitate towards the freight world.
Speaker 2 (40:11):
Yeah. So, like I started off my career at Amazon,
and I you know, wrote a lot of software which
now runs fulfillment by Amazon Service. There we were big
consumers of transportation, right, like trucks coming from hosts the
certainly are distributing all over the country. I mean now
Amazon maybe after Walmart or a couple other players, probably
(40:34):
one of the larger trucking consumers in in in in
in the US. And then several of my businesses, whether
it was delivered or even the one before, we were
either builders or consumers or both of the freight word.
And so you know, from that I understood both the
(40:56):
problems in this space, right, Hey, why does it you know,
why is it so tedious? Right? And like why there
are so many inefficiencies in this space. It's a large space.
It's so crucial and important too, you know for augmented
(41:17):
So that's how I got into it. But I think
the way become a sort of a computer science math
type of person, and I look at things as like
this node arc networks. You know, you have nodes and
you have arcs, and like arcs can be like ships
and trucks and planes, and and nodes are like distributor
warehouses or or you know, like small distribute like last
(41:44):
mile distribution warehouses or cross crosstocking depots or so there's
like different nodes, you know, and truck is a is
an ARC that connects almost all nodes in America, I say,
is the most common form of So like, okay, if
you want to go and change logistics in general or
supply chain broadly, let's start with the most important arc.
(42:04):
Through that we will learn the ecosystem, the warehousing, the
distribution ecosystem, and from that we can now branch out
to those verticals if you will. We were starting off
with trucking, but augments mission is broader, right. Our mission
is that can we make logistics better? And that requires
(42:24):
coordination with nodes and arcs or different types.
Speaker 1 (42:27):
All right, well, well good luck with that. With that
goal in mind, you know, before we go, I always
like to ask my guests if they have a favorite
book about transportation leadership or in your case, technology that's
kind of close to your heart that you might want
to recommend our listeners to take a look at.
Speaker 2 (42:45):
Okay, so I think I'll give you maybe two. I
think the first one is is a very technical book.
It's about how to optimize network is called network Flows.
The main author is Rabia Ahuja. It's like a seminal
book on how do you model physical networks into sort
(43:08):
of this computer science way of thinking graph theory, and
then now you can optimize. It's very dense, but it's
fascinating and you can start to see networks in everything,
like you know, like an airline is a network where
you know a airplane is going from one to the other.
Wheels or networks, ships are network and how do you
optimize it? And it's a you know, it's a it's
(43:29):
an interesting read. It might for you to sleep if
you if you read it on your bedstand. I think
in terms of leadership, I like this the hard things
about hard things, you know, it's a it's a great
book about grit that how leaders just need to lean
in on on the toughest the toughest calls, and and
(43:50):
the complexity of decisions that you need to make and
the discipline of execution to build anything of meaning. You know.
So I love that book. I re reiated every time
I have, you know, tough days building businesses, I go
back and read that book and say like, Okay, it's
not that bad. You know.
Speaker 1 (44:13):
Well, I really want to thank you for your time,
Harish and your insights today. This is definitely an interesting conversation.
Speaker 2 (44:19):
So thank you for having me. It was great chatting
with you, and I want to.
Speaker 1 (44:22):
Thank you for tuning in. If you'd liked the episode,
please subscribe and leave a review. We've lined up a
number of great guests for the podcast, so please check
back to your conversations with C suite executives, shippers, regulators,
and decision makers within the freight markets. Also, if you
want to learn more about the freight transportation markets, check
out our work on the Bloomberg Terminal at Bigo and
on social media. This is Lee Klaskal signing off and
(44:44):
thanks for talking transports with me. Bye.
Host
Lee Klaskow
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