it's great to be here thanks a lot
the time to come and learn a little bit

about what we're doing
I'm Amari ruff co-founder and CEO of soo

do we are in more of the transportation
space we leverage different technologies

to connect small and medium sized
trucking companies to corporations that

ship goods
so we're housed right up the road at a

TDC at the accelerator there we've been
there since about 2016 it's been a great

experience we love being there and
having the connectivity to Georgia Tech

and to this department especially to you
know come and bounce different ideas and

also from a recruiting perspective is
always great you know have all these big

brains and bright minds here that we can
bring onto the team and help us you know

continue to expand and reach our goals
so when I first started the company we

looked at the industry and a little bit
background on me I'm a serial

entrepreneur this is actually my third
company that I've started my most

previous I was in the telecommunications
industry where we it was a contracting

company and we did a residential and
commercial installation services for

major cable providers so think of those
guys that come to your house and install

your cable and your your internet and
your phone service which was a voice

over IP I had a team of those guys and I
started that company with one truck a

few hundred bucks and I was able to grow
it to over 200 trucks and we have five

offices across the country we're able to
exit that business so I looked at my

next thing and it was like okay I'll
jump into logistics and the initial goal

first was just to start a trucking
company like I thought to myself okay I

had all these trucks there were four
Rangers not like tractor trailers but I

was like hey I can do the same thing you
know easily with no problem but I in and

started to do a lot of discovery and I
learned that it was a gonna be a lot

more capital-intensive than I had
anticipated

so I ended up doing
more of a pivot to a non asset based

model where this is kind of what I see
in an industry which was you know the

trucking industry six hundred billion
dollar industry and as we all know

everything we see we touch we eat was
most likely moved on a truck but what

was really interesting was that 90% of
all trucking companies have six or less

trucks so in order for them to get
quality Freight opportunities from you

know quality shippers or very large
shippers they would have to have

capacity right at least a hundred trucks
even to just start those conversations

so they would have to go through freight
brokers to get that quality work and

when we looked at the freight brokers
the freight brokers are really that

problem you know they were the ones that
one out of every four transactions have

to go through that freight broker and
they were just glorified call centers

you know they're their sole goal was to
maximize margins off of every

transaction that was it not a lot of
value add back to the truck or very

limited value add back to the shippers
so here brokers extremely expensive

literally sucks the life out of the
truck or barely leaving them with any

money to truly run their businesses with
so when we looked at that as the problem

we thought to ourselves okay those
brokerages are just human capital

hundreds thousands of people on the
phones making cause the completed

transaction what we could do is we could
layer on some technology to complete

that transaction so of course we we live
in a world where it's the uber model

right you know everything could be
leveraged through you know machine

learning component or maybe leverages
some AI so I don't have the strong

technical background I know enough to be
dangerous but I had to I had to reach

out to some people that were a little a
little smarter than me you know they're

really bring this this this thought and
vision to life so my co-founders

actually he's actually Georgia Tech grad
strong product background he's our CEO

today so when I first had that full
vision it was all in my mind I reached

out to him and he was actually running
one of the vertical

is over at a TDC and we knew each other
from our kids going to school together

so when I called him he was like hey
this sounds pretty interesting why don't

you come up here to a EDC then I jumped
into customer discovery and started to

really you know flush out the idea and
kind of homed in on you know some sort

of MVP so we did something that was
really unique that it's funny now

looking back on and I don't even know
how we actually survived and did it but

so during customer discovery as a young
company we're probably about two three

employees strong and I got an
opportunity to pitch to Walmart so went

down to Bentonville we pitched and the
pitch was actually pretty good and we

got a contract but remember we only have
like three employees are we gonna manage

that right so we ended up taking five
off-the-shelf technologies and we kind

of integrated them all together and we
called it like our Frankenstein right

and we knew that it can manage you know
a small portion of the Walmart business

but eventually we would have to raise
some venture capital to replace

Frankenstein piece by piece and we were
actually able to do that so I'll kind of

grow through and this is the freight
brokers this is kind of what they look

like and what's crazy is they look like
this today you know literally you walk

into an office and you will see these
hundreds and thousands of people all on

the phones and it's just like you know
call center or you're at like some sort

of money trading brokerage or you know
what do they call them the the boiler

room yeah that's that's kind of what's
going on in there and these guys some of

some of these companies are still
sending faxes and communicating with the

truckers that way so we knew that this
model could definitely be disrupted

especially in this large of an industry
if we could just get it right right so

the way we solved this market mismatch
is number one we've created

well we've gathered a network of
truckers of roughly about 300,000

trucking companies that we know a lot
about right and we were able to gather

all these truckers from different
methods of course as a start-up you've

got to be extremely scrappy
if nothing's gonna come super-easy to

you so you've got to you know be able to
do what it takes to get things done and

continue to progress the company so we
when we recruited new members of the

team they came with existing trucker
relationships so we got some of our

capacity from there I had a relationship
with a truck in association I was able

to capture all of their members and get
them within our network and then we were

actually able to gather a list of every
trucking company in the United States

and we've got a team in Columbia South
America that goes through and they vet

that list so the analogy I like to use
is uh I don't know if you all remember

when Google Maps first launched you
would see the little cars with the

globes on top that's just driving around
just collecting data that's what our

team in Columbia South America is doing
they're calling through that list and

they're asking hey what's your truck
type what's your trailer type what are

different lanes you like to run what are
the commodities you like to move what's

your drivers vacation schedule how do
you like to be communicated with so all

this information is being gathered and
housed into our system so here we're

just kind of scroll through that piece
so here's a snapshot of what our actual

system looks like so this is where all
of our carriers are housed and if you

look a little - let's see a little to
the right you'll see where they're

approved and then there be a tab
sometimes that says not approve so that

just lets us know kind of what their
status is and we also keep record of

their star ratings so we keep a rated on
these carriers so we know what

opportunities to introduce these
carriers to cuz we work with some small

and medium-sized businesses that their
Freight may not be time sensitive so

that allows us the opportunity to put
some of those truckers on that non time

sensitive Freight so we can bet them and
really understand what's their level of

service once we're able to get quality
ratings on these carriers then we're

able to introduce them to better paying
opportunities and more high profile

customers we work with some of the
largest brands in the world today so

we've quality is is key you know yeah we
can come in and cut the

and but at the end of the day service is
what's going to maintain is what's gonna

help us maintain that customer
relationship so if you look here this is

another snapshot of our system where we
house all of those different preferences

so the truck type the trailer type you
know lanes they like to run and then we

also created a carrier portal where the
carrier dispatcher or the trucker

himself can log in and update this
information so if they grow their fleet

or they start to expand offices or
they're just looking just to grow their

businesses and by capturing you know
different commodities and move a

different types of freight they can log
in and update this information

themselves and so here's something
really cool that we've done if in the

transportation industry pricing is is
everything and pricing can be affected

by various things you know there could
be a new law that's passed or you know

some different stipulations and prices
will go up or prices will go down we can

get hit with hurricanes like we did last
year that you know that are really bad

back to back and those will shoot the
rates you know through the roof so what

we've done is we've created this
proprietary you know pricing system

where we leverage multiple external
market data sources and we bring that

into our system and we weigh that
against our internal market data so

internally this could be from different
RFPs that we may have been on that we

put prices in and then the customer
gives us feedback saying hey you're one

you're in first place or you're in tenth
or year and 30th so we're collecting all

this data and we're putting this in our
system so we feel like we've got a good

understanding of where the market is and
then we bring that external data in a

way that against our internal data to
give us the most optimized price so

that's something cool that we're doing
that's a little different that gives us

an advantage and helps us price
different customers if it could be more

of a spot basis emergency real time
basis or it could even be we could

leverage this tool to price more RFPs
which will be locked in prices for the

next
- or quarterly rates so this this allows

us to do that and I the gentleman that
actually created that systems right here

so he's our he's our team member at
Georgia Tech guy as well

so I had to give make sure I give Andrew
a shout out so here is what we call our

pseudo sage search so what we've so we
connect with our customers it could be

which we're still in an industry that's
a tad bit traditional and that a lot of

technology advancement there so some
customers we still connect via EDI or

some customers we connect via API which
is more preferable for us but we pride

ourselves in being flexible and being
able to connect with the customers in a

way that's comfortable for them so that
helps us win it from a sales cycle

perspective where we're not asking our
customers to change a lot of their

behavior and majority of our
efficiencies kind of happen on the back

end and that gives them a level of
comfort where we're not saying like hey

we've got to change all these different
things in what you're doing no we'll

connect with you in a way that's
comfortable for you so we felt that

that's sort of like an advantage to
working with su but so we'll receive

that that freight information that data
it'll be lane data meaning location

pickup is in Atlanta delivery could be
in Memphis pickup times commodities

weights all that information will hit
our system and our algorithm is going to

take all of those different preferences
into account based off of all the

truckers within our network so locations
truck type trailer types commodities

they like to move vacation skills
there's all those things are taken into

account and that's immediately gonna
give us a top five top ten top 50 trucks

that best fit to move that load of that
particular time so right there that's

that solves a huge issue with that human
capital if you think back to how those

traditional brokers operate where
they're just hitting the phones now our

operations team which we still have
customer success people because our

industry still requires a human touch
component to it but we equip them with

technology advances advancements so they
can react quickly a source capacity

it shouldn't quickly and then here is
where we really differentiate from our

competitors is our multicast system
so the way we differentiate from

traditional brokerages is number one
we're just leveraging technology boom

we're different simple as that
they're just call centers people on

phones making calls now on the digital
side they put us in a bucket where they

call us a digital broker because we're
still licensed and bonded as a freight

brokerage company so we're considered a
digital broken our competitors we go

against uber Freight which just jumped
in the market that's doing really well

and there's another company called
transfix that's out of New York they've

raised probably about 80 million dollars
or so so they're doing they're doing

decent they're doing pretty well then
there's another company called convoy

which is out of Seattle which is backed
by Bezos right so that's a lot of fun

for us right we're going to get its uber
and pretty much Amazon so and we're just

the startup out there but remember the
industry is gigantic seven hundred

billion dollar industry so not one
player is going to dominate the entire

industry today now a little fun fact is
the top 18 well the top 20 freight

brokerages today make up less than 18
percent of the market if you think about

that so it's extremely fragmented tons
of opportunity out there these are the

same talks that I have with our
investors like like what do you do it's

uber and Bezos is another company where
we're gonna give you money like it's

okay like we're gonna keep our heads
down focus on a segment of the market

and we'll win we'll win in our
particular lane our goal is not to you

know defeat or conquer convoy but it's
to stay in our lane and capture a

portion of the market which we feel
extremely confident that we can do so

the way we differentiate from our
competitors do perforates the transfixes

and the convoys and the and the compound
I know if you all are aware they just

got valued at one point 1 billion
dollars in 3 years

so 3 years they've become a unicorn so
which is really exciting but what's cool

is that when they were at our stage as a
company we're actually further along

than they were we've got bigger
customers we've got better margins and

better net revenue so they just had
Bezos on this

but hey we're gonna keep working hard
though so the way we differentiate is we

feel that there's opportunity in
leveraging voice technology and

leveraging chatbots that's where we
really feel that we can do some things

different so our competitors are saying
hey download this mobile app and that's

gonna be the way you communicate with us
just over model you know you don't have

to call anybody just work with this
mobile app and that's how everything's

gonna operate but our industry is
extremely traditional you know the

average age of a trucker's in the
mid-50s and forcing them to adopt to new

technologies is really tough so we've
seen and we know for a fact that our

competitors have faced a lot of
resistance and getting their adoption

from a mobile app perspective so that's
where we were like hey we see some

opportunity and voice technology so
today now we do have a mobile app for

those truckers that are a little more
technology advanced but believe it or

not some of these guys still have flip
phones so what we've done is we've

developed chat BOTS that can send SMS
text messages with that load information

so based off of their preferences when
the load matches they'll receive a text

message and they can communicate back
and forth and ask questions we've also

created that carrier portal that I spoke
about so if it's more a 2 plus truck

operation that that dispatcher can log
into the system and they could see

different Freight information and they
could also bit on different freight and

ask questions and it's powered by a chat
bot but what we've also done is we've

developed and designed that chat bot to
actually make outgoing calls as well so

who in here is kind of familiar with
Google duplex and you may know Google

duplex so more of a conversational AI
component so that's where we're trying

to take it we're not there today today
you know it's still a little robotic

voice and you know yes or no kind of
things to be said but within the next 6

to 9
months our goal is to have that that

chat but what the conversation oai
components who be able to complete an

entire transaction right so you think at
the press of one button today now we can

call five truckers or we can call five
hundred truckers but it's an extremely

simplistic you know but we're working
through it but like I said long term

goal is we'll press that button well
will receive the freight information the

chatbot will analyze it then from there
we'll source the most qualified capacity

do an outreach negotiate secure price
dispatch that truck track the truck all

the way to delivery retrieve the
paperwork invoice the customer and pay

the trucker as well that's where we're
going with it and then that would

eliminate you know majority of the human
touch component will still have customer

success people because that's just
what's required in our industry things

are going to happen but that's our goal
and we feel that it's a hard nut to

crack but I'm sure with all you guys
have helped we can crack that nut

anybody confident help us out maybe not
yeah yeah so that's so that's what we're

going with it so it's an exciting time
to you know be in the logistics industry

from a transportation perspective in our
industry also we hear a lot about driver

shortage and you know there's not many
truckers out there a lot of guys are

retiring one of the things that we're
doing to combat that is since we're

Enterprise focused we're starting to
leverage our customers private fleets so

one of our customers is a B and Bev to
say and they have their own private

fleet that goes from let's say warehouse
to warehouse making deliveries from A to

B but they're going from B to a empty so
we're gonna do is turn that from a cost

center now to a profit center so we may
drop a UPS load on that truck or we may

drop a Walmart load on that truck and
we'll set different business rules in

our systems so of course a B and Bev's
not picking up high and again on one of

their
or anything like that but we feel that

that will give us additional capacity
quality drivers as well so that's

something that we're kind of
experimenting as well and something else

is that's pretty cool is we're actually
rolling out a new SAS product that we

are starting we're gonna be starting a
pilot with a chemicals company which is

abrasca which is a Brazilian own
chemicals company but the US location is

up in Philadelphia so what we've done is
when we spoke to them our goal was first

to help them move their chemical
products but they said hey we've got all

these regulations and different things
going on so we have the truckers and

capacity that we need but our problem is
outreach a fish sourcing that capacity

efficiently that's already within our
network so we thought it was like back

to Andrew again who's our all-star from
Georgia Tech of course this is his

product here this pseudo SAS platform
where now we've turned we've taken our

our technology and we've white labeled
that and we're going to put that in the

hands of our customers so they can
source their capacity by leveraging our

chatbots
so now it's kind of like hey moving

freight from A to B is really thin
margins I mean five 7% is what we'll see

maybe ten you know and in a great day
but we'll use that as a foundation of

the business and maybe even undercut the
prices just to get more customers in so

we can sell them our SAS product which
will make a lot better margins so those

are some of the things that we're
talking about and what's cool is that

being a start-up we can make these
decisions real time you know we don't

have to you know go through legal and a
bunch of red tape Andrew came up and was

like hey I got this idea he white
boarded it and we rolled it out just

like that
so that's one of the really fun things

of is you know working with the startup
we can just do different things we can

pivot we can try different things out
but I like to tell the team that let's

just fell fast if anything but let's
always keep the entrepreneur spirit

let's always try different things let's
be risk takers but you know if it

doesn't work we'll just scrap it and
will continue to move

you know cuz that's how we really make
an impact and on the industry so I'll

screw through as I'm glancing that time
I can set up here and talk to you guys

all day so I'm just going through a
little bit so today now the things that

I've talked about isn't you know what we
think or what we hope to do you know

it's it's what we're doing today and
it's resonating with big brands you know

as you see Walmart was ah our first
enterprise customer that we've landed

we're working with other extremely large
brands today and we've got a pipeline of

other strong ones as well so definitely
exciting times and our goal is just to

continue to enhance our platform and
continue to grow the business and add

great team members to the team and then
of course this industry is being

disrupted today just like you know
Airbnb did the hotel industry and just

like uber did the taxi cab industry you
know sudo is playing a part and

disrupting you know the logistics
industry today and I kind of scroll

through that and this is a few of our
other team members today and a few of

our investors that's doing this so today
now we've raised about three million

dollars today in venture capital so
we've got a little funding we're gearing

up for a series a raise now and we're
also gearing up for UPS peak season

which is one of our new customers so
we'll be helping them out with the

holiday delivery so great times to be
you know within the sudu umbrella but

that is a little bit about us and I
guess are we gonna open for questions

now or later I'm open
okay yeah there we go

I'm open for questions

no great questions so number one was how
do we actually build our team you know

without funding um Wow so I've always
been really good my strengths are

business development in sales and by
being the founder I was able to

articulate the vision of the business so
I knew that I could look within my

network I'm a really relationship driven
individual so my co-founder our kids

actually went to school together when
they were one there's seven now and I

remember you know being at different
birthday parties I would always see him

and he was always talking about
technology and what he's doing at

Georgia Tech so when I had the idea of
the company I reached out to him so I

looked at my network and I just took a
chance and once I was able to convince

him to take the crazy jump to come on
board

I really engulfed myself in the
technology ecosystem here in the Atlanta

area which is a really you know
tight-knit community and by going to

different events and networking with
different people you see in me really

cool people who may have worked with the
startup who just exited and looking for

their next thing or they may have
clumped down and ran out of funding and

they're looking for the next thing so
there's always people out there that are

looking that you could find and network
with my my CTO I actually got him from

being over at a TDC he was our our AI
our entrepreneur in residence we would

have to check in with him on a weekly
basis and I convinced him to turn down

the job from Amazon to jump on board
with us because it's the vision you know

just knowing that you can come on early
there's an equity component to it which

is equities the key cuz of course
everybody wants to be able to have you

know and a vested interest in the
business so that's kind of how I sold

that and then from a marketplace
perspective how to you know build a

marketplace from scratch we first were
able we worked on the trucker side first

and we're able to get a ton of capacity
the truck is within our network aren't

Sol su do truckers they work with other
brokerages or they may have customers on

their own but what it was is we wanted
to outreach to them reach out to them

let them know who we are what we're
doing so we know whether whether I guess

their gaps are you know one guy may say
hey I've got loads going from Atlanta to

Memphis all the time but I could never
get out of Memphis so we knew that

information is in our system and we kept
note of that so now we get a new

customer we say hey we're gonna focus on
things coming out of Memphis because J&J

trucking was interested in that so we
did that on a repeated basis and were

able to gain that and then on the supply
side we're always selling we're always

you know looking for customers like we
will land a large customer like Walmart

who may move a hundred thousand loads a
day maybe right but we'll take the beach

injury we'll move a little bit of
Freight right now and then we've got a

little truckers and it will slowly start
to grow both sides of that marketplace

so fully that helps what's your answer
good any more questions

oh we got one now yes sir

yes yeah so the question was um you know
what's our revenue model yes so we do

operate like a brokerage but we don't
take the traditional brokerage margins

traditional brokerages could be anywhere
from 20 to 30 sometimes 40 percent that

they're taken off the top so Walmart or
one of our customers will pay us a

thousand bucks to move you know these
loads and then we'll pay the trucker 900

or 950 just based off of the lane and
we'll take a spread from that

transaction there's also a component
where since we focus on small and

medium-sized trucking companies there's
a we call it a partner financing

component because these guys need their
money real time so aren't we paying

about net 25 net 30 they'd like to get
paid immediately and we can command

around the two to three percent you know
spread off of that so that helps us as

well but as we roll out this SAS product
and just depending on how the success of

the pilot goes with a new customer will
probably start taking free at cost or

even at a loss and incorporate that into
our CAC which is our customer

acquisition costs and then just to sell
them the SAS product because we'll be 80

90 95 percent margins off of that so as
we think through things I'm thinking

that it'd be more of our long-term play
and of course I got to bounce that off

of our all-star over here to make sure
that that fits right yeah any other

questions

we're just starting with their Atlanta
operations before suit and one of the

guys that I actually might have been
trained at my first brokerage done is

working with echo Global Logistics was
helping out consulting with students

that he introduced me to the Mari
Michelangelo of morva they talked

through ideas because some of my ideas
have been having mine that well what

they were doing in the exfoliant vision
week to later I was sitting at a seat so

there's a lot of luck and handsome stand
somebody ad we had some prior

connections that I have trained my prior
positions that work with them or were

around that at least what was your
specialty yes so it worked out we had a

combination of individuals on the team
that didn't have industry knowledge

which brought value because we could
look and say why don't they do it this

way but at the same time we needed to
make sure that we brought on individuals

that had that Logistics experience in
that background that could help balance

the two and that's where Andrew came on
board into play and then we also have a

few more individuals I think everybody
outside of the executive suite everybody

has logistics experience just so we've
got a really good balance with we're

team of 15 now we've got 11 in Columbia
South America and we actually we just

got a green light we're moving our
office next door in 80 DC so they tore

down the wall so now it's like a double
office because we're growing it so that

we're like big stuff now man you guys
we're excited about and we're growing

the team we'll probably add three more
team members before the year is out as

we gear up for peak I think we we see
ourselves more of emergency spot market

planned in that area we can commend
higher margins there and then our

customers see a lot of value because we
can react quickly you know by leveraging

our technology so I think that's where
we'll play but a lot of times our

customers will make us play in the
dedicated space just to build the

relationship but from a marketplace
perspective that's not bad because it's

going to give us our critical mass and
it's more predictability there and

there's a lot of truckers out there that
are looking for that predictability so

it's just a matter of we've we looked at
the country as we want to build pockets

right and then we we want to gain
critical mass in those particular

pockets and then we could do more of a
load pairing you know component to it

where you know truckers now are going a
to be UPS b2c Walmart C to D a B and Bev

then D back to a with a chip load and
that's the goal to be able to get to

that point where truckers are in our
network we understand their growth what

they want to accomplish what are the
revenue goals and then we put different

things in places where if they're L o SS
X they can get more points here and just

kind of make it sort of like a
gamification sort of thing well with

that we need more capital so if there's
any of investors out there you know we

could always use more money that's
no we're doing no no yeah so you know we

thought we've actually had some meetings
about that where we were like and this

is like cuz of course we've got a thing
we think really big if we're not

thinking big we're not we're not
thinking well so we blockchain has been

a very popular thing out there now and
we've been looking at different ways

where we can leverage blockchain but the
thing was like okay what is the problem

that blockchain is actually going to
solve for us so we looked at okay for

drivers if we could tie into a
customer's ERP system right and we could

leverage a customer's credit for the
individual trucker because we know that

Walmart's always gonna pay and now we've
got visibility through their ERP system

and now it's almost like that small
trucker has the credit of a Walmart and

now they can grow their fleets and get
really good equipment so those are

that's one of the use cases we've kind
of looked at but solving driver shortage

in particular we really haven't looked
at doing that because that's not really

our business model but we have looked at
different things and how can we

incentivize the companies to grow
through giving them quality free you

know that's some of the things we looked
at there is a one startup that's um

that's up-and-coming right now they're
in talks with Volvo on their first round

of funding they're actually at 80 BC as
well and they're focused on driver

shortage their company it's called spot
queue really cool companies so what

they're doing is they're saying so the
electronic logs are in place now and

it's it's a big problem you know no more
fudge in the books or anything like that

so drivers can only drive
ten hours right then they gotta shut

down for a certain amount of time a lot
of times they will run out of those

hours based off of being at a dock a lot
longer getting their truck loaded or

unloaded so they're running out of time
admit route to drop off a delivery

so what spot queue is doing is they're
keeping track of the hours of operations

and before that truck has to shut down
they're able to bring a quality driver

in that truck by using a crowdsource
model it's already vetted already

qualified so now that load could be
delivered so they're in talks with Volvo

right now very serious talk Sonam they
could be making a splash in the industry

so hopefully my buddy could solve that
problem and then we could just leverage

his technology
any other questions no no they we

definitely measure maintain the
relationship with the shipper and we

manage the relationship with the carrier
because the large shipper that's the

thing they don't have a bandwidth to
work with these small guys that they're

small and you know they're just like
look we want to work with one entity and

then have access to thousands of assets
you know so that's how it works so we'll

always maintain that relationship just
to make sure that levels of service are

there and then that the transactions are
working the way they're supposed to

network they keep them Network so I'm
trying to understand your overall drive

to not not there's a great question so
when we went to the there are companies

out there and really big companies that
like for example Lufthansa they came to

visit us yesterday they came all the way
from Frankfurt we've had been talking

with them for six six months connected
with them in Silicon Valley they came

they have so many regulations because
they're international airline right so

they have a carrier base that they
already work with that's already

qualified so their problem would be an
outreach just like Braska brass concezio

moving these chemicals we don't need
more capacity we just need to be more

efficient internally so we just seen
that as an opportunity just to get hooks

in additional customers yeah absolutely
so we're still working to the revenue

model but it'll be an integration charge
and then for every load that's moved we

will make you know a spread off of that
but if you look at our margins in the

industry how thin they are and then if
we can incorporate the SAS product in

place of that will actually come out a
lot better with hooks and our customers

that are a lot stronger but we can if
you've got some good ideas I definitely

know

because yeah sure no I appreciate we're
going to talk offline about that

definitely you know hey we we by no
means know everything you know we always

need help
definitely I appreciate it yeah we're

all set we're good all right thank you
everyone right now into the wonderful

world of parts and manufacturing right
it's a great job of Mari

yeah invigorating so I'm Paul Noble I'm
founder and CEO of audit and we are also

an 80 DC company so I'm uh even less of
it than a stone's throw away from Omari

and his team and what our organization
does is we are using artificial

intelligence developing a platform that
harmony harmonizes parts data and

predicts inventory in the manufacturing
supply chain so I'll jump quick into a

brief overview of my background and how
we got started so I grew up in the

supply chain in my you know early part
of my career I worked for Sherwin

Williams for a little over 10 years most
of that time was spent in the industrial

manufacturing supply chain industrial
distribution channel and so we would

sell our book of brands and products
through distributors like Grainger and

fasten all HD supply to industrial
manufacturing customers so I worked on

large deals to go to a you know
coca-cola or UPS and sell them our

products at all their facilities and and
then subsequently ran the eastern US

business unit within that group about a
thirty million dollar business unit and

more and more
on my time doing it kind of in the

trenches by myself as well as leading a
team across a large geography saw that

there were massive data problems within
the supply chain and it was affecting my

business it was affecting my distributor
partners businesses and it was costing

manufacturing companies millions and
millions of dollars across their

enterprises so after feeling that pain
for a long period of time I decided hey

let me go tackle this myself so I'm not
a native Atlantan I'm from Cleveland

Ohio originally moved with Sherwin
Williams to Atlanta and after I was here

for a few years before starting the
company and we initially started it as a

sales enablement company for suppliers
and distributors to better serve

manufacturing companies and I got
connected to a TDC and it was really a

testament to the ecosystem of you know
how we were able to develop as a company

company early on and how we've continued
to develop and I'll talk a little bit

more about that as we get into my
current team and how we met at a TDC but

just to give some exposure for those
that maybe aren't as familiar with the

startup ecosystem and you know all of
the great resources you have here we

feel very fortunate to have you all as a
resource to us and the connection to

Georgia Tech but this entire Atlantic
ecosystem is you know right up there

with you know competing with Silicon
Valley New York Boston Chicago so be

aware of that there's a lot of
opportunity here and now that's why we

really took took notice and decided to I
had opportunities to move out of Atlanta

but decided to plant our roots here and
build the company here which we're

really excited on the trajectory we were
going so so started this sales

enablement
company and don't want to bore you too

much with that but as Amari talked about
and startup life fail fast so we

realized that we were in the kind of the
wrong part of the supply chain while I

knew what the pain points were of being
a supplier and I knew the pain points of

the distribution partners we were too
far downstream from the actual problem

and we were with parts of the supply
chain distribution and supply that were

too far behind and technology to adopt
something that we were developing for

them and wasn't a big enough pain point
they were worried about competing

against Amazon and getting an e-commerce
site and adopting a CRM not bolting on

something that can help them you know on
top of something like Salesforce so with

that said about a year ago we pivoted
and we began focusing and we've learned

a lot in that process about those data
challenges and went to the manufacturing

customers themselves
and what we discovered and what I'll

kind of get into here is really what our
business is today and what we've been

developing over the last year and what
we realized is that yes data was a

problem but why was it a problem and if
you think of global manufacturing

organizations they spend trillions of
dollars on parts to maintain their

assets and facilities as well as produce
their products and if you look at

something like automotive or equipment
they also have service parts networks

that they need to manage and that data
is you know in the millions and millions

of movements and data points so what's
the problem

it's the systems that they're running
off of so si P Oracle all these legacy

ERP systems that they're running off of
it's not that they don't want to manage

this data better so that the systems of
record that they're working off of were

invented before the internet so they're
by nature extremely disconnected a mix

of on-prem and cloud and all sorts of
you know various instances

Frankenstein's systems like Amar'e was
talking about

they've just been plugging holes and
trying to each organizations trying to

figure out these problems so what that
causes is disparate data so you picture

a global organization you're a VP of
supply chain and you have all these

different silos of data across the globe
so how can you manage that as one

organization so that's the first problem
and then the addition in addition to the

disconnect if 'ti everything is still
very manual in those systems so if you

look at you know parts so we're focused
on maintenance parts you're talking

about like Siemens motors and Timken
bearings and all these things that make

the facilities go when a company orders
that Siemens gives them the physical

good they don't give them the digital
footprint of that product so if I'm

coca-cola bottler I get the motor and I
have to enter that into mysap system

manually and there's charactered
limitations and there's all these manual

entry points for inventory and
criticality and all these things that

are just way too difficult to manage so
as we were developing this business we

knew about the that pain point and we
meet we knew we needed to solve the

problems that these legacy ERP systems
were creating so at that point we

figured you know what is there to help
make human superhuman especially around

data it's artificial intelligence so we
began developing this platform to be

able to essentially look at these issues
at every individual organization where

can we show value to a global
manufacturer and so we took that

information and we began building an AI
that can go in to the ERP system and

read these material master records that
they have so you picture all the parts

needed across a global enterprise it's
hundreds of thousands of records and

there's massive amounts of duplication
and all those manual

problems are just incredibly challenging
to wrap your arms around so we have an

AI that first reads that and understands
the different variables that you know

you may call something a motor one thing
I may describe is some more something

else so when you have all these people
across an organization and during this

data it's all different so we can go in
and read and and merge and classify

things that may be duplicates and really
right-size the data and understand

what's there and what they use and it's
not your traditional cleanse we're not

cleansing it to make it EECOM ready data
with all the attributes

we're just understanding what it is so
that we can better wrap our arms around

it to start and because it's real-time
we're consistently making it better on

top of that the disparate data that we
talked about we're able to merge that

whether it's the same ERP system or
multiple ERP systems a lot of the issues

caught are caused through mergers and
acquisitions so if I acquire a company

typically you're just stacking their
data on top of your data and it's just

companies that grow that way
specifically or a target of ours because

their pain point is huge so we merge
that and create a global source of truth

so they can run their company off of the
same data makes pretty easy sense but

it's not that easy to do so everyone
understands and you see a ton of data

companies and everyone understands that
data is really really important but it's

really hard to monetize the value in a
lot of cases right so there's a lot of

traditional methods out there that that
you look at that are ecstatic so a

consult
I heard consulting company they come in

cleanse my data they give it back to me
in the next five minutes later it's

already starting to deteriorate right
that's what we're attacking in many

cases or there is a software solution
using older technology and linear

regression models and all sorts of
different things like that that you know

you can't really put like
I cleaned my data now I hope it saves me

money as a business so one thing to keep
in mind as you're entering the business

world or as you're doing business is
while the technology may be cool how's

it going to save these organizations
money especially the types of

organizations that we're working with
right so keep that in mind so we kept

that in mind as we're developing this
and that's where that third part of that

is so we're using AI to take all of that
material record data and marry it to

inventory movements so there's hundreds
of thousands of data records and then

there's millions of movements across
this organization so that's movements

like I ordered this from the supplier
then I received it on this date and then

I issued it to the maintenance person
and then or they put it back into stock

like all these movements are really
difficult to to manage and understand so

what happens is that because the data is
bad because there's so many movements

it's hard to really grasp companies are
wasting tens of millions of dollars in

working capital they're working off of
subjective inventory management

strategies so it's they go if I stock
more I'll be more reliable because as

we're talking manufacturing any of any
business that inventories things but

specifically in manufacturing it's all
about you know Six Sigma reliability

right so we're talking Six Sigma you're
saying Ari I want to be 99.999% reliable

always have things in stock so if you
tell me to stock less I think that I

might run out so I don't want to do that
so that's why there's this disconnect in

inventory optimization a lot of cases so
what we do is we take movements from

five ten years of history and we relate
it to a Sigma level so we can optimize

stocking levels with that data so we can
actually tie it to dollar related

outcomes so we can say you can reduce
your inventory by thirty percent which

is our average
right off the top because there's so

many problems and it's been overlooked
for so long and you can remain Six Sigma

reliable and we make it very easy I
don't have a demo to show you but we

make it very easy they can look by plant
and just essentially say all right what

does it cost me to be Six Sigma 5 Sigma
4 Sigma what does that save me dollar

wise and how can i optimize that for the
entire organization or plant by plant

you know some plant managers won't want
to roll the dice

others will to save money on their you
know profit and loss statements so so

that inventory prediction is important
and that's really what we look at as a

value initially to our customers right
we have to we know that we can't just go

and like hey we have a high it's gonna
help you you'll learn more and you'll

get better believe us please you know so
we want to show them value upfront which

is this working capital reduction when
he talks and that's what we do to help

and it helps us understand but what it
also does is that's our data acquisition

strategy so AI as you know needs a lot
of data to learn from and be trained

appropriately and what to look for so
this data acquisition strategy is so

important because it gets the data
flowing and we can learn by their use of

their ERP system so we're not putting
them into a new system we're essentially

the intelligence behind the scenes of
these ERP systems so as they use si P we

can understand the types of decisions
they make and how that related to a

dollar outcome and learn whether it's
positive or negative and use the future

learnings and not always looking back to
the history to improve predictions over

time for them across different business
units why that's important and this is a

bit of a case study of like what we show
a customer right so this might give you

a better understanding so if you look at
what we go in we look at material master

data
movement history how much are you

inventory how much are you holding
typically it's about 12 months of usage

or need that organizations are planning
for and some plan look at this maybe

every month maybe a quarter maybe once a
year sometimes never right so this

number just keeps inflating but on
average is about twelve months so we

give them 12 months here's what you hold
and then we we create a baseline of what

do you actually use every month so
that's pretty simple it's not hard to

figure out and there's a massive gap
between that and so we we joke around

and call that god mode so like if you
had no inventory and everything appeared

right when you needed it this is what
you would spend and so that's where we

start attacking and that's where our
technology essentially learns from their

organization and we take that total
inventory held number and we keep

shrinking it and shrieking it so we say
to our customers we're gonna take you

from this just in case objective
strategy more and more truly just in

time and you'll become more and more
reliable for less and less money and

less inventory held so that's really
beneficial to each individual

organization you know but as we said
we're looking at a specific part of the

supply chain which is maintenance repair
operations so this is a I think I have a

slide on this too I'm jumping around a
little bit but it's a huge market in

itself and it's a it's a niche that we
can really carve hook in go dominate

early write deserve is our vision but
all of these same companies so back to

the disconnect if 'ti you look at a
couple of our cups customers and

pipeline for instance so if you look at
Mohawk industries and graphic packaging

international both Atlanta based
companies an ABN Bev and Kimberly Clark

and Georgia Pacific they all use the
same products generally speaking from a

maintenance perspective same motors same
drives but they're all independently

even as siloed as they are in their own
organizations they're all working

in silos across these organizations
right so what we're doing from a network

effect perspective is we're reading all
of their catalogs and we're anonymously

understanding the Siemens motor that's
used by all of them we create a master

knowledge base around not only
attributes but reliability and usage

data that allows us to improve
prediction and data control across our

network of customers so it's not data
sharing and set necessarily it's just a

deeper understanding so we're creating a
brain around mro that can sit on any ERP

system and can help the network effect
and allow them to know that if they

don't use a part as much as someone else
what may they expect from that part in

terms of reliability and help improve
their inventory prediction so not only

is that they're a network effect there
but there's also you know why are we a

recurring value why should a customer
keep us hooked in after we showed them

this big pop of savings in year one Abe
we're gonna continue to show him better

and better savings but it won't be as
significant as year one but be the it

goes back to large organizations what a
I can allow them to do is where they're

really good and this is what we work
long-term with a lot of customers on is

you you think you know Kimberly Clark
I'm really good at what I do in North

America but South America is not so good
and we're moving into Asia and we have

operations in Europe so what a I can
help them do and what we specifically

help them do is transfer knowledge from
their best people to the system so the

system begins learning at what the best
demand planners are what the best

inventory management personnel that they
have from making their human superhuman

back to that whole analogy it allows
them to transfer knowledge to the system

so the system begins to be smarter and
we eliminate the variable

so everyone becomes more level at the
highest level which is really intriguing

because it's very difficult to Train all
of those individuals as people turnover

retire a lot 99 percent of that
knowledge is locked in their personnel

z' heads so so what this does is for us
allows operations procurement and

finance to have a unified strategy you
know from this perspective so operations

gets their confidence that they'll
always have what they need to be

reliable and operate the plant maximize
uptime for the lowest cost procurement

can drive out costs because they have a
better understanding and can drive down

inventory and eliminate tail spend and
buy from more streamlined vendors and

then finance knows what is what are we
spending where do we have opportunities

to save working capital and how can we
have a greater finger on the pulse

across the organization so this is the
really cool part though so we talked

about that's all boring stuff so we
talked about you know intelligent

digital supply chain right that's our
vision is we do all these things to show

value but what we're trying to do and
what we're building as a company is this

connected intelligent digital supply
chain so that the information of what

manufacturers are using can better
connect them with their suppliers of

those parts so they can understand how
they're being used right now that part

of the supply chain is completely
disconnected so by going to the

manufacturers as we did we're now rather
than swimming upstream with the original

business that we're developing we're
swimming downstream and passing relevant

and good data through the entire supply
chain so each part can do what they do

better they can understand how their
products are being used if I'm Siemens I

know how my products being used I know
you know better forecasting I know how I

can improve my product cuz I know how
it's being used by my customers which if

you know distribution really
you have zero visibility when I was a

supplier I had zero visibility of who
was actually using my products unless it

was an isolated case where they called
us in or a distributor of ours brought

us in so that's really powerful so that
the point of that is the is creating a

digital footprint of physical goods and
so we start with the value to our

customers in vendor optimize inventory
and procurement working capital but

where I'm really excited about what this
can do is that we can now understand the

digital needs or the needs in general of
what what type of parts can be printed

on demand right so through additive
manufacturing what are they inventory

now that could they can eliminate from
inventory and begin to print those parts

and transfer digital rights from Siemens
rather than actually Siemens having to

make and shift and inventory the
products to them how can we leverage IOT

systems and understand all of the data
that's being pulled from an asset and

you're predicting maintenance failures
but then you go back to the old way of

you know ordering something and pulling
it out of stock we want to connect that

system and those different systems so we
want you know we're essentially creating

this central eco system where the
digital digital footprint digital rights

are all understood and can be
appropriately distributed and again I

joke about this there is certainly a an
opportunity for a trusted ledger but it

wouldn't be a start-up presentation if
we didn't talk about the opportunity for

blockchain in our business model right
and we might do an IC o---- so soon -

all right so the technology itself from
a blueprint perspective and is that

house we're building or we're focused on
specific things that we know it's into

materials its maintenance but as we're
building the technology there's the

opportunity for we've already been asked
many many times by customers and

prospects hey can you do this for our
direct parts the the parts that go into

our automobile or the raw materials that
we buy can you look at specific signals

yes we can so we're looking at that and
we see it as an applicable growth with

each of our customers because they have
both and the use of that technology to

really optimize more of their supply
chain and digitize more of their supply

chain and so as we as we look we're in a
fortunate situation that we've partnered

and we're selected to partner with sa P
so they have a you know s ap recognized

and you know continues to work with us
so they have a program called si Pio

this is their innovation arm rolls up
into their strategy group and so we've

been splitting time between Atlanta and
the Bay Area in San Francisco working

with them understanding deeper a deeper
understanding of the challenges that

their system causes where they're going
and where we can help integrate more

effectively and not be working against
each other but be working with each

other on how can the seemly seamlessly
be added to add value to their system

add value to their customers and get
them you know moving their customers

from on-prem to the cloud as is one of
their number one focuses as an

organization so for the us that was
super important as a start-up to get the

validation of the system we're building
off of for them to bring us in and if

you know anything about sa P or Oracle
area these behemoth ERP systems they're

really difficult to work with even when
you have a relationship with like ours

so that's been really important for us
as we continue to work with customers

but to try to work with them without
that would be really really difficult

and it what it did for us as a start-up
is it you know if you're attacking a

market and there's a market leader there
or so

one that is that system of record you'd
be surprised how important it is to

really go verify your assumptions so we
had a lot of assumptions of where we

could help based on the customers
telling us their pain about SI P but it

was so important accelerated our growth
as a company you know by at least a year

if not more by actually working with
them over the last several months

concentrating on the back end and like
what do we need to do to integrate and

make this seamless in real time and
position us to effectively take what our

customers are telling us and make it a
reality so we went into this our target

customers are manufacturing customers
five or more plants as they grow as the

number grows the problems grow so we're
looking at you know probably even more

10 plus plants you see the problems
continue to grow and we're focused

obviously on si P but we also see this
applicable to other systems as well and

work with those customers and these are
some of our customers as we've mentioned

so cool story about how we met and back
to it sounds like a commercial for ac/dc

but we love it that much so 80 DC is a
great spot it's even the past 3 years

that you know we've been there it's
grown significantly and these are my

co-founders so both Georgia Tech grads
Gerald Moss is a neural AI expert so the

AI we're talking about as neural AI it
allows just kind of go crazy right and

learn learn as it learn as it goes he's
also a part of the perpetual lab as a

fellow and we met through ac/dc jr. and
George they were working on another

business that was just wrong time data
problems in the manufacturing space a

common theme there they were working at
a visual recognition technology for

parts so you may be familiar with a
company called

heart pick that was acquired by Amazon
that within last year - they were

working on something very similar called
part scope and we connected initially on

our original ideas and we're looking
like how can we work together we were

working with a lot of tool manufacturers
so on and so forth

but it goes back to what Amari talks
about from a relationship standpoint and

how important network can be and meeting
new people and understanding people that

are focused on different things than you
are because things come back around so

fast forward a year or so later we had
made our pivot part scope wasn't working

out as effective as while the technology
was cool it was just a nice to have the

data was the problem we were
experiencing the same thing the data was

the problem so we came together and we
had that common common thread and we

knew AI didn't was a solution so through
a CDC we connected and and have

developed our our current product in our
current company from there so I just

think it's you know it's a really a
testament to the ecosystem the tech

ecosystem and and and how it ends so
other than that from where we're at as a

company we're you know finalizing our
first institutional funding round so

we're gonna be growing significantly
over the next six months and beyond you

know double doubling or tripling the
team within next few months and hiring

engineering resources hiring sales
resources to to really give this a go

and attack the market very very quickly
so I guess with that you know the time

wise I don't know how well I was on time
all right cool we can yeah answer any

questions you might have
yeah

a cloud-based or is it like a is it a
black box is there some kind of

dashboard it's a magic box
no um one of our customers actually use

that these are the magic box so no it's
yeah it's uh cloud-based yeah through an

API and and we can where we could pull
the right data points to understand and

and organized and then we do have a
dashboard of sorts and reports that they

can see you know all of that complex
data presented to them and like

suggestions of where they should make
you know we we use predictions so we'll

give them a prediction from an inventory
perspective and they can either take

projection or not taking the prediction
and then we'll learn from that yeah so

we can understand the usage of someone
that's just placing orders and doing

things like that like that specific data
but then there's also typically

inventory optimization teams and
planners that are looking at this you

know from a business unit or a geography
or you know global perspective that will

be making more of like the specific
decisions and strategy decisions off of

that information

yeah yeah so yeah with that change of
you know companies that are invested in

older instances of Si P there are it's
easiest with someone that's moving to or

is on the s4 HANA platform or any cloud
base TREC ERP system easier to integrate

easier to take advantage of those
raishin so that's much more seamless in

what we're focusing on from a product
perspective but any any customer that's

on more of a legacy system depending on
which version that is there are ways

that we can map the data out of our
premise systems it's just less real-time

you know it's still dramatic we we joke
that we take these customers from you

know the Flintstones to Leave It to
Beaver if anyone gets those references

before we need to take them to the to be
the Jetsons so to speak so we can work

with any customer on any system we can
work with CSV exports from you know a

non-si P system or JD Edwards or
something like that an old model but

certainly we're targeting the lowest
hanging fruit which is those customers

moving to cloud or already on the cloud

yeah yeah so it's not it's not something
that you can just like at this point

we're working towards that where you
just download and it it works across the

enterprise right so there is some
understanding and integration involved

but our integration strategy is much
less than you know adopting a new ERP

system so we typically give a time frame
about 90 days that we can understand get

in at that point to now as we're moving
forward with the customer and do a

contract a contractual relationship
we've already done analysis we've

already seen their data train some of it
understand that so we can begin showing

value almost immediately and can do
those analysis the analysis really

quickly

yeah

yeah so there's um we you know it were
asked about competition where so things

that we're seeing are some software
based solutions that are using machine

learning and and more traditional
algorithms to look at some of the same

types of data and offer similar results
where we're a little bit different we

haven't seen you know our particular
approach as specific tying data harm

inventory optimization and deep learning
kind of all together and so we think

we're a little you know we're on the
leading edge of that we do see these

technologies that will be adopted by
more you know see our window closing

within the next few years of that worthy
the one with this technology but we're

also looking a lot of what we're
attacking is project-based work

consultant based work consultants that
have developed procurement type software

or software that you know goes on you
know with humans behind the scenes

analysts behind the scenes is really
much of this space we're tacking but you

know it's we're certainly not without
competition but our unique approach has

us a little head of the curve

yeah
so to start like where we perform our

initial analysis analysis there is
neural net but looking at history is not

it's not as needed it's really creating
that baseline so we can learn a lot and

do some optimization there but it's you
know where we're using the neural that

is based on when we were to hook in and
learn from the decisions so that's

really where in from an inventory
optimization standpoint where we can

take each individual decision and add it
to the prediction models yeah that makes

sense yeah it's more looking forward and
a knowledge transfer

that's that where it's being used and
applying it to that prediction

yeah very much very much so yeah no
thank you for that and it's something

that were consistently trying to remain
focused on because we we do get asked a

lot of like because that direct
materials piece is a bigger component of

revenue for a lot of these customers so
they're you know we understand and we've

gotten less away from getting pulled in
a lot of directions and focusing on the

data component itself and being focused
on that but we're very very much

committed to building the MRO niche
right now because it is so valuable and

it is you know even more unloved than
the other parts of the supply chain

thank you thank you more questions

yeah

yeah so we're gonna be doing more more
traditional marketing type type targeted

marketing ABM type marketing account
based marketing and we know the types of

customers that would be a good fit so
we've been targeting those that were

either introduced through Georgia Tech
and ac/dc or sa P is bringing us into

deals or with consultants that are
bringing us into deals and then we're

doing direct outreach on our own so we
haven't had to just like you know do a

bunch of traditional marketing things
where were you know targeting through

ads and stuff like that we're really
just going to people that we know have

this problem and just saying hey this is
what we do let's work and based on our

value to them we don't need we don't
need hundreds of thousands of customers

like our revenue model is SAS based but
it's based on physical locations of how

many plants do you have and that metric
is really important to our growth so

that that yields that we need you know a
handful of customers to be really pretty

successful from a start-up perspective
so we're just focused on like hey let's

find those that have the most specific
need that we can be directly connected

with and then we're gonna be adding to
the funnel dramatically over the next

year good question yeah so we're working
with them directly on on some proof of

concepts where they're testing our
technology on potentially being in

specific modules

yeah we really enjoyed it I love doing
things like this and wherever we can be

helpful
anyone else pacifically please reach out

it love doing these types of things yeah
thanks for the time