April 23, 2024 • 47 mins
Encapture is the intelligent document processing platform that helps companies be more efficient and customer-centric.
Encapture uses machine learning to help employees stop wasting time on mundane and repetitive tasks so they can focus on better serving their customers.
Banks, lenders, insurers, and companies with high volumes of paperwork trust Encapture to keep their operations efficient, secure, and humming. Our customers tell us we're a refreshing alternative to traditional enterprise capture software given our platform is easy to use and scale.
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Episode Transcript
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Intro / Outro (00:02):
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(00:22):
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Kevin Horek (00:34):
Welcome back to the show. Today, we have Will
Robinson. He's the CEO atEncapture. Will, welcome to the
show.
Will Robinson (00:40):
Thanks for having me on, Kevin. Glad to be here.
Kevin Horek (00:42):
Yeah. I'm excited to have you on the show. I think
what you're doing in the AI kindof machine learning bank and
lending space is actually reallyinnovative and cool, but maybe
before we get into all that,let's get to know you a little
bit better and start off withwhere you grew up.
Will Robinson (01:01):
Yeah. Sure. I'm a I'm a Texan. I grew up in Dallas
and went to school down atBaylor, which is Central Texas,
big family school for for me.And, you know, it's funny.
I I kind of I was a I was afinance and econ major, like, in
the business school and kind of,you know, thought I wanted to
(01:22):
kinda go down this financecareer. And I moved to New York
City and, worked in finance for4 or 5 years. And I worked a lot
with tech companies and reallyjust fell in love with with
technology and software and feltlike it was going to change the
world, and thought, hey, I wouldlove to I would love to be an
operator in this space for mycareer. So, that's how I got
(01:43):
into what I'm doing now. I Iworked for a big tech company
before here in Dallas, beforejoining Encapture and kind of
being on the ride that we'vebeen on for the past 5 years.
Kevin Horek (01:53):
Very cool. So what got you passionate about finance
at an early age and made youwanna go into it at least to
begin?
Will Robinson (02:02):
Yeah. That's a good question. I I've always
been kind of a math and numbersguy, and Okay. I thought it was
interesting to kind of learnhow, companies raise money to go
do things Sure. Showing thefinancing side of that.
And so, and candidly, I had areally funny experience. I did a
summer abroad, one summer and Iwas talking to some, some other
(02:25):
American students. We were atlunch one day and I remember
saying, hey, you know, nextsummer is the, is kind of the
last summer of college, and whatare you guys gonna do in the
summer? And they all said, well,we're gonna move to New York
City and do investment banking.And I I had no idea what that
meant.
And so I remember going back tomy dorm room and, like, googling
what is investment banking andand why you know, if if all 3 or
(02:46):
4 of these guys wanna do that,why is it? And and kind of
thought that, hey, this could bea really interesting start to my
career and a place where I canlearn a ton. And and it was. It
was a great it was a greatstart, and I felt like it's
really propelled me to to dowhat I do now, albeit with a
different background.
Kevin Horek (03:01):
Got it. Makes sense. So walk us through what
exactly is Encapture, and, let'sdive into that.
Will Robinson (03:10):
Yeah. So encapture is a machine learning
platform. And and by the way,I'm gonna try to stay away from
a lot of buzzwords, and if I usethem, we'll talk about what they
mean. Sure. But we, have theability to help process
documents as part of kind ofthese really paperwork intensive
workflows at banks and lenders.
And so specifically, our machinelearning can read a document and
(03:34):
it can understand the system canunderstand what type of document
it's looking at, and then it canpull out the important
information off of that documentand use it for a variety of
different things. It can put itin another system. It can check
the data across multipledocuments
to make sure that the data is consistent. It can
check
the data against a third party system to see if
(03:54):
there's any discrepancies. Andreally what we are eliminating
is a lot of manual data entryand a lot of kind of stare and
compare processes at these bigbanks and lenders. So a simple
example I use is something thata lot of people, if you've ever
bought a home, you can relate tothis when you're applying for a
mortgage. You You know, youyou're talking to your loan
(04:16):
officer at the lender andthey're saying, okay. You know,
Will, you're gonna buy thishome.
We need to see how much how bigof a mortgage you can afford. So
I'm going to need to collectsome documentation from you, a
recent pay stub, maybe a coupleof years of your tax returns.
I'm going to need to make sureyou're real. So, you know, send
in a copy of your driver'slicense or passport. And so the
lender is collecting all thesedocuments to kind of make a
(04:37):
credit decision.
But a lot of times in thebackground, there's people there
manually reviewing thesedocuments or putting this data,
you know, trying to figure outhow much money does Will make a
year, what's his income, howmuch does he have in the bank,
etcetera. There's a lot of roomfor automation around that. And
so that's where we play kind ofin the back office, helping
process these incoming loandocuments, pulling out the
(04:58):
important data, and making surethat the bank can do something
actionable with it.
Kevin Horek (05:03):
Interesting. So how did Encapture or Encapture come
to be, and and what made youguys actually decide to build
this thing?
Will Robinson (05:13):
Yeah. It's a it's a good question. The company
itself is 25 years old. So
Kevin Horek (05:19):
Okay.
Will Robinson (05:19):
We I joined this company about 5 years ago. It
wasn't even called Encapture atthe time. Okay. But I joined as
part of kind of a private equityinvestment that the company
received. And, we hadhistorically been a kind of a
professional servicesconsultancy on behalf of some
really big software players.
(05:40):
And we would come alongsidethese software vendors and we
would help them sell theirsoftware. It was all around
workflow automation and kind ofthis back office document
workflow review. And we wouldcome alongside them. We would
help them sell it. We wouldimplement the software.
We would, you know, we justcharge kind of an hourly rate to
do that. But the company, gosh,maybe 10, 12, 15 years ago
(06:03):
started building their ownproduct called encapture to help
collect the documents upfront,just make sure that the that
the, you know, the end customerkind of had everything that they
needed, as part of the workflow.And so the company would kind of
resell, you know, their vendorsoftware, but then sell a little
bit of encapture as well. And,when I joined about 5 years ago,
(06:23):
the strategy was, well, it'sgonna be a lot more interesting
for us as we think about growingto invest in our invest in our
own product more, invest inEncapture. At the time, machine
learning was kind of just cominginto its own in terms of its
capabilities around meetingdocuments and extracting data.
And I felt like we would bebetter off as a company to
(06:46):
really pivot away from theprofessional services and these
legacy partnerships and insteadbecome more of a pure play
software company. And and so,obviously, that's that's easy
that's easier said than done.Never said. Yes. I don't, I
don't necessarily recommend thatas a default strategy for for
most businesses.
A lot of businesses try to dothat, say, oh, we've been a
(07:07):
we've been a services company. II want to be a software company
now. It it's taken a lot of workand effort and blood, sweat, and
tears to do that, but but we'rethankful that we've been able to
do it.
Kevin Horek (07:19):
No. Very cool. I I wanna cover that a little bit
before we dive a little bitdeeper into what you're doing
today. Did obviously, you usedkind of the consulting side
though to build a product, like,to fund it, I mean, or or did
you raise money or or walk usthrough that.
Will Robinson (07:35):
Yeah. Good question. So the consulting
side, that was kind of our cashcow at the time. So that's where
we were making all of ourprofit. That was, you know, the
historical business model.
And so, you know, we didn't justturn that off overnight. And
that's what was so challengingabout kind of rebuilding the
company and and and pivoting thecompany while you're still
trying to, you know, do thething you've been doing for a
long time. And so we use the,you know, the profits from our
(07:58):
consulting to really reinvestinto, into our our software
platform. And that was a veryincremental process. It took I
mean, candidly, it took us, youknow, 3 to 4 years to
completely, kind of let go ofall of our legacy consulting
business, and become kind ofthis pure play software
business.
And so I'm thankful my investorswere were comfortable with that
(08:21):
strategy and approach. Youdefinitely have to take kind of
a long term vision to be able todo that.
Sure.
In in terms of raising money to do it, we
decided that we just wanted tofund this, organically. Okay. We
you know, there were pros andcons to both, but we felt like
we felt like in the long run, itwould be better for,
(08:44):
mechanically better for theshareholders and and better for
us as as leaders of the businesswho also were shareholders. We
felt like we could create morevalue over the long run by doing
this ourselves versus going outand kind of following a
traditional venture capitalmodel where you you go raise a
lot of money and try to goreally, really fast. So that was
our approach and, you know, itwas a really hard decision to
(09:06):
make, especially a couple yearsago when we were starting to
have success and the softwareworld was was going just
absolutely insane from afundraising perspective.
We intentionally kinda sat thatout and said, hey. You know
what? We're comfortable with thegrowth we have and the progress
we're making and the way thatwe're funding that. Hindsight
2020, that was a very wisedecision for us. I feel like
(09:27):
we're in a much stronger,healthier spot as a company,
and, you know, we're not havingto make some of the hard
decisions that that many othersare at this point.
So that's the path we've beenon, a bit nontraditional, but,
we felt like the consulting, youknow, allowed us to fund our own
things. And then also, it itkept us really close to the
customer and their pain points.And so as we as we developed our
(09:48):
product and really built out andcapture, built out the the AI
side of it, we felt like wealways had a really good sense
of the problem we were trying tosolve. And I think that allowed
us to to, not make quite as manymistakes. Still made plenty.
Kevin Horek (10:02):
No. I I think that's really good advice. And
and the company that I ended upbeing a part of that got
acquired, we did the same thing.We were kind of a software
company, and then we werebuilding a product, and then we
eventually kinda switched tothat. But yeah.
And to your point, it's it'shard, but doing a startup is
hard no matter how it's funded.Right?
Will Robinson (10:22):
Yeah. No. It is. I mean, it's yeah. It's kind of
the grass is always greener.
Yeah.
You know,
there are days that I wish, man, if I had just
done this as a start up, Iwouldn't have all this legacy,
culture and legacy kind ofmindset and legacy business
model support. But at the sametime, I I had enough of a
starting base in terms ofcustomer base and relationships
(10:42):
with customers that provided mea really solid footing to kind
of grow off of that and and andgrow the software. So, you know,
wherever you are, whether you'rein a a true start up or you're
maybe in a business that'strying to transform, I think
really leaning into, whateverstrengths you have at the moment
is really important. And and andhonestly, I wish I had moved
(11:03):
faster. I wish I had been alittle bit more bold in terms of
that that transition away fromthe legacy.
I think I hold on a little bittoo long to a few clients, a few
projects, a few people,internally, that I thought, oh,
these people are gonna be ableto make transition with me.
They're gonna be able to be partof kind of the new vision, the
new culture. And, you know,unfortunately, many of them were
(11:25):
not. They they were just verymuch accustomed to the way
things have been done, and itwas better to kind of start
fresh with a lot of roles. Sohad a lot of turnover on that
front, which was not, notnecessarily plan A for us and
definitely hard to go through.
But ultimately, we're a muchstronger organization now
because we have, you know, theright people in the right seats.
Kevin Horek (11:46):
Interesting. Okay. I wanna dive a little bit deeper
into that. So I'm curious, didyou use or did you get to
leverage some of your currentconsulting customers into kind
of the SaaS company that, youknow, in Capture is today? Or or
how did you leverage that andstart getting some early
(12:07):
customers?
Will Robinson (12:08):
Yeah. That was a that was a big part of our
strategy. We had a we had a wekinda had an initial set of
customers. And remember, theseare customers that had purchased
Encapture a decade ago, and theywere still using it. Now they
were using it in a way that wedidn't see as, you know,
necessarily the vision for theway forward, but they they had
the product, they were they wereworking with us already, they
(12:31):
were getting value out of it.
And so we were able to startwith them and then say, okay,
what else can we do for you? Orhere's our vision for where
we're trying to take theproduct. How does that, marry up
with with what you guys need inyour organization? And candidly,
you know, selling into sellinginto banks and lenders is very,
very hard. It's a verytraditional group of buyers.
(12:51):
They have a, they need a lot ofsocial proof, and so having
logos, established logos Ah,yes. Was a huge help for us, and
being able to kind of point tocase studies and say, well,
look, this is what we're alreadydoing for a peer of yours. That
really allowed us, I think, toaccelerate our growth versus
starting from scratch. And so wedefinitely leveraged them. Now,
(13:12):
I will say we got to a pointprobably 18, 24 months ago where
we did have some legacycustomers that were not really
buying into the vision of wherewe were going as a company and
where our product was going.
And we have this choice of,well, do we continue to support
kind of their legacy use casewith the legacy product? And and
(13:33):
for many of them, we we chosenot to. They chose not to as,
you know, Mutual. And we kind ofsaid, look, if we keep
supporting this legacy customerbase, that's just going to
distract us from what we'rereally trying to do. And so we,
you know, we parted ways.
And again, it's hard to hard todo that, to have churn and say,
hey, well, you know, customersare leaving, but ultimately,
those customers were a reallybig distraction for all of our
(13:56):
teams. And there wasn't therewasn't growth in those accounts
that we needed to see or wewanted to see. So ultimately,
even though it was a bit of areset, from a revenue
perspective, it was I I I feellike our portfolio customers now
is a lot healthier, and it's alot more aligned with our vision
as a company.
Kevin Horek (14:12):
No. Makes a lot of sense. So let's dive a little
bit deeper into what exactlyEncapture is. So what was it and
what is it today?
Will Robinson (14:23):
Yeah. That's a good question. So it started as
a it started in the old dayswhere if you wanted to get a
mortgage or a loan, you know,and I I've mentioned the example
of a loan officer asking fordocuments. Typically, the way
you would do that is you wouldwalk to you would go into a
local bank branch, and you wouldhave, like, a stack of your tax
(14:44):
returns, or you'd have yourdriver's license, and that
branch employee would makecopies of of, you know, your
documents, or they'd even keepkeep the kind of the documents
you brought. And they would,have, like, a FedEx truck come
by, pick them up every singlenight, and they would courier
those documents to some sort ofcentral processing facility,
usually in the middle ofAmerica, and people would, you
(15:07):
know, open up your file, open upyour, you know, your document
set and they would start lookingthrough it.
And if there were any issues,maybe you didn't provide the
right documents or you didn't,something looked off, they would
then call the bank branch andsay, hey. You need to call this
borrower back, have them comeback up, and submit additional
documents. So as you canimagine, it's a very, very,
(15:28):
laborious, time intensive, longprocess. I mean, it could take
several weeks for thosedocuments to make their way. And
so, the product started reallyas an integration into the big
scanners, the big multifunctiondevices that we all kind of have
in our office buildings or thatyou have in a branch.
You know, it's the big scannerthat copier machine that's, you
(15:48):
know, several feet high. And,what we would do is we would sit
on we would integrate with thatmachine and so when you scanned
or copied a document, you wouldhit a little button on the LCD,
you know, display that said sendto encapture. And so we would
digitally ingest that documentand we would put it in the right
workflow so that you didn't haveto courier a document to a
(16:10):
physical location. So it's kindof this digitization of of
documents in a very, very basicway that was our original use
case. There was no, you know,there was there was nothing
smarter than that other thanjust sucking documents off of a
scanner and and sending theminto the right workflow, you
know, someplace across thecountry.
You know, where we are now iswe've kind of built on that
(16:32):
foundation of capturingdocuments. We can capture from a
lot of different sources, notjust a scanner, but we can
capture from your email, from afax machine, from a, you know, a
customer portal online. It's allAPI driven, so we can really
kind of ingest, suck indocuments anywhere. But the
secret sauce now is the AI. Andso that was something we didn't
have that we built out, And theAI can do 2 things.
(16:55):
1, it can identify the document,that the system just received.
Am I looking at a driver'slicense? Am I looking at a pay
stub? Am I looking at a taxreturn? There's hundreds of
documents we can we can look at.
And then based on that, can Ipull out the important
information? You know, driver'slicense, it would be somebody's
name or date of birth oraddress. If it's a pay stub,
(17:16):
it's, you know, how much didthey get paid and what's the
time period on that. So I cankind of create a calculation of
your annual income. If it's abank statement, what's the date
of the bank statement?
How much do they have in theirbank account? What are the
debits and credits in in thataccount that, you know, a bank
will use or a lender will use tokind of determine your income?
So it's pulling all these keypieces of data, and that's
(17:39):
really what we've evolved to.And that's where there's a ton
of efficiency gains that theselenders have because they don't
have to do that, sit there anddo it manually.
Kevin Horek (17:48):
Very cool. It it's it's fascinating to me. Maybe
banks well, I don't know thisfor sure and you can correct me
or you could tell me your answeris banks aren't traditionally
known for being kind of cuttingedge on technology, but the the
I've had some people kind of inthe Fintech space recently on
the show, including yourself,where banks are actually
(18:11):
leveraging a lot more kind ofmachine learning and AI, whether
it's, like, from a third partyvendor like yourself or they're
building it internally than Iever had, like, ever thought of,
which is awesome. I'm I'm gladthat's the case. So I'm curious
to maybe dive a little bitdeeper into some other real life
use cases because right now, AIis the hype.
(18:36):
You know, Apple calls it machinelearning because AI is scary to
a lot of people. It's arguablythe same thing or, like so where
where are we at and kind of whatis the state of kind of Fintech
and banking leveraging some ofthis technology, and then how
are you helping with that? Yeah.
Will Robinson (18:53):
That's a great question. There's there's a lot
to unpack there. I would say at,like, a 50,000 foot level, we
are kind of peak hype peak hypecycle around NI broadly broadly
speaking. I mean, there's justso much talk about it, and it's
really been generated by thissorry for the pun, but it's been
generated by generative AI, GenAI, the chat gpt type technology
(19:18):
that has really come to theforefront of the market in the
last year. And I think that'sbeen this is one of the first
types of technologies that Ithink from a mass consumer
perspective, people go, wow.
This is really impressivetechnology. That that Gen AI is
not, is very, very, very earlystage at at banks and lenders.
(19:41):
Really, I think across manyindustries. I think people are
still trying to figure out howgood is it and where can we use
it. You know, banks so and I saythat to say there's a lot of
different types of of, andtechniques of AI and machine
learning that, you know, thatexist and that have existed for
several years.
For example, our our, you know,our AI and machine learning is
(20:01):
really under this kind ofnatural language processing and
computer vision type technology.So it's a bit of a different
approach from, the Gen AI chatGPT approach, but and it has
very different use cases. Andso, I think I think a couple of
things. Banks are very muchwanting to lean in to AI. They
feel like there's a need forefficiency and automation.
(20:25):
Just like every other otherindustry, banks struggle to hire
and retain good people. And soSure. It's expensive just to
throw bodies at a problem, andthere's a lot of process in
banks. There's a lot ofregulation that drives process.
You have to do it right, butthey're very open to using
technology to solve that.
But they want proven technology.They want they don't wanna be
bleeding edge. And and they alsodon't you know, they're very
(20:48):
wary of having technologyinteract with the end customer.
Banks
Kevin Horek (20:53):
Makes sense. Yeah.
Will Robinson (20:53):
Banks pride themselves on on that
relationship. Right? A lot ofbanks talk about this. If you
talk to a banker, it's like,hey, we we pride ourselves on
the relationships and providinggreat customer service. They're
not sure AI can do that.
And so, you know, banks arelooking to invest in places like
where we play, which is more ofthe back office, where customers
don't see it, borrowers don'tsee it, but it helps them be a
lot more efficient, in terms ofprocessing loans or generating
(21:16):
reports or doing, you know,certain compliance functions.
Nope. Makes a
Kevin Horek (21:22):
lot of sense. So and you can correct me if I'm
wrong here, is you guys havebeen using kind of AI and
machine learning for years wellbefore the chat GPTs of the
world kind of popped up andbecame, you know, trendy, I
guess, for lack of a better termfor
Will Robinson (21:36):
Yeah. We have, you know, and that's, you know,
we've tried to call it differentthings over the years, to kind
of almost shy away from the termAI because Yeah. You know, it it
kind of made people's head spinwhen you say AI or machine
learning. They don't really knowwhat that means or how it works.
Sometimes they just think it'slike this magical thing, that
just magic you know, it justjust solves all the world's
(21:57):
problems.
And so there's a lot of AI.Yeah. There's a lot of AI, like,
proven AI technology that existstoday that is not Gen AI that
you can utilize in kind of yourexisting businesses or if you're
a if you're a softwareentrepreneur or developer that
(22:17):
you can incorporate into yourproduct that I think is a lot
more proven. It may not look ascool and sexy as some sort of
chatbot that can just talk toyou. But at the same time, it
can provide real value for, foryour, you know, either your
business or your customer base.
And so I, you know, I that'skind of where I encourage
(22:37):
different people to start is,like, yeah, Gen AI is cool and
it will continue to get betterand better. But there's other,
you know, technologies out therethat that can provide real
proven value today where there'sa body of case studies, that
that you know you're gonna getgood value out of.
No. That makes a lot
Kevin Horek (22:54):
of sense. Well, and you're you're using it in a way
that's how do you how do you sayit? Like, that is is useful to
companies. Right? Like, I I'mnot saying a chatbot or
something simple like that isn'tuseful, because they are.
But you're solving, like, a realbusiness problem with kinda
(23:15):
machine learning and allowing,like you said, the back office
to be more efficient. Right? Andthat's what companies are really
paying
Will Robinson (23:23):
you for. Yeah. I mean, if you think about any
sort of b to b, you know,software company, thankfully,
you typically, you know, you youtypically have a buyer that's
trying to make a rationalbusiness decision. If I'm gonna
spend this amount of money withyou a year on your software,
what sort of business return amI going to get? And being able
to articulate that clearly,whether whether you're helping
(23:45):
them, you know, grow theirrevenue or cut costs or,
maintain, you know, compliancewith certain regulations, those
are like the big three that thata bank would think about.
You know, you have to be able todemonstrate that, as part of
your sales process. And sothere's, you know, there's many
(24:05):
different ways to get there, butultimately, you you have to
build confidence through thesales process that whatever
you're selling them is gonnawork. And and so, whether, you
know, whether they see thatthrough a demo or through social
proof with with, other peers oftheirs that have done it already
and can provide a referral callor you can, you know, have a
case study. Like, there's a lotof, there's a lot of avenues to
(24:27):
getting there. But, ultimately,it's got the jet the spin
justification, has to stand onits end 2 feet.
No. That that makes a lot
Kevin Horek (24:35):
of sense. So I'm curious, how do you integrate
with other technologies thatcurrent your current customers
are using? Because I thinkthat's also really powerful
about what you guys
Will Robinson (24:47):
do. Yeah. I mean, it's critical if you think
about, you know, us kind of inthe background looking at all
these documents as they comeinto a bank and pulling out the
data, that that data all has togo somewhere. And so we have a
bunch of integrations with, abunch of the the key systems
that that banks and lenders use.I will say this, in terms of
(25:09):
just general strategy forwhatever industry that that you
may be in, having theintegration solves several
several problems for anycompany.
1, obviously, there's thetechnical side of getting data
from your system to the othersystem that the company needs.
But it also creates some brandidentity and brand, I don't
(25:32):
know, positioning alongsidethose partners where a buyer is
gonna say, well, okay. Well, ifyour software at Encapture
integrates with this system,this system is kind of the the
leading player in my space. Andso if they're willing to work
with you and you guys arewilling to have a if they're
willing to have a partnership,you must be a legitimate
software company. And and allowsyou know, that's been one thing
(25:52):
that's allowed us, I think, togrow our brand is by positioning
through these technicalpartnerships we have, position
our brand alongside some reallybig players in the banking
space, and it it builds up a lotof credibility for us.
So that's an important part ofof of any, you know, soft and
again, I'll speak for for asoftware company, kind of making
sure that you fit in theecosystem and that people your
(26:16):
your buyers or prospects see youas, like, a credible player in
their ecosystem is gonna bereally important to to to
customer adoption.
Kevin Horek (26:23):
No. I I 100% agree with you. I think just the fact
that you leveraged yourconsulting clients to become
customers of your SaaS business,and then you also leverage the
fact that you've worked withthese big brands to help sell
your your your new, you know,your new platform. And then on
top of that, you leverageintegrations. I I think nobody
(26:47):
talks about that as much as Iwish a lot of people did because
it's not really any differentand but some people think that
you have to start from scratchand say, like, well, we've never
done anything for that.
But it's like, no. No. Thesethese people have been customers
for years now, and, you know,we're just moving them you're
(27:08):
just effectively moving them toa different system or product.
They're still customers. Right?
Like and then your to your pointis allowing those integrations
does validate your product.
Will Robinson (27:20):
Yeah. It's it's it's a critical part of the
journey and, you know, thisworld the world is becoming more
and more connected and there'sYeah. You know, there's there's
more and more systems at theseorganizations, so you have to be
able to play nicely with others.
Kevin Horek (27:32):
No. It makes sense. So how did you manage the road
map of when you were building itearly on and and to what now
that it's, like, a living,breathing product that has
customers. Because let's behonest. You have some very well
known banks on there that, youknow, could easily say, we'll
(27:53):
give you a couple $1,000,000 orwhatever the number is to build
x, y, and z.
And you might say, yeah. Okay. Ithink that makes sense. We can
roll that out to all ourcustomers and they would
benefit. Or you could say, like,that's not really in our product
road map or maybe parts of itare.
So how do you kinda manage that?Because that can be really
tricky as a start up.
Will Robinson (28:15):
Yeah. There's there's no easy answer to that.
I think a lot of it depends on,how much clarity you have in
your vision and, you know,funding is obviously a huge a
huge piece. If a big company isgonna give you several
$1,000,000 to take the theproduct in a certain direction,
that's a hard that's somethingthat's gonna keep you up at
night, you know. Is this where Iwanna go with my product, and is
(28:37):
this gonna work elsewhere?
One of the things that we reallyfocus on here and and have and
and try to do a good job of isjust always taking, kind of the,
the customer feedback and relateit back to the business problem
and saying, okay. What's thebusiness problem that you're
trying to solve? And getting areally clear view of that, And
(29:00):
then we will try to reallyinfluence the how we solve it
for you. And what that allows usto do is validate the problem
with other customers. Right?
If a really big customer isthrowing us a lot of money to to
go solve something, is this aproblem that other, you know,
for us, other banks are gonnahave? Is it just other big banks
or small banks gonna have thesame issue? And if we feel like
(29:23):
it's something that we can gosell again and again and again
and kind of solve similarproblems, then we're gonna, you
know, we're gonna probably havea pretty strong point of view of
how we go build that and and notnecessarily want the big
customer to tell us how thatworks. So there's some give and
take there. I think as long aswhen it comes to customers, it's
keeping a clear, clear side onwhat is the problem you're
(29:45):
solving for them.
And and also this kind of bucksprobably, maybe some more
traditional design thinking, oror product thinking. I wouldn't
always rely on your customer toto have the best view of how to
solve that. I I think that partof what makes companies great
(30:05):
and, you know, you can use anextreme example like a like a,
like a Steve Jobs at Apple.Like, he kind of, you know,
would say, hey. Like, peopledon't know what they want.
Right? Like, if people ask mewhat they want, they would never
ask for an iPhone or an iPad or,you know. And so I think there's
a little bit of of, you have togo create the vision and create
the dream, and you're probablynot going to get that from your
(30:28):
customer. And so I wouldn'tthere there's a balance. Right?
There's a balance of ofunderstanding their problem, but
also being confident in yourselfto go build what you think is
gonna elegantly solve that evenif it may be different from what
they say they want.
No. Makes makes a lot
Kevin Horek (30:41):
of sense. So I'm curious to get your thoughts on
because you've been in the theFintech space a long time, what
advice do you like to pass on tokind of founders or maybe people
that are struggling in theFintech space or that have, you
know, that you wish you wouldhave known, you know, maybe
earlier on in your career?
Will Robinson (31:04):
Oh, that's a good question, Kevin. I man, where do
you even start? There's there'sthere's so much so many battle
scars, I would say, from doingit. I think I think if you're a
founder regardless of ofindustry, whether it's Fintech
or or elsewhere or you're you'rerunning a business, This sounds
(31:25):
so cliche, but it's so true. Thepeople you have on your team,
are everything.
I mean, that's everything. And,you know, I used to have people
give me that advice, and I kindajust roll my eyes and be like,
okay, that sounds really fluffyand, you know, whatever. I you
know, I'm a smart guy. I can gofigure this out. But, you just
(31:46):
get to a certain size and scale.
There's no way you're gonna besuccessful unless you have the
right folks with the rightmentality and right skill set on
your team. And, and that's beena big thing that we've we've, I
think, learned from as we'vegone on our journey here in
encapture. And that's probablybeen the the one common theme I
can point to when I look at oursuccesses here, as well as our
(32:09):
failures, is is the people thatwere involved in that. And not
to say that that that greatpeople don't make mistakes. We
have all made many mistakes inour journey, but but really
great people learn from that andcan kind of push through and
figure out how not to make thatagain or how to, you know, build
a more resilient company.
(32:29):
And I think people who struggleare ones who who can't see, how
to get themselves out of that,and they kind of feel like
they're just overwhelmed by the,you know, by the the mistake or
the pressure. And so that'sthat's a big thing is as you get
going, whether you have, youknow, 3 employees or 30 or 300,
really being intentional aboutthe type of people you have, the
(32:52):
culture you're trying to build.And when I say culture, I mean
kind of set of core values andattributes of your team to
create a high performing team.Being very, very intentional
about that is gonna serve youwell even if it even if you run
off some people in the shortterm that you may think are
really critical. You know, I'veI've had people here who, when I
(33:12):
started 5 years ago and theywere existing employees at at at
the company, I would have said,man, if if this guy or this this
girl leaves the company, we arescrewed.
Like, there's no way we're gonnamake it. And you know what?
Like, those folks have left andwe're doing better. We're doing
better because it wasn't itwasn't their technical skill set
that was holding us back orkeeping us afloat. It was, it
(33:34):
was their mindset and abilitykind of be part of the team and
the vision we were trying to do.
Kevin Horek (33:41):
Interesting. Now I I agree with you. I like, yeah,
I I think especially nowadayswith, like, people being remote
more and more, not everybody'sremote or it's hybrid or
whatever, But just having thatkind of team, it's very, very
challenging to build a reallygood team. But if you can get
(34:02):
it, you're so lucky, really.
Will Robinson (34:07):
Well and, like, I would I would challenge it and
say the mark of being a goodleader of a business Okay. Is
your ability to attract andretain the right kind of people
and build that build thatenvironment where they can be
successful and you guys can besuccessful as a company. And
that looks very different, youknow, based on the type of
(34:29):
business you're trying to build,you know, specific values of
that organization. And so, youknow, if you're if you're
sitting there as maybe atechnical leader or a technical
founder who's who's got a reallygreat idea for a product and
maybe can build a great product,that is certainly important, but
you're not gonna go very far, ifyou if you can't surround
(34:51):
yourself with people that canhelp push the overall vision
forward. And so I I I see it aslike a must a must have where,
you know, you're you're justyou're not gonna be successful
unless you have a good team.
You're just not gonna you're notgonna break through.
Kevin Horek (35:05):
No. I 100% agree with you. That that makes sense.
I'm curious then, but how do youtry to retain that talent? Like,
how do you basically get out oftheir way and let them do what
you hire them to do withinobviously parameters, but, like,
to make sure they're successfuland they're happy and they stay
long term?
Will Robinson (35:26):
Man, that's a that's a that's a $1,000,000
question. I think there'sseveral I think there's several
parts at it. 1, creating clearexpectations upfront of, the
type of person that you want atyour company as part of your
recruiting process. Okay. Andsetting clear expectations for
that individual of what the therole and responsibility looks
like.
(35:47):
That's where I I think mostorganizations go sideways, get
sideways with their with theirstaff is it's never really been
super clear on what what goodlooks like in the role. And so
sitting down and really definingthat is pretty important. It's
also incumbent upon the leaderto set clear vision for the
business. This is where I dothink, like, you know, the CEO
(36:08):
kinda earns earns his paycheckor her paycheck is is not only
recruiting a good team, butsetting a very clear vision of
this is where we're trying to goas an organization. This is what
we're trying to this is theproblem we're trying to solve.
This is the mission that we'reon, and making sure that that
people understand that. And andif you have the right type of
person, they'll be able to buyinto it and kind of come
(36:28):
alongside you in that journey.So, you know, setting people up
for success is is the best wayto ensure success. And if you
have clear parameters aroundthat, you'll learn pretty
quickly if if someone's gonna bea good fit at the organization
or not. Doesn't mean they'regonna be, you know, completely
value added if they want, but ifthey've got the right mindset
and attitude, and and they'rebuying into what you're doing,
(36:52):
you're gonna see them be a lotmore productive and valuable to
the organization than someonewho's just got a set of
technical skills, that maybelooks at the job in a more
transactional way.
So, you know, those are the bigthings. Obviously, I mean, you
know, things like compensationand and and parts and benefits,
like, I think those are thingsthat you kinda just have to get
(37:12):
right. I think it's kinda like II heard it described once is
it's kind of like, you know,comp and benefits is kinda like
brushing your teeth. There's a,you know, not brushing your
teeth enough is a problem, andand then brushing your teeth too
much is also a problem. There'sjust kind of the right amount.
There's kind of the right amountand right setup. That's the
sweet spot. And so, you know, Idon't think you have to have
(37:33):
every every perk imaginable ortry to, you know, outdo kind of
the, you know, the Google way,if you will. But if you look at
your company, your team, youknow, your financial
constraints, you you can look atand say, okay. What's important
to my people?
What's important to us? Andlet's just get it right so that
people don't people who don't,you know, you don't have a
situation where people love yourbusiness, love their job, but
then have to feel like they needto leave because something's not
(37:55):
right on the comp or benefitsside.
No. That that makes a lot
Kevin Horek (37:59):
of sense. I also find that not well, not
everybody's motivated by moneyall the time too. Right? Like,
more it seems more and morepeople actually care about, you
know, adding value and feelingvalued and learning at a job.
And if they're making, you know,a little bit less than they
would somewhere else, if yougive them that, like, some
people value that a lot morethan, you know, just making the
(38:20):
most amount of money, andthey're fine hating their job.
Right?
Will Robinson (38:26):
Yeah. I I try to stay away from from that
mentality because those folksand you can identify them in
your recruiting process, theones who are kind of trying to
maximize the money side becausethey'll they'll they'll have job
hopped a lot. They'll kinda havehopped around, and they won't
really have stayed anywhere longenough to, like, I think, truly
grow themselves. And and this issomething I tell a lot of our
(38:49):
our junior people is, like,look, if if you wanna make good
money in your in your job,that's fantastic, and and we're
here to support that. The bestthing you can do is is really
invest in a business where youcan grow and develop your, you
know, your leadershipcapabilities, your skill set,
because that's ultimately gonnaset you up to find jobs that
(39:10):
that that that do provide thatlevel of income that you want.
And, you know, if you're alwayshopping to another job that pays
20 k here more, you know, 30 kmore here, like, you're gonna
look up in 5 years and have had3 or 4 different jobs, and you
really won't have grown andyou'll just kind of plateau out
much at a much lower, you know,call it comp level than someone
who's really invested and grown.So, I I think that's something
(39:32):
to to really look out for. And Iwould say too, like, even in the
more, call it, compensationfocused roles, like like revenue
related roles or sales roles,obviously, you know, that's a
big part of of of, I'm making agross generalization here, but
that's a big part of many, manysales reps is kind of what sort
of money can I make here? But Ithink you need to see if that
(39:54):
type of person is sotransactional that the minute
they get a better offersomewhere else or maybe times
are tough at your business,maybe they have a slow quarter
or whatnot, they're looking tobail versus kind of lean in and
say, okay, hey, how do I makethis better?
How do I invest in the business?Because you're just gonna get a
lot more out of this out ofthose folks.
Kevin Horek (40:10):
No. I I think that's actually really good
advice. So I I'm curious becauseyou've been in kind of the
machine learning AI space for anumber of years now, where do
you where are we at? What do yousee happening? Any predictions
for the future?
Or or or maybe even, just anyother ideas on how people could
(40:30):
leverage this technology whetherthey're in the Fintech space or
not?
Will Robinson (40:37):
Man, I'll give you just some hot zingers here.
Sure. Then we
can unpack if we want to, but I think AI is very
much gonna be highly disruptiveover the next 5 to 20 years
Okay.
Yep. Of our economy. I think I think in the
next year, I think people willstill be kinda dabbling with it
(40:58):
and try figure it out. But Ithink 5 years from now, you'll
really start to see AI havepenetrated certain industries
and use cases that fundamentallychange the way that companies
operate. And and so I'm a bigkind of believer in the the
power of AI.
I I don't have a super here's mynext Zinger, I guess. I don't
(41:20):
believe it's gonna be this, youknow, Skynet take over the world
type situation. I don't I don'tthink our AI is nearly capable
enough to do that nor is ourcompute power on the hardware
side, there yet. Now that couldchange, but, at this point, I
would I'm more in favor of let'slet's give more more people the
(41:41):
ability to access AI and use itand build it versus try to over
regulate it. I think that willdo some some long term damage.
And I think every industry isgoing to, you know, every
industry is getting disrupted byby software and technology, and
that that will continue. But Ithink it will accelerate with
with AI. And so if whateverindustry you're in or business
(42:03):
model you have, I think sittingdown and looking at how can AI
help. And and candidly, youdon't have to be an expert in
all the different ways that AIworks or use cases today. I
would just start with whatproblems would it be really nice
to solve within my currentbusiness model or my current
industry.
(42:23):
And then and then there'sprobably a way for AI to do it.
You can go search for that, youknow, secondarily, but I would
start with with solving bigproblems. So that those are kind
of my kind of my high leveltakes on on on AI and kind of
where the world's going.
Kevin Horek (42:37):
No. I I agree with you. I I don't think it's all
doom and gloom. If anything, Ithink it's gonna and you're
already well, Captured built awhole business around it. It's
basically getting rid of thekind of boring, mundane, kind of
time sucking tasks.
Right? And I think if you canleverage AI to do some of that
stuff for, you know, yourselfand your team, and they can work
(43:00):
on some of the funner parts oftheir job, it frees them up to
to do and grow and and probablymaybe even stick around longer
because, you know, they're notgoing through some manual stuff
that a computer can do nowadayswith, you know, machine learning
or or whatever. Right? Is isthat fair to say?
Will Robinson (43:18):
Yeah. I mean, people wanna have look.
Everybody I mean, this is gonnaget philosophical. I think
everybody's searching formeaning and purpose in their
life. Sure.
And, you know, whether or notyou think your job is part of
that, you spend everybody spendsso much time doing their job
that Yeah. That if if it's asoul sucking experience, no
matter how much, you know,meaning or purpose you get
(43:38):
outside of your job, I don't Idon't think you're gonna be, you
know, I just I think you'reyou're leaving yourself short on
that front. And I think as a asa leader in a business, I think
it's our, candidly our ourcalling and mission to provide
high quality employeeexperiences at the organizations
that we run and that we lead.And so if you wanna if you wanna
(43:59):
keep great people, you know,making it to where they feel
heard and valued, is iscritical. And part of that is
providing them the tools andresources they need to do their
job.
And if you can eliminate the,you know, the boring, mundane
tasks out of their day,generally, they're gonna they're
gonna enjoy it more and feelmore connected to your ultimate
vision. You know, I would saythis too, like, one thing that
(44:21):
we've embraced at Encapture, youknow, some people can get really
excited about helping banks bemore efficient, but a lot of
people and if you even ask, youknow, our employees, there's a
lot of them, like, yeah, okay,whatever. Like, that's cool. We
help banks be more moreefficient. But, like, that
doesn't get me out of bed everymorning.
What we've done though is we'vebeen able to take our technology
and work with a nonprofit,called BED, which helps kind of
(44:48):
third world countries, a lot ofcountries in Africa and Latin
America kind of manage their,kind of their their orphan and
institutionalized childrenpopulation. So there's a lot of
kids that are orphaned or maybeabandoned or or run away from
home. And these countries intheir foster care systems are
trying to, you know, take careof these kids and and either,
you know, reunite them withtheir family or maybe find an
(45:11):
adopted home for them to be in.But, you know, that's a very,
there's there's incompletedocumentation or paperwork. A
lot of these kids don't knowdon't have their, you know,
don't have a birth certificateor don't know where they're
from.
And so this nonprofit, BEB, BEB,is helping to solve that by
using their own software to kindof create these digital
identities for these children.And we're able to partner with
(45:33):
B. E. B. And help them process,all the, all the paperwork that
they have to process to kind ofcreate that digital identity.
So for us, it's a really coolway to use our skill set and our
expertise and our technology ina way that we feel like has a
direct kind of social impact onthe world. And that's been a
really fun project andpartnership for our people to
(45:53):
get involved in and say, hey.I'm making a real difference in
a way that that brings me a lotof value.
Kevin Horek (45:59):
That's awesome. No. That's really great. That's
that's cool. But we're kindacoming to the end of the show.
So how will we close withmentioning where people can get
more information about yourself,the company, and any other
links, and maybe mention thenonprofit as well so people can
check that out?
Will Robinson (46:17):
Yeah. Absolutely. So, you can, you know, check us
out online encapture.com. Youcan check us out on LinkedIn.
I'm there as well.
The organization is called, beb,and the website is
bebglobal.org. It's a greatnonprofit. Again, especially if
you're in the software techspace, they're using software to
(46:39):
help, take care of thesechildren, and to unite them with
family. And, you know, there'snot many nonprofits who have
leaned into using technologyyet, and so it's a really cool
organization. So I I highlyencourage you to to check it
out.
Kevin Horek (46:51):
Very cool, Will. Well, I really appreciate you
taking the time out of your dayto be on the show, and I look
forward to keeping in touch withyou and have a good rest of your
day, man.
Will Robinson (46:58):
Awesome. Thanks so much, Kevin. Enjoyed it.
Kevin Horek (47:00):
Thank you. Me too. K. Bye.
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Kevin Horek (00:34):
Welcome back to the show. Today, we have Will
Robinson. He's the CEO atEncapture. Will, welcome to the
show.
Will Robinson (00:40):
Thanks for having me on, Kevin. Glad to be here.
Kevin Horek (00:42):
Yeah. I'm excited to have you on the show. I think
what you're doing in the AI kindof machine learning bank and
lending space is actually reallyinnovative and cool, but maybe
before we get into all that,let's get to know you a little
bit better and start off withwhere you grew up.
Will Robinson (01:01):
Yeah. Sure. I'm a I'm a Texan. I grew up in Dallas
and went to school down atBaylor, which is Central Texas,
big family school for for me.And, you know, it's funny.
I I kind of I was a I was afinance and econ major, like, in
the business school and kind of,you know, thought I wanted to
(01:22):
kinda go down this financecareer. And I moved to New York
City and, worked in finance for4 or 5 years. And I worked a lot
with tech companies and reallyjust fell in love with with
technology and software and feltlike it was going to change the
world, and thought, hey, I wouldlove to I would love to be an
operator in this space for mycareer. So, that's how I got
(01:43):
into what I'm doing now. I Iworked for a big tech company
before here in Dallas, beforejoining Encapture and kind of
being on the ride that we'vebeen on for the past 5 years.
Kevin Horek (01:53):
Very cool. So what got you passionate about finance
at an early age and made youwanna go into it at least to
begin?
Will Robinson (02:02):
Yeah. That's a good question. I I've always
been kind of a math and numbersguy, and Okay. I thought it was
interesting to kind of learnhow, companies raise money to go
do things Sure. Showing thefinancing side of that.
And so, and candidly, I had areally funny experience. I did a
summer abroad, one summer and Iwas talking to some, some other
(02:25):
American students. We were atlunch one day and I remember
saying, hey, you know, nextsummer is the, is kind of the
last summer of college, and whatare you guys gonna do in the
summer? And they all said, well,we're gonna move to New York
City and do investment banking.And I I had no idea what that
meant.
And so I remember going back tomy dorm room and, like, googling
what is investment banking andand why you know, if if all 3 or
(02:46):
4 of these guys wanna do that,why is it? And and kind of
thought that, hey, this could bea really interesting start to my
career and a place where I canlearn a ton. And and it was. It
was a great it was a greatstart, and I felt like it's
really propelled me to to dowhat I do now, albeit with a
different background.
Kevin Horek (03:01):
Got it. Makes sense. So walk us through what
exactly is Encapture, and, let'sdive into that.
Will Robinson (03:10):
Yeah. So encapture is a machine learning
platform. And and by the way,I'm gonna try to stay away from
a lot of buzzwords, and if I usethem, we'll talk about what they
mean. Sure. But we, have theability to help process
documents as part of kind ofthese really paperwork intensive
workflows at banks and lenders.
And so specifically, our machinelearning can read a document and
(03:34):
it can understand the system canunderstand what type of document
it's looking at, and then it canpull out the important
information off of that documentand use it for a variety of
different things. It can put itin another system. It can check
the data across multipledocuments
to make sure that the data is consistent. It can
check
the data against a third party system to see if
(03:54):
there's any discrepancies. Andreally what we are eliminating
is a lot of manual data entryand a lot of kind of stare and
compare processes at these bigbanks and lenders. So a simple
example I use is something thata lot of people, if you've ever
bought a home, you can relate tothis when you're applying for a
mortgage. You You know, youyou're talking to your loan
(04:16):
officer at the lender andthey're saying, okay. You know,
Will, you're gonna buy thishome.
We need to see how much how bigof a mortgage you can afford. So
I'm going to need to collectsome documentation from you, a
recent pay stub, maybe a coupleof years of your tax returns.
I'm going to need to make sureyou're real. So, you know, send
in a copy of your driver'slicense or passport. And so the
lender is collecting all thesedocuments to kind of make a
(04:37):
credit decision.
But a lot of times in thebackground, there's people there
manually reviewing thesedocuments or putting this data,
you know, trying to figure outhow much money does Will make a
year, what's his income, howmuch does he have in the bank,
etcetera. There's a lot of roomfor automation around that. And
so that's where we play kind ofin the back office, helping
process these incoming loandocuments, pulling out the
(04:58):
important data, and making surethat the bank can do something
actionable with it.
Kevin Horek (05:03):
Interesting. So how did Encapture or Encapture come
to be, and and what made youguys actually decide to build
this thing?
Will Robinson (05:13):
Yeah. It's a it's a good question. The company
itself is 25 years old. So
Kevin Horek (05:19):
Okay.
Will Robinson (05:19):
We I joined this company about 5 years ago. It
wasn't even called Encapture atthe time. Okay. But I joined as
part of kind of a private equityinvestment that the company
received. And, we hadhistorically been a kind of a
professional servicesconsultancy on behalf of some
really big software players.
(05:40):
And we would come alongsidethese software vendors and we
would help them sell theirsoftware. It was all around
workflow automation and kind ofthis back office document
workflow review. And we wouldcome alongside them. We would
help them sell it. We wouldimplement the software.
We would, you know, we justcharge kind of an hourly rate to
do that. But the company, gosh,maybe 10, 12, 15 years ago
(06:03):
started building their ownproduct called encapture to help
collect the documents upfront,just make sure that the that
the, you know, the end customerkind of had everything that they
needed, as part of the workflow.And so the company would kind of
resell, you know, their vendorsoftware, but then sell a little
bit of encapture as well. And,when I joined about 5 years ago,
(06:23):
the strategy was, well, it'sgonna be a lot more interesting
for us as we think about growingto invest in our invest in our
own product more, invest inEncapture. At the time, machine
learning was kind of just cominginto its own in terms of its
capabilities around meetingdocuments and extracting data.
And I felt like we would bebetter off as a company to
(06:46):
really pivot away from theprofessional services and these
legacy partnerships and insteadbecome more of a pure play
software company. And and so,obviously, that's that's easy
that's easier said than done.Never said. Yes. I don't, I
don't necessarily recommend thatas a default strategy for for
most businesses.
A lot of businesses try to dothat, say, oh, we've been a
(07:07):
we've been a services company. II want to be a software company
now. It it's taken a lot of workand effort and blood, sweat, and
tears to do that, but but we'rethankful that we've been able to
do it.
Kevin Horek (07:19):
No. Very cool. I I wanna cover that a little bit
before we dive a little bitdeeper into what you're doing
today. Did obviously, you usedkind of the consulting side
though to build a product, like,to fund it, I mean, or or did
you raise money or or walk usthrough that.
Will Robinson (07:35):
Yeah. Good question. So the consulting
side, that was kind of our cashcow at the time. So that's where
we were making all of ourprofit. That was, you know, the
historical business model.
And so, you know, we didn't justturn that off overnight. And
that's what was so challengingabout kind of rebuilding the
company and and and pivoting thecompany while you're still
trying to, you know, do thething you've been doing for a
long time. And so we use the,you know, the profits from our
(07:58):
consulting to really reinvestinto, into our our software
platform. And that was a veryincremental process. It took I
mean, candidly, it took us, youknow, 3 to 4 years to
completely, kind of let go ofall of our legacy consulting
business, and become kind ofthis pure play software
business.
And so I'm thankful my investorswere were comfortable with that
(08:21):
strategy and approach. Youdefinitely have to take kind of
a long term vision to be able todo that.
Sure.
In in terms of raising money to do it, we
decided that we just wanted tofund this, organically. Okay. We
you know, there were pros andcons to both, but we felt like
we felt like in the long run, itwould be better for,
(08:44):
mechanically better for theshareholders and and better for
us as as leaders of the businesswho also were shareholders. We
felt like we could create morevalue over the long run by doing
this ourselves versus going outand kind of following a
traditional venture capitalmodel where you you go raise a
lot of money and try to goreally, really fast. So that was
our approach and, you know, itwas a really hard decision to
(09:06):
make, especially a couple yearsago when we were starting to
have success and the softwareworld was was going just
absolutely insane from afundraising perspective.
We intentionally kinda sat thatout and said, hey. You know
what? We're comfortable with thegrowth we have and the progress
we're making and the way thatwe're funding that. Hindsight
2020, that was a very wisedecision for us. I feel like
(09:27):
we're in a much stronger,healthier spot as a company,
and, you know, we're not havingto make some of the hard
decisions that that many othersare at this point.
So that's the path we've beenon, a bit nontraditional, but,
we felt like the consulting, youknow, allowed us to fund our own
things. And then also, it itkept us really close to the
customer and their pain points.And so as we as we developed our
(09:48):
product and really built out andcapture, built out the the AI
side of it, we felt like wealways had a really good sense
of the problem we were trying tosolve. And I think that allowed
us to to, not make quite as manymistakes. Still made plenty.
Kevin Horek (10:02):
No. I I think that's really good advice. And
and the company that I ended upbeing a part of that got
acquired, we did the same thing.We were kind of a software
company, and then we werebuilding a product, and then we
eventually kinda switched tothat. But yeah.
And to your point, it's it'shard, but doing a startup is
hard no matter how it's funded.Right?
Will Robinson (10:22):
Yeah. No. It is. I mean, it's yeah. It's kind of
the grass is always greener.
Yeah.
You know,
there are days that I wish, man, if I had just
done this as a start up, Iwouldn't have all this legacy,
culture and legacy kind ofmindset and legacy business
model support. But at the sametime, I I had enough of a
starting base in terms ofcustomer base and relationships
(10:42):
with customers that provided mea really solid footing to kind
of grow off of that and and andgrow the software. So, you know,
wherever you are, whether you'rein a a true start up or you're
maybe in a business that'strying to transform, I think
really leaning into, whateverstrengths you have at the moment
is really important. And and andhonestly, I wish I had moved
(11:03):
faster. I wish I had been alittle bit more bold in terms of
that that transition away fromthe legacy.
I think I hold on a little bittoo long to a few clients, a few
projects, a few people,internally, that I thought, oh,
these people are gonna be ableto make transition with me.
They're gonna be able to be partof kind of the new vision, the
new culture. And, you know,unfortunately, many of them were
(11:25):
not. They they were just verymuch accustomed to the way
things have been done, and itwas better to kind of start
fresh with a lot of roles. Sohad a lot of turnover on that
front, which was not, notnecessarily plan A for us and
definitely hard to go through.
But ultimately, we're a muchstronger organization now
because we have, you know, theright people in the right seats.
Kevin Horek (11:46):
Interesting. Okay. I wanna dive a little bit deeper
into that. So I'm curious, didyou use or did you get to
leverage some of your currentconsulting customers into kind
of the SaaS company that, youknow, in Capture is today? Or or
how did you leverage that andstart getting some early
(12:07):
customers?
Will Robinson (12:08):
Yeah. That was a that was a big part of our
strategy. We had a we had a wekinda had an initial set of
customers. And remember, theseare customers that had purchased
Encapture a decade ago, and theywere still using it. Now they
were using it in a way that wedidn't see as, you know,
necessarily the vision for theway forward, but they they had
the product, they were they wereworking with us already, they
(12:31):
were getting value out of it.
And so we were able to startwith them and then say, okay,
what else can we do for you? Orhere's our vision for where
we're trying to take theproduct. How does that, marry up
with with what you guys need inyour organization? And candidly,
you know, selling into sellinginto banks and lenders is very,
very hard. It's a verytraditional group of buyers.
(12:51):
They have a, they need a lot ofsocial proof, and so having
logos, established logos Ah,yes. Was a huge help for us, and
being able to kind of point tocase studies and say, well,
look, this is what we're alreadydoing for a peer of yours. That
really allowed us, I think, toaccelerate our growth versus
starting from scratch. And so wedefinitely leveraged them. Now,
(13:12):
I will say we got to a pointprobably 18, 24 months ago where
we did have some legacycustomers that were not really
buying into the vision of wherewe were going as a company and
where our product was going.
And we have this choice of,well, do we continue to support
kind of their legacy use casewith the legacy product? And and
(13:33):
for many of them, we we chosenot to. They chose not to as,
you know, Mutual. And we kind ofsaid, look, if we keep
supporting this legacy customerbase, that's just going to
distract us from what we'rereally trying to do. And so we,
you know, we parted ways.
And again, it's hard to hard todo that, to have churn and say,
hey, well, you know, customersare leaving, but ultimately,
those customers were a reallybig distraction for all of our
(13:56):
teams. And there wasn't therewasn't growth in those accounts
that we needed to see or wewanted to see. So ultimately,
even though it was a bit of areset, from a revenue
perspective, it was I I I feellike our portfolio customers now
is a lot healthier, and it's alot more aligned with our vision
as a company.
Kevin Horek (14:12):
No. Makes a lot of sense. So let's dive a little
bit deeper into what exactlyEncapture is. So what was it and
what is it today?
Will Robinson (14:23):
Yeah. That's a good question. So it started as
a it started in the old dayswhere if you wanted to get a
mortgage or a loan, you know,and I I've mentioned the example
of a loan officer asking fordocuments. Typically, the way
you would do that is you wouldwalk to you would go into a
local bank branch, and you wouldhave, like, a stack of your tax
(14:44):
returns, or you'd have yourdriver's license, and that
branch employee would makecopies of of, you know, your
documents, or they'd even keepkeep the kind of the documents
you brought. And they would,have, like, a FedEx truck come
by, pick them up every singlenight, and they would courier
those documents to some sort ofcentral processing facility,
usually in the middle ofAmerica, and people would, you
(15:07):
know, open up your file, open upyour, you know, your document
set and they would start lookingthrough it.
And if there were any issues,maybe you didn't provide the
right documents or you didn't,something looked off, they would
then call the bank branch andsay, hey. You need to call this
borrower back, have them comeback up, and submit additional
documents. So as you canimagine, it's a very, very,
(15:28):
laborious, time intensive, longprocess. I mean, it could take
several weeks for thosedocuments to make their way. And
so, the product started reallyas an integration into the big
scanners, the big multifunctiondevices that we all kind of have
in our office buildings or thatyou have in a branch.
You know, it's the big scannerthat copier machine that's, you
(15:48):
know, several feet high. And,what we would do is we would sit
on we would integrate with thatmachine and so when you scanned
or copied a document, you wouldhit a little button on the LCD,
you know, display that said sendto encapture. And so we would
digitally ingest that documentand we would put it in the right
workflow so that you didn't haveto courier a document to a
(16:10):
physical location. So it's kindof this digitization of of
documents in a very, very basicway that was our original use
case. There was no, you know,there was there was nothing
smarter than that other thanjust sucking documents off of a
scanner and and sending theminto the right workflow, you
know, someplace across thecountry.
You know, where we are now iswe've kind of built on that
(16:32):
foundation of capturingdocuments. We can capture from a
lot of different sources, notjust a scanner, but we can
capture from your email, from afax machine, from a, you know, a
customer portal online. It's allAPI driven, so we can really
kind of ingest, suck indocuments anywhere. But the
secret sauce now is the AI. Andso that was something we didn't
have that we built out, And theAI can do 2 things.
(16:55):
1, it can identify the document,that the system just received.
Am I looking at a driver'slicense? Am I looking at a pay
stub? Am I looking at a taxreturn? There's hundreds of
documents we can we can look at.
And then based on that, can Ipull out the important
information? You know, driver'slicense, it would be somebody's
name or date of birth oraddress. If it's a pay stub,
(17:16):
it's, you know, how much didthey get paid and what's the
time period on that. So I cankind of create a calculation of
your annual income. If it's abank statement, what's the date
of the bank statement?
How much do they have in theirbank account? What are the
debits and credits in in thataccount that, you know, a bank
will use or a lender will use tokind of determine your income?
So it's pulling all these keypieces of data, and that's
(17:39):
really what we've evolved to.And that's where there's a ton
of efficiency gains that theselenders have because they don't
have to do that, sit there anddo it manually.
Kevin Horek (17:48):
Very cool. It it's it's fascinating to me. Maybe
banks well, I don't know thisfor sure and you can correct me
or you could tell me your answeris banks aren't traditionally
known for being kind of cuttingedge on technology, but the the
I've had some people kind of inthe Fintech space recently on
the show, including yourself,where banks are actually
(18:11):
leveraging a lot more kind ofmachine learning and AI, whether
it's, like, from a third partyvendor like yourself or they're
building it internally than Iever had, like, ever thought of,
which is awesome. I'm I'm gladthat's the case. So I'm curious
to maybe dive a little bitdeeper into some other real life
use cases because right now, AIis the hype.
(18:36):
You know, Apple calls it machinelearning because AI is scary to
a lot of people. It's arguablythe same thing or, like so where
where are we at and kind of whatis the state of kind of Fintech
and banking leveraging some ofthis technology, and then how
are you helping with that? Yeah.
Will Robinson (18:53):
That's a great question. There's there's a lot
to unpack there. I would say at,like, a 50,000 foot level, we
are kind of peak hype peak hypecycle around NI broadly broadly
speaking. I mean, there's justso much talk about it, and it's
really been generated by thissorry for the pun, but it's been
generated by generative AI, GenAI, the chat gpt type technology
(19:18):
that has really come to theforefront of the market in the
last year. And I think that'sbeen this is one of the first
types of technologies that Ithink from a mass consumer
perspective, people go, wow.
This is really impressivetechnology. That that Gen AI is
not, is very, very, very earlystage at at banks and lenders.
(19:41):
Really, I think across manyindustries. I think people are
still trying to figure out howgood is it and where can we use
it. You know, banks so and I saythat to say there's a lot of
different types of of, andtechniques of AI and machine
learning that, you know, thatexist and that have existed for
several years.
For example, our our, you know,our AI and machine learning is
(20:01):
really under this kind ofnatural language processing and
computer vision type technology.So it's a bit of a different
approach from, the Gen AI chatGPT approach, but and it has
very different use cases. Andso, I think I think a couple of
things. Banks are very muchwanting to lean in to AI. They
feel like there's a need forefficiency and automation.
(20:25):
Just like every other otherindustry, banks struggle to hire
and retain good people. And soSure. It's expensive just to
throw bodies at a problem, andthere's a lot of process in
banks. There's a lot ofregulation that drives process.
You have to do it right, butthey're very open to using
technology to solve that.
But they want proven technology.They want they don't wanna be
bleeding edge. And and they alsodon't you know, they're very
(20:48):
wary of having technologyinteract with the end customer.
Banks
Kevin Horek (20:53):
Makes sense. Yeah.
Will Robinson (20:53):
Banks pride themselves on on that
relationship. Right? A lot ofbanks talk about this. If you
talk to a banker, it's like,hey, we we pride ourselves on
the relationships and providinggreat customer service. They're
not sure AI can do that.
And so, you know, banks arelooking to invest in places like
where we play, which is more ofthe back office, where customers
don't see it, borrowers don'tsee it, but it helps them be a
lot more efficient, in terms ofprocessing loans or generating
(21:16):
reports or doing, you know,certain compliance functions.
Nope. Makes a
Kevin Horek (21:22):
lot of sense. So and you can correct me if I'm
wrong here, is you guys havebeen using kind of AI and
machine learning for years wellbefore the chat GPTs of the
world kind of popped up andbecame, you know, trendy, I
guess, for lack of a better termfor
Will Robinson (21:36):
Yeah. We have, you know, and that's, you know,
we've tried to call it differentthings over the years, to kind
of almost shy away from the termAI because Yeah. You know, it it
kind of made people's head spinwhen you say AI or machine
learning. They don't really knowwhat that means or how it works.
Sometimes they just think it'slike this magical thing, that
just magic you know, it justjust solves all the world's
(21:57):
problems.
And so there's a lot of AI.Yeah. There's a lot of AI, like,
proven AI technology that existstoday that is not Gen AI that
you can utilize in kind of yourexisting businesses or if you're
a if you're a softwareentrepreneur or developer that
(22:17):
you can incorporate into yourproduct that I think is a lot
more proven. It may not look ascool and sexy as some sort of
chatbot that can just talk toyou. But at the same time, it
can provide real value for, foryour, you know, either your
business or your customer base.
And so I, you know, I that'skind of where I encourage
(22:37):
different people to start is,like, yeah, Gen AI is cool and
it will continue to get betterand better. But there's other,
you know, technologies out therethat that can provide real
proven value today where there'sa body of case studies, that
that you know you're gonna getgood value out of.
No. That makes a lot
Kevin Horek (22:54):
of sense. Well, and you're you're using it in a way
that's how do you how do you sayit? Like, that is is useful to
companies. Right? Like, I I'mnot saying a chatbot or
something simple like that isn'tuseful, because they are.
But you're solving, like, a realbusiness problem with kinda
(23:15):
machine learning and allowing,like you said, the back office
to be more efficient. Right? Andthat's what companies are really
paying
Will Robinson (23:23):
you for. Yeah. I mean, if you think about any
sort of b to b, you know,software company, thankfully,
you typically, you know, you youtypically have a buyer that's
trying to make a rationalbusiness decision. If I'm gonna
spend this amount of money withyou a year on your software,
what sort of business return amI going to get? And being able
to articulate that clearly,whether whether you're helping
(23:45):
them, you know, grow theirrevenue or cut costs or,
maintain, you know, compliancewith certain regulations, those
are like the big three that thata bank would think about.
You know, you have to be able todemonstrate that, as part of
your sales process. And sothere's, you know, there's many
(24:05):
different ways to get there, butultimately, you you have to
build confidence through thesales process that whatever
you're selling them is gonnawork. And and so, whether, you
know, whether they see thatthrough a demo or through social
proof with with, other peers oftheirs that have done it already
and can provide a referral callor you can, you know, have a
case study. Like, there's a lotof, there's a lot of avenues to
(24:27):
getting there. But, ultimately,it's got the jet the spin
justification, has to stand onits end 2 feet.
No. That that makes a lot
Kevin Horek (24:35):
of sense. So I'm curious, how do you integrate
with other technologies thatcurrent your current customers
are using? Because I thinkthat's also really powerful
about what you guys
Will Robinson (24:47):
do. Yeah. I mean, it's critical if you think
about, you know, us kind of inthe background looking at all
these documents as they comeinto a bank and pulling out the
data, that that data all has togo somewhere. And so we have a
bunch of integrations with, abunch of the the key systems
that that banks and lenders use.I will say this, in terms of
(25:09):
just general strategy forwhatever industry that that you
may be in, having theintegration solves several
several problems for anycompany.
1, obviously, there's thetechnical side of getting data
from your system to the othersystem that the company needs.
But it also creates some brandidentity and brand, I don't
(25:32):
know, positioning alongsidethose partners where a buyer is
gonna say, well, okay. Well, ifyour software at Encapture
integrates with this system,this system is kind of the the
leading player in my space. Andso if they're willing to work
with you and you guys arewilling to have a if they're
willing to have a partnership,you must be a legitimate
software company. And and allowsyou know, that's been one thing
(25:52):
that's allowed us, I think, togrow our brand is by positioning
through these technicalpartnerships we have, position
our brand alongside some reallybig players in the banking
space, and it it builds up a lotof credibility for us.
So that's an important part ofof of any, you know, soft and
again, I'll speak for for asoftware company, kind of making
sure that you fit in theecosystem and that people your
(26:16):
your buyers or prospects see youas, like, a credible player in
their ecosystem is gonna bereally important to to to
customer adoption.
Kevin Horek (26:23):
No. I I 100% agree with you. I think just the fact
that you leveraged yourconsulting clients to become
customers of your SaaS business,and then you also leverage the
fact that you've worked withthese big brands to help sell
your your your new, you know,your new platform. And then on
top of that, you leverageintegrations. I I think nobody
(26:47):
talks about that as much as Iwish a lot of people did because
it's not really any differentand but some people think that
you have to start from scratchand say, like, well, we've never
done anything for that.
But it's like, no. No. Thesethese people have been customers
for years now, and, you know,we're just moving them you're
(27:08):
just effectively moving them toa different system or product.
They're still customers. Right?
Like and then your to your pointis allowing those integrations
does validate your product.
Will Robinson (27:20):
Yeah. It's it's it's a critical part of the
journey and, you know, thisworld the world is becoming more
and more connected and there'sYeah. You know, there's there's
more and more systems at theseorganizations, so you have to be
able to play nicely with others.
Kevin Horek (27:32):
No. It makes sense. So how did you manage the road
map of when you were building itearly on and and to what now
that it's, like, a living,breathing product that has
customers. Because let's behonest. You have some very well
known banks on there that, youknow, could easily say, we'll
(27:53):
give you a couple $1,000,000 orwhatever the number is to build
x, y, and z.
And you might say, yeah. Okay. Ithink that makes sense. We can
roll that out to all ourcustomers and they would
benefit. Or you could say, like,that's not really in our product
road map or maybe parts of itare.
So how do you kinda manage that?Because that can be really
tricky as a start up.
Will Robinson (28:15):
Yeah. There's there's no easy answer to that.
I think a lot of it depends on,how much clarity you have in
your vision and, you know,funding is obviously a huge a
huge piece. If a big company isgonna give you several
$1,000,000 to take the theproduct in a certain direction,
that's a hard that's somethingthat's gonna keep you up at
night, you know. Is this where Iwanna go with my product, and is
(28:37):
this gonna work elsewhere?
One of the things that we reallyfocus on here and and have and
and try to do a good job of isjust always taking, kind of the,
the customer feedback and relateit back to the business problem
and saying, okay. What's thebusiness problem that you're
trying to solve? And getting areally clear view of that, And
(29:00):
then we will try to reallyinfluence the how we solve it
for you. And what that allows usto do is validate the problem
with other customers. Right?
If a really big customer isthrowing us a lot of money to to
go solve something, is this aproblem that other, you know,
for us, other banks are gonnahave? Is it just other big banks
or small banks gonna have thesame issue? And if we feel like
(29:23):
it's something that we can gosell again and again and again
and kind of solve similarproblems, then we're gonna, you
know, we're gonna probably havea pretty strong point of view of
how we go build that and and notnecessarily want the big
customer to tell us how thatworks. So there's some give and
take there. I think as long aswhen it comes to customers, it's
keeping a clear, clear side onwhat is the problem you're
(29:45):
solving for them.
And and also this kind of bucksprobably, maybe some more
traditional design thinking, oror product thinking. I wouldn't
always rely on your customer toto have the best view of how to
solve that. I I think that partof what makes companies great
(30:05):
and, you know, you can use anextreme example like a like a,
like a Steve Jobs at Apple.Like, he kind of, you know,
would say, hey. Like, peopledon't know what they want.
Right? Like, if people ask mewhat they want, they would never
ask for an iPhone or an iPad or,you know. And so I think there's
a little bit of of, you have togo create the vision and create
the dream, and you're probablynot going to get that from your
(30:28):
customer. And so I wouldn'tthere there's a balance. Right?
There's a balance of ofunderstanding their problem, but
also being confident in yourselfto go build what you think is
gonna elegantly solve that evenif it may be different from what
they say they want.
No. Makes makes a lot
Kevin Horek (30:41):
of sense. So I'm curious to get your thoughts on
because you've been in the theFintech space a long time, what
advice do you like to pass on tokind of founders or maybe people
that are struggling in theFintech space or that have, you
know, that you wish you wouldhave known, you know, maybe
earlier on in your career?
Will Robinson (31:04):
Oh, that's a good question, Kevin. I man, where do
you even start? There's there'sthere's so much so many battle
scars, I would say, from doingit. I think I think if you're a
founder regardless of ofindustry, whether it's Fintech
or or elsewhere or you're you'rerunning a business, This sounds
(31:25):
so cliche, but it's so true. Thepeople you have on your team,
are everything.
I mean, that's everything. And,you know, I used to have people
give me that advice, and I kindajust roll my eyes and be like,
okay, that sounds really fluffyand, you know, whatever. I you
know, I'm a smart guy. I can gofigure this out. But, you just
(31:46):
get to a certain size and scale.
There's no way you're gonna besuccessful unless you have the
right folks with the rightmentality and right skill set on
your team. And, and that's beena big thing that we've we've, I
think, learned from as we'vegone on our journey here in
encapture. And that's probablybeen the the one common theme I
can point to when I look at oursuccesses here, as well as our
(32:09):
failures, is is the people thatwere involved in that. And not
to say that that that greatpeople don't make mistakes. We
have all made many mistakes inour journey, but but really
great people learn from that andcan kind of push through and
figure out how not to make thatagain or how to, you know, build
a more resilient company.
(32:29):
And I think people who struggleare ones who who can't see, how
to get themselves out of that,and they kind of feel like
they're just overwhelmed by the,you know, by the the mistake or
the pressure. And so that'sthat's a big thing is as you get
going, whether you have, youknow, 3 employees or 30 or 300,
really being intentional aboutthe type of people you have, the
(32:52):
culture you're trying to build.And when I say culture, I mean
kind of set of core values andattributes of your team to
create a high performing team.Being very, very intentional
about that is gonna serve youwell even if it even if you run
off some people in the shortterm that you may think are
really critical. You know, I'veI've had people here who, when I
(33:12):
started 5 years ago and theywere existing employees at at at
the company, I would have said,man, if if this guy or this this
girl leaves the company, we arescrewed.
Like, there's no way we're gonnamake it. And you know what?
Like, those folks have left andwe're doing better. We're doing
better because it wasn't itwasn't their technical skill set
that was holding us back orkeeping us afloat. It was, it
(33:34):
was their mindset and abilitykind of be part of the team and
the vision we were trying to do.
Kevin Horek (33:41):
Interesting. Now I I agree with you. I like, yeah,
I I think especially nowadayswith, like, people being remote
more and more, not everybody'sremote or it's hybrid or
whatever, But just having thatkind of team, it's very, very
challenging to build a reallygood team. But if you can get
(34:02):
it, you're so lucky, really.
Will Robinson (34:07):
Well and, like, I would I would challenge it and
say the mark of being a goodleader of a business Okay. Is
your ability to attract andretain the right kind of people
and build that build thatenvironment where they can be
successful and you guys can besuccessful as a company. And
that looks very different, youknow, based on the type of
(34:29):
business you're trying to build,you know, specific values of
that organization. And so, youknow, if you're if you're
sitting there as maybe atechnical leader or a technical
founder who's who's got a reallygreat idea for a product and
maybe can build a great product,that is certainly important, but
you're not gonna go very far, ifyou if you can't surround
(34:51):
yourself with people that canhelp push the overall vision
forward. And so I I I see it aslike a must a must have where,
you know, you're you're justyou're not gonna be successful
unless you have a good team.
You're just not gonna you're notgonna break through.
Kevin Horek (35:05):
No. I 100% agree with you. That that makes sense.
I'm curious then, but how do youtry to retain that talent? Like,
how do you basically get out oftheir way and let them do what
you hire them to do withinobviously parameters, but, like,
to make sure they're successfuland they're happy and they stay
long term?
Will Robinson (35:26):
Man, that's a that's a that's a $1,000,000
question. I think there'sseveral I think there's several
parts at it. 1, creating clearexpectations upfront of, the
type of person that you want atyour company as part of your
recruiting process. Okay. Andsetting clear expectations for
that individual of what the therole and responsibility looks
like.
(35:47):
That's where I I think mostorganizations go sideways, get
sideways with their with theirstaff is it's never really been
super clear on what what goodlooks like in the role. And so
sitting down and really definingthat is pretty important. It's
also incumbent upon the leaderto set clear vision for the
business. This is where I dothink, like, you know, the CEO
(36:08):
kinda earns earns his paycheckor her paycheck is is not only
recruiting a good team, butsetting a very clear vision of
this is where we're trying to goas an organization. This is what
we're trying to this is theproblem we're trying to solve.
This is the mission that we'reon, and making sure that that
people understand that. And andif you have the right type of
person, they'll be able to buyinto it and kind of come
(36:28):
alongside you in that journey.So, you know, setting people up
for success is is the best wayto ensure success. And if you
have clear parameters aroundthat, you'll learn pretty
quickly if if someone's gonna bea good fit at the organization
or not. Doesn't mean they'regonna be, you know, completely
value added if they want, but ifthey've got the right mindset
and attitude, and and they'rebuying into what you're doing,
(36:52):
you're gonna see them be a lotmore productive and valuable to
the organization than someonewho's just got a set of
technical skills, that maybelooks at the job in a more
transactional way.
So, you know, those are the bigthings. Obviously, I mean, you
know, things like compensationand and and parts and benefits,
like, I think those are thingsthat you kinda just have to get
(37:12):
right. I think it's kinda like II heard it described once is
it's kind of like, you know,comp and benefits is kinda like
brushing your teeth. There's a,you know, not brushing your
teeth enough is a problem, andand then brushing your teeth too
much is also a problem. There'sjust kind of the right amount.
There's kind of the right amountand right setup. That's the
sweet spot. And so, you know, Idon't think you have to have
(37:33):
every every perk imaginable ortry to, you know, outdo kind of
the, you know, the Google way,if you will. But if you look at
your company, your team, youknow, your financial
constraints, you you can look atand say, okay. What's important
to my people?
What's important to us? Andlet's just get it right so that
people don't people who don't,you know, you don't have a
situation where people love yourbusiness, love their job, but
then have to feel like they needto leave because something's not
(37:55):
right on the comp or benefitsside.
No. That that makes a lot
Kevin Horek (37:59):
of sense. I also find that not well, not
everybody's motivated by moneyall the time too. Right? Like,
more it seems more and morepeople actually care about, you
know, adding value and feelingvalued and learning at a job.
And if they're making, you know,a little bit less than they
would somewhere else, if yougive them that, like, some
people value that a lot morethan, you know, just making the
(38:20):
most amount of money, andthey're fine hating their job.
Right?
Will Robinson (38:26):
Yeah. I I try to stay away from from that
mentality because those folksand you can identify them in
your recruiting process, theones who are kind of trying to
maximize the money side becausethey'll they'll they'll have job
hopped a lot. They'll kinda havehopped around, and they won't
really have stayed anywhere longenough to, like, I think, truly
grow themselves. And and this issomething I tell a lot of our
(38:49):
our junior people is, like,look, if if you wanna make good
money in your in your job,that's fantastic, and and we're
here to support that. The bestthing you can do is is really
invest in a business where youcan grow and develop your, you
know, your leadershipcapabilities, your skill set,
because that's ultimately gonnaset you up to find jobs that
(39:10):
that that that do provide thatlevel of income that you want.
And, you know, if you're alwayshopping to another job that pays
20 k here more, you know, 30 kmore here, like, you're gonna
look up in 5 years and have had3 or 4 different jobs, and you
really won't have grown andyou'll just kind of plateau out
much at a much lower, you know,call it comp level than someone
who's really invested and grown.So, I I think that's something
(39:32):
to to really look out for. And Iwould say too, like, even in the
more, call it, compensationfocused roles, like like revenue
related roles or sales roles,obviously, you know, that's a
big part of of of, I'm making agross generalization here, but
that's a big part of many, manysales reps is kind of what sort
of money can I make here? But Ithink you need to see if that
(39:54):
type of person is sotransactional that the minute
they get a better offersomewhere else or maybe times
are tough at your business,maybe they have a slow quarter
or whatnot, they're looking tobail versus kind of lean in and
say, okay, hey, how do I makethis better?
How do I invest in the business?Because you're just gonna get a
lot more out of this out ofthose folks.
Kevin Horek (40:10):
No. I I think that's actually really good
advice. So I I'm curious becauseyou've been in kind of the
machine learning AI space for anumber of years now, where do
you where are we at? What do yousee happening? Any predictions
for the future?
Or or or maybe even, just anyother ideas on how people could
(40:30):
leverage this technology whetherthey're in the Fintech space or
not?
Will Robinson (40:37):
Man, I'll give you just some hot zingers here.
Sure. Then we
can unpack if we want to, but I think AI is very
much gonna be highly disruptiveover the next 5 to 20 years
Okay.
Yep. Of our economy. I think I think in the
next year, I think people willstill be kinda dabbling with it
(40:58):
and try figure it out. But Ithink 5 years from now, you'll
really start to see AI havepenetrated certain industries
and use cases that fundamentallychange the way that companies
operate. And and so I'm a bigkind of believer in the the
power of AI.
I I don't have a super here's mynext Zinger, I guess. I don't
(41:20):
believe it's gonna be this, youknow, Skynet take over the world
type situation. I don't I don'tthink our AI is nearly capable
enough to do that nor is ourcompute power on the hardware
side, there yet. Now that couldchange, but, at this point, I
would I'm more in favor of let'slet's give more more people the
(41:41):
ability to access AI and use itand build it versus try to over
regulate it. I think that willdo some some long term damage.
And I think every industry isgoing to, you know, every
industry is getting disrupted byby software and technology, and
that that will continue. But Ithink it will accelerate with
with AI. And so if whateverindustry you're in or business
(42:03):
model you have, I think sittingdown and looking at how can AI
help. And and candidly, youdon't have to be an expert in
all the different ways that AIworks or use cases today. I
would just start with whatproblems would it be really nice
to solve within my currentbusiness model or my current
industry.
(42:23):
And then and then there'sprobably a way for AI to do it.
You can go search for that, youknow, secondarily, but I would
start with with solving bigproblems. So that those are kind
of my kind of my high leveltakes on on on AI and kind of
where the world's going.
Kevin Horek (42:37):
No. I I agree with you. I I don't think it's all
doom and gloom. If anything, Ithink it's gonna and you're
already well, Captured built awhole business around it. It's
basically getting rid of thekind of boring, mundane, kind of
time sucking tasks.
Right? And I think if you canleverage AI to do some of that
stuff for, you know, yourselfand your team, and they can work
(43:00):
on some of the funner parts oftheir job, it frees them up to
to do and grow and and probablymaybe even stick around longer
because, you know, they're notgoing through some manual stuff
that a computer can do nowadayswith, you know, machine learning
or or whatever. Right? Is isthat fair to say?
Will Robinson (43:18):
Yeah. I mean, people wanna have look.
Everybody I mean, this is gonnaget philosophical. I think
everybody's searching formeaning and purpose in their
life. Sure.
And, you know, whether or notyou think your job is part of
that, you spend everybody spendsso much time doing their job
that Yeah. That if if it's asoul sucking experience, no
matter how much, you know,meaning or purpose you get
(43:38):
outside of your job, I don't Idon't think you're gonna be, you
know, I just I think you'reyou're leaving yourself short on
that front. And I think as a asa leader in a business, I think
it's our, candidly our ourcalling and mission to provide
high quality employeeexperiences at the organizations
that we run and that we lead.And so if you wanna if you wanna
(43:59):
keep great people, you know,making it to where they feel
heard and valued, is iscritical. And part of that is
providing them the tools andresources they need to do their
job.
And if you can eliminate the,you know, the boring, mundane
tasks out of their day,generally, they're gonna they're
gonna enjoy it more and feelmore connected to your ultimate
vision. You know, I would saythis too, like, one thing that
(44:21):
we've embraced at Encapture, youknow, some people can get really
excited about helping banks bemore efficient, but a lot of
people and if you even ask, youknow, our employees, there's a
lot of them, like, yeah, okay,whatever. Like, that's cool. We
help banks be more moreefficient. But, like, that
doesn't get me out of bed everymorning.
What we've done though is we'vebeen able to take our technology
and work with a nonprofit,called BED, which helps kind of
(44:48):
third world countries, a lot ofcountries in Africa and Latin
America kind of manage their,kind of their their orphan and
institutionalized childrenpopulation. So there's a lot of
kids that are orphaned or maybeabandoned or or run away from
home. And these countries intheir foster care systems are
trying to, you know, take careof these kids and and either,
you know, reunite them withtheir family or maybe find an
(45:11):
adopted home for them to be in.But, you know, that's a very,
there's there's incompletedocumentation or paperwork. A
lot of these kids don't knowdon't have their, you know,
don't have a birth certificateor don't know where they're
from.
And so this nonprofit, BEB, BEB,is helping to solve that by
using their own software to kindof create these digital
identities for these children.And we're able to partner with
(45:33):
B. E. B. And help them process,all the, all the paperwork that
they have to process to kind ofcreate that digital identity.
So for us, it's a really coolway to use our skill set and our
expertise and our technology ina way that we feel like has a
direct kind of social impact onthe world. And that's been a
really fun project andpartnership for our people to
(45:53):
get involved in and say, hey.I'm making a real difference in
a way that that brings me a lotof value.
Kevin Horek (45:59):
That's awesome. No. That's really great. That's
that's cool. But we're kindacoming to the end of the show.
So how will we close withmentioning where people can get
more information about yourself,the company, and any other
links, and maybe mention thenonprofit as well so people can
check that out?
Will Robinson (46:17):
Yeah. Absolutely. So, you can, you know, check us
out online encapture.com. Youcan check us out on LinkedIn.
I'm there as well.
The organization is called, beb,and the website is
bebglobal.org. It's a greatnonprofit. Again, especially if
you're in the software techspace, they're using software to
(46:39):
help, take care of thesechildren, and to unite them with
family. And, you know, there'snot many nonprofits who have
leaned into using technologyyet, and so it's a really cool
organization. So I I highlyencourage you to to check it
out.
Kevin Horek (46:51):
Very cool, Will. Well, I really appreciate you
taking the time out of your dayto be on the show, and I look
forward to keeping in touch withyou and have a good rest of your
day, man.
Will Robinson (46:58):
Awesome. Thanks so much, Kevin. Enjoyed it.
Kevin Horek (47:00):
Thank you. Me too. K. Bye.
Intro / Outro (47:03):
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website at building the futureshow dot com to join the free
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show. The music is done byElectric Mantra. You can check
him out at electricmantra.comand keep building the future.
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