May 22, 2025 • 28 mins
Voice AI at the drive-thru is one or two years away from being ready to be rolled out to hundreds of thousands of locations, Checkmate CEO and founder Vishal Agarwal tells Bloomberg Intelligence. In this episode of the Choppin’ It Up podcast, Agarwal sits down with BI’s senior restaurant and foodservice analyst Michael Halen to discuss the rapid evolution of voice AI technology. He also comments on how kiosks have become a must have, the rapid growth of catering and what problems AI is best suited to solve.
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Speaker 1 (00:11):
Welcome to Chopping it Up. I'm your host, Mike hallon
the senior restaurant food Service Analysts at Bloomberg Intelligence, our
research and that a BIS five hundred analysts around the
globe can be found exclusively on the Bloomberg terminal. If
you enjoy the pod, I'd love it if you could
leave us a review on Apple or Spotify. Today I'm
joined by Vishal Agarwal, the founder and CEO of Checkmate.
(00:33):
Thanks for joining me, Mishelle.
Speaker 2 (00:35):
Thank you, Mike. Thanks for having me. It's fun to
be here. I get your emails pretty regularly, Like I
have a pretty good span blocker, but I get your
emails pretty consistently consistently in my inbox. So glad to
be here. Looking forward to seeing my name on there.
Thank you man.
Speaker 1 (00:51):
I'm excited for the interview. You look sharp in your
LinkedIn profile. Pick be honest. Who sported the leather jacket first?
Was it you for Jensen Huang and video ceo?
Speaker 2 (01:03):
Yeah? I hadn't heard of in video back then. You
know true story that pick is from my free wedding shoot.
So we were doing a pre wedding shoot and I'm like, wait,
I don't have a good LinkedIn profile picture. Can you
just make one into a professional one? They're like sure,
and the background I'm pretty sure it's not evident there.
(01:25):
But the background is actually a shape shot. It's at
Madison Park here in Manhattan. I love that park, and
the shake shot right in the middle there, so that's
where it shot at.
Speaker 1 (01:38):
Yeah, oh good stuff.
Speaker 2 (01:40):
Man.
Speaker 1 (01:40):
Listen for the record, I prefer your style. Jensen goes
a little over the top in my personal opinion.
Speaker 2 (01:46):
I will let him know. I think that's good feedback
for him. Thank you.
Speaker 1 (01:53):
All right, So let's start at the beginning. How did
checkmate come to be?
Speaker 2 (01:57):
How did Checkmate come to be? It's so funny. I'm
based in New York. I've always been based here and
moved here from India in about early twenty twelve. But
the funniest thing is that this idea did spark off
from San Francisco, right, so, as they say, the mothership
always has some bearing no matter where you're at. I
(02:19):
was working for an e commerce retail company here, wanted
to try out something new, wanted to, you know, build
a solution to an existing problem. And I was dining
in at at a restaurant at the SF airport and
it was just taking an enormous amount of time for
me to get my check and like I could miss
(02:41):
my flight, right, So that's where the idea came from.
Was the first idea that we had was to build
a mobile app that you could use to pay and
split your check when you're dining in in restaurants, so
you know, you don't have to wait for the server
to bring your check, you don't have to spend time
in splitting all of that. Right. That's why the name
Checkmate and our website is it's a Checkmate dot Com
(03:06):
because somebody was asking me for two hundred thousand dollars
for Checkmate dot Com in twenty fifteen, and it's a
Checkmate was twelve dollars. I said, that was one of
the easiest decisions that I've ever made in my life.
You know, I'll go with it to Checkmate dot com.
So that's that's how we started, right, And then that's background.
Speaker 1 (03:28):
That's great for the listeners. Mishal and I met at
the very first Food on Demand conference, which was in
Dallas back in twenty eighteen. Your comments about who owns
customer data really calls the ruckus.
Speaker 2 (03:42):
It did it did, like, I still remember that Drinkydinky hotel,
that that small lobby that was supposed to be a
conference based food and demand has come a massive, massive
way since then. But you know, we started with that
mobile app Checkmate, and I was going door to door
selling to various restaurants and an operator said like, hey, listen,
(04:08):
what are you selling me? Seems like a nice to have,
but come here, come just come behind the counter and
I'll show you what the real problem is. And what
he showed me, I'm like, okay, this is a problem
worth solving. Where he had two POS systems and at
least nine other tablets, and a customer had to tower
(04:30):
over those tablets to place an order with the restaurants,
so they were literally creating a wall between their customers
and themselves. Like why do you exist in the first place? Right?
That's how you know we looked at that problem. We said,
this is a problem worth solving. We went down the
route of let's integrate these orders into the POS systems.
(04:52):
You know, in a startup, you usually make if you
make one hundred decisions, ninety eight of them, you're like,
why in God's name did I make those? But there
are a couple that stick with you through your journey. Right.
The one thing that we decided since day one is
we're not going to consolidate all of those orders into
yet another tablet. We'll go straight to the prs And
(05:14):
that was a harder route, but it has served us
so well and that's the entire foundation today on which
our business has been built. So that's how we got
the start with, you know, integrating third party platforms into
the POS systems. A couple of POSS they had APIs
with the third party platforms. We scraped emails and pushed
(05:36):
them through the POS system, became large enough for the
third party platforms to give us API access and then
grew from there.
Speaker 1 (05:47):
Yeah, it was that was a crazy time tablet hell
and people having to read off a tablet and punch
the order into the POS ordering accuracies or through the roof.
Speaker 2 (06:00):
Man.
Speaker 1 (06:00):
That was definitely a good problem for you to solve.
Speaker 2 (06:05):
Not just that though, not just that. The one thing
that always blew my mind whenever I walked into a
new restaurant here, especially in lunchtime, is all of those
tablets will be going off at the same time, right,
So imagine if you have a phone in your pocket,
it starts ringing. What's your first instinct, like, have to
shut it right? And I imagine you're a staff, you're
(06:27):
a deployee standing behind the counter, there's a line of
customers waiting, and you have six other mobile phones going
off at the same time. That always blew my mind.
So it was really fun to solve it.
Speaker 1 (06:40):
So you expanded your offering pretty significantly from there.
Speaker 2 (06:45):
What was next? So obviously it was the right problem
at the right time integrating third party orders into the
POS systems. Worked with five guys on next larger enterprise customers.
Rbs it's buyer Brands is also an investor in US,
and as we scaled that out, what we realized was
(07:07):
we can't survive if we are a one point solution,
which means if you're only doing the third party degradation,
they're going to last very long. So we had to
diversify and add products that were tangential to what we
were already providing. The next obvious stop was first party ordering.
We were working with brands like RB's Sonic, buffaloil Wings
(07:29):
five guys, so we had the enterprise capability and now
we wanted to add a first party ordering, and you know,
referencing back to that all time famous conference, it was
always a fight between of them versus us, first party
versus third party, right, and my stance since then has
(07:52):
always been, it's not them versus us, but a restaurant operator.
It's part of the same value chain to have both. Right,
Unless you're a Dominos or a subway, you're not going
to have the kind of marketing reach that a door
Dash or a grap or a new Breed has. Use
those platforms to gain customers, and when you've gotten some
(08:14):
loyal customers, allow them to order directly with you. So
it's part of the same bucket. We were only offering
a part of that bucket. So then we added a
first party solution to us. So we acquired a company
in March of twenty twenty three, right, very small company,
really solid product, and started offering first party web and
(08:36):
app solution and a very very strong catering platform as well.
With it first party catering, so if somebody came to
your site, you could audit catering from there. What we've
also done is built a Kiosk solution on top of
that platform to basically be able to provide the customers
(08:57):
a very holistic sense of their digital ordering channels, and
like I was saying earlier, the fundamental foundation of all
of this, the fundamental foundation has always been the POS integration, right,
because if we think back to the days of multiple
(09:17):
tablets on a tablet on a tabletop, what coused a
problem is these were all disintegrated, disjointed solutions. They were
providing the revenue, but at what cost. I'm earning one
hundred dollars, but it's costing me eighty dollars just to
maintain that revenue. Right, at first, that one hundred dollars
(09:39):
seemed good. When the accounting team got up, They're like,
it's not that good. So what a lot of the
enterprise customers started demanding was I just need a solution
that works with my core system. And my core system
is the POS. So we have the third party integration
built on top of the POS. The first party solution
(10:02):
just works out of the box, integrated with the POS.
Catering works with the POS. Kiosk you eighty six something
on a POS, it goes out to all of your channels.
Kiosk orders print to your POS. Right, So we're providing
this holistic digital ordering suite to the restaurant operators, primarily
(10:23):
to enterprise operators. As we continued moving on, the next
big opportunity that came to us was the drive through
AI right or in general voice AI solution. Again, as
we looked at the market and saw the rapid evolution
(10:46):
of AI, we realized a lot of the companies that
were developing these solutions were spending fifty percent of their
time and just doing POS integrations. That's when I, like
bubbe hit like, we already have this right week, so
why don't we do the other fifty So we acquired
a small team along with the you know, code that
(11:12):
they had developed and the software they developed, to start
down this journey of developing a very robust right through
AI and a voice AI solution again going to come
back to the same point or just integrated with your
POS it just works right out of the game. So
that's where the evolution of our journey has taken us
(11:34):
to focusing on continue to provide enterprise grade digital ordering
channels so that the restaurant operators can be omnipresent. All right,
good stuff.
Speaker 1 (11:48):
I'd like to dig into those verticals a little bit too.
What kind of average check increases are your kiosk customers
getting from the technology and how much of the improvement
is more consistent up selling versus giving customers more time
to browse the menu versus the fact that credit card
customers just tend to spend more.
Speaker 2 (12:09):
That was our hypothesis as well, right when we were
getting into kiosk, Right, that's what everyone claimed, like, hey,
we will increase your average check size by fifteen to
twenty percent. We're not necessarily seeing that right at the
end of the day, Like again, these I go back
to the statement that one of the initial prisoner had
(12:31):
told me, what's the nice to have versus what they
must have? Chiosks have made a comeback into having into
being a must have, whether it is going to increase
your average check size or not. Right when I've spoken
with enterprise brands walked into their restaurants, spends time on
the floor that have chaosks, their thought is it may
(12:55):
or may not increase check size, it may or may
not save labor, because those are the two biggest selling
points of chiosks. Right, but today customers have come to
expect a kiosk. So if you're not doing kiosk you're
taking away one of their preferred channels. So it's not
(13:19):
necessarily about like, hey, come here and spend more. It's like,
come use the channel that's more preferred to you. So
if you want to come in browse at leisure, you
don't want to have the social pressure of the person
in front of you or the light behind you. Use
a kiosk. Right. A couple of the brands that we
spoke with and actually went and saw, what they said
(13:43):
was we've just moved the labor from behind the counter
to the floor. You know what I'm saying. A customer
walks in the door, You greet the customer, you tell
them like, please order here. If you need assistance, I'm here.
Otherwise I will leave you. Right, So you're increasing that
touch point, you're taking away the barrier of that counter
(14:05):
and the pos So it's been very eye opening in
terms of how we are selling this. We did invent kiosks.
We're not going to revolutionize kiosks, but we want to
provide a channel that seamlessly just works out of the
box and provides a great user experience for the brands
and for the diners.
Speaker 1 (14:26):
Yeah, it definitely frees up employees to do more high
value jobs and just bring up a cash redit sure, right,
and i'd imagine you know, your clients are seeing, you know,
an impact on employee turnover and employee satisfaction.
Speaker 2 (14:42):
We are starting to roll this out with a couple
of pilot with one in rollout with another large enterprise
customer in the three hundred plus location range, and the
conversation with both of them started off is like, yeah,
I don't think so we need Kiosk. I said, how
do you know, why don't you try this out at
(15:05):
one two locations on our die and see if it works.
We won't charge anything, and if it doesn't work, you know,
keep the hardware or shape it back. We don't care, right,
And that's maybe starting to see more openness and adoption.
Take oh, our customers are actually coming in and using it,
and now can we have more options there? And can
we have pizza sliced in a few different ways there? Right?
(15:26):
So yeah, that's what we're seeing exciting things about it.
Speaker 1 (15:30):
Yeah, it's really interesting too how sometimes some of these
companies are maybe a little too early with technology. I
mean Jack in the Box installed Kiosks in their restaurants
a decade ago. Wow, uninstalled them and then went back.
Speaker 2 (15:45):
Did not know that? Wow?
Speaker 1 (15:47):
Okay, yeah, yeah, So it's it's interesting, man. I think
some can be a little too early. I know Brinkers
tried out robot bussers right and those, but who knows,
maybe a decade from now they will and things have.
Speaker 2 (16:04):
Changed so much the hardware what you can do with
the software.
Speaker 1 (16:10):
So yeah, and catering is another interesting vertical. A lot
of the companies I cover our working to expand their
catering business, including Chapaulae through their Hat and the Ring.
On their first quarter earnings call, are you seeing increasing
demand from your customers for a catering solution?
Speaker 2 (16:31):
Yeah, In addition to the drive through the a solution
that we're working on, catering is our biggest opportunity. We
have definitely seen that a lot of the brands are looky.
The funny thing about catering is it's it's like an iceberg.
Only twenty percent of it is visible above the surface.
Eighty percent of the work actually happens behind behind the scenes.
(16:54):
So if it's a restaurant operator, you know, manager for
a brand, their ability to take in orders, to schedule orders,
to provide a timeline, to provide a cutoff, to do
a minimum, to do a maximum, to reroute orders, to
do a house account. All of these functionalities are actually
(17:16):
behind the scenes. So the catering interface honestly is the
easier one. And that's why when we looked at the
catering market and then compare it with the solution that
we have, we were like, this is really good. And
we actually ran this by a few independent consultants as well,
and again that's where we are seeing a huge opportunity
and scope for growth because now this gives the brands
(17:39):
and ability to create a catering sales program around it
and to create targets because now they have the tools
and the solution that can empower them to do more. Right. So, yeah,
definitely seeing a lot of growth there.
Speaker 1 (17:57):
Very cool. Last year McDonald donalds they ended their AI
voice trial with IBM after some well publicized issues. On
the other hand, Taco Bell and Wendy's are ramping up
their trials. What have been some of the issues with
voice AI to date and when do you think it'll
be ubiquitous.
Speaker 2 (18:20):
When you think about voice AI, right, we're kind of
segregating it into two aspects. One is a phone ordering AI.
I think that's ubiquitous today, right if the people doing
that can get the menu right. Right, It's not about
the phone ordering, It's not about the AI anymore. It's
a huge comportit of that is the menu right. The
(18:42):
number of people I personally get approached by somebody saying, hey,
I have a phone AI startup and here's a demo,
and my only question to them is have you ever
connected this to a real pos and then have a
customer order? That's when the rubber hits the road, right
on the drive through AI side, which is where majority
(19:04):
of our focus and attention is right now, where we
also see the largest opportunity. We think that market is,
if not one, maybe two years out from being in
a place where you can easily roll out and support
hundreds and thousands of locations. Right now, what we are
(19:27):
focused on is just one or two brands and getting
the experience absolutely right for them. The long tail here, Mike,
is really really law right. Just think about the interface.
You open up your Uber Eats app and you want
(19:47):
to order a chicken burger. They will tell you exactly
how to order it. They are guiding the interface. You
think you are selecting, but they're telling you this is
the only way to order. You select one year, two year, three? Here,
how many modifiers, how many additions, divisions and submit? It's
very very defined. Drive through AI boys AI takes away
(20:12):
that interface, takes away those boundaries. So now like I
myself listen to over one hundred live calls from customers
every single week, my mind is the same order, how
many different ways can they be to order it? But
there are because every individual is different, and that is
(20:33):
what you know. Obviously, the technology is advanced massively and
we are catching up. So what maybe was a five
year time frame has become a one one and a
half year time frame. But that's how we are looking
at this is if we, as responsible restaurant technology solution providers,
want to provide solution that the brands can rely on,
(20:56):
that they can trust us with, we have to go
slough first. If we start saying like we haven't drive
through the ice solution that's at ninety five percent accuracy
and I can service twenty brands at the same time,
you're going to burn the entire industry down. No one's
ever going to trust anyone else ever again, right, So again,
(21:18):
it just feels like, you know, it's a new startup
all over again, and we are working on this problem,
being deep in the trenches and traveling next week to
be on site, to be to listen to actual customer interactions.
But such an exciting, such an exciting space to be
in and to solve problems for.
Speaker 1 (21:38):
Yeah, it's really interesting. I remember hearing a few years
ago that, you know, one of the major problems was
more about accents and dialects being understood but by the
voice AI. But now it sounds like it shifted more
to menu customization. So is that is that accent park
kind of solved?
Speaker 2 (21:58):
It's improved. You know, I have been told very clearly
by my engineering team never to use the word solved
or fixed when it comes to AI. You know how
kind of inherit like. It's now become inherited in how
I speak has become better. It's improved. It's not going
to be completely solved. And that's where I go back
to saying, the long tail here is really long. Right,
(22:22):
you can hit that eighty percent mark, That twenty percent
is going to be very It's not hard. But if
you're not dedicated and focused on it, and you have
your attention all over the place, then you're going to
be stuck between eighty and eighty two percent for the
rest of your life. But it has to be a
very concerted client by client effort to say, for your brand,
(22:45):
this is how your customers order. You know, again, it
comes from a place of listening to real customer calls
and recordings. The same person in three different chicken burger
brands the same order, their customers will speak it out
(23:08):
in a different way. The way you order a Chick
fil A versus Popeyes versus you know, your KFC. It's fairy,
very different. That's why it requires so much effort on
a per brand, per region basis to make sure you
get it right. And you know, we are even coming
(23:33):
across situations with the menu differs from region to region.
And it's a national brand. You know, you have thousands
of locations across the country, but just because of some people,
because of customers in a specific region ordering their chicken
in a specific way has forced that brand to make
(23:55):
a slightly more nuanced menu in that region. You have
to account for that, right, So that's where we're seeing
the challenges come up versus you know, rolling out a
third party integration solution at scale. Now, that's a solved problem, right,
you know the steps you have to take to get there,
but drive through. We're being very very cautious and how
(24:18):
what we promise and what we tell the brands.
Speaker 1 (24:21):
Yeah, it's really interesting. Staying on the topic of AI,
restaurant industries being inundated with AI solutions. I think some
of them were also known as big data solutions a
couple of years ago, but I think a lot of
them would fit into that nice to have category which
we spoke to earlier, excluding the areas you know you're
playing in. What restaurant pain points are AI best suited
(24:44):
to solve?
Speaker 2 (24:47):
Was watching an interview by Jeff Bezos, right, and he
made a statement that really stuck with me. Right, he said,
AI now is like electricity. It will make better everything
that it runs through. Right. That made me think. So
(25:08):
that was one part of the conversation. Right then, I
was interviewing another candidate and I was talking to him
about his application of AI and what he's doing, and
he's like Michell. Today, the restaurant operators, if they have
a problem, they literally call me and tell me like
I'm sorry, I forgot my password, right, So that's how
(25:29):
behind they are on tech adoption. How are you going
to make them adopt AI? I tried to combine these
two conversations, and I said, do you know how electricity works? Like?
Not really? I said, but you know when you switch
out the light, your bug goes on. That's what AI
(25:50):
should do the restaurant operators. We should basically help solve
the problems for the restaurant operators while AI works in
the background. That's how I'm thinking about the application of
AI in an industry that has always been to like, hey,
your tech backward. You know, by the way, I think
the restaurant industry is take backward. Is tech backward not
(26:13):
because of their fault, but because of our fault at
some level, because we take people have come and said
we'll solve all of your problems on heaven and Earth
and everything in between. So they've become skeptical. But we
need to understand what their problems were were that they
(26:33):
couldn't solve earlier. But now AI can solve, right, So
we have to approach it from a perspective of what's
your problem? Not how can I make you use AI?
That's not an answer right. I run seventy locations in Florida,
(26:54):
and I have no idea what happens. But suddenly, like
at any point in time, seven percent of my stores
are offline in on the third party platforms. That's the problem. Now,
let's solve that using AI, making it more intelligent, either
telling you when your stores are going offline or telling
you in advance. Hey, keep a lookout. These four stores
(27:17):
are a problem, and usually they go offline because of
high drive away time, So that's what you should be
looking for. So basically, AI is helping us find the
needle in the haystack, pinpoint the problem, and not worry
about your other sixty three stores, but just focus on
these seven stores. That's how we are approaching the application
(27:38):
of AI in the restaurant space. And by the way,
that password problem also solvable by AI. I mean you
don't have to use air for that, but get rid
of using a password for God's sake, not right, Like
I don't even input user in my password on my
Chase banking app. It's faciety. There's different solutions to the problems.
(28:02):
It's not always the I, but our goal is like
always come at it from a problem perspective.
Speaker 1 (28:09):
Good stuff, man, this was fun. Thanks for doing it.
It's a checkmate dot com right if you want to
find out more about that Checkmate.
Speaker 2 (28:18):
Thank you so much for you appreciate you having me
here on Mike.
Speaker 1 (28:21):
You got it man. I also want to thank the
audience for tuning in. If you like the discussion, please
share it with your friends and colleagues. Check back soon
for an interview with Felix Linn, the CEO of HF
Foods Group.
Welcome to Chopping it Up. I'm your host, Mike hallon
the senior restaurant food Service Analysts at Bloomberg Intelligence, our
research and that a BIS five hundred analysts around the
globe can be found exclusively on the Bloomberg terminal. If
you enjoy the pod, I'd love it if you could
leave us a review on Apple or Spotify. Today I'm
joined by Vishal Agarwal, the founder and CEO of Checkmate.
(00:33):
Thanks for joining me, Mishelle.
Speaker 2 (00:35):
Thank you, Mike. Thanks for having me. It's fun to
be here. I get your emails pretty regularly, Like I
have a pretty good span blocker, but I get your
emails pretty consistently consistently in my inbox. So glad to
be here. Looking forward to seeing my name on there.
Thank you man.
Speaker 1 (00:51):
I'm excited for the interview. You look sharp in your
LinkedIn profile. Pick be honest. Who sported the leather jacket first?
Was it you for Jensen Huang and video ceo?
Speaker 2 (01:03):
Yeah? I hadn't heard of in video back then. You
know true story that pick is from my free wedding shoot.
So we were doing a pre wedding shoot and I'm like, wait,
I don't have a good LinkedIn profile picture. Can you
just make one into a professional one? They're like sure,
and the background I'm pretty sure it's not evident there.
(01:25):
But the background is actually a shape shot. It's at
Madison Park here in Manhattan. I love that park, and
the shake shot right in the middle there, so that's
where it shot at.
Speaker 1 (01:38):
Yeah, oh good stuff.
Speaker 2 (01:40):
Man.
Speaker 1 (01:40):
Listen for the record, I prefer your style. Jensen goes
a little over the top in my personal opinion.
Speaker 2 (01:46):
I will let him know. I think that's good feedback
for him. Thank you.
Speaker 1 (01:53):
All right, So let's start at the beginning. How did
checkmate come to be?
Speaker 2 (01:57):
How did Checkmate come to be? It's so funny. I'm
based in New York. I've always been based here and
moved here from India in about early twenty twelve. But
the funniest thing is that this idea did spark off
from San Francisco, right, so, as they say, the mothership
always has some bearing no matter where you're at. I
(02:19):
was working for an e commerce retail company here, wanted
to try out something new, wanted to, you know, build
a solution to an existing problem. And I was dining
in at at a restaurant at the SF airport and
it was just taking an enormous amount of time for
me to get my check and like I could miss
(02:41):
my flight, right, So that's where the idea came from.
Was the first idea that we had was to build
a mobile app that you could use to pay and
split your check when you're dining in in restaurants, so
you know, you don't have to wait for the server
to bring your check, you don't have to spend time
in splitting all of that. Right. That's why the name
Checkmate and our website is it's a Checkmate dot Com
(03:06):
because somebody was asking me for two hundred thousand dollars
for Checkmate dot Com in twenty fifteen, and it's a
Checkmate was twelve dollars. I said, that was one of
the easiest decisions that I've ever made in my life.
You know, I'll go with it to Checkmate dot com.
So that's that's how we started, right, And then that's background.
Speaker 1 (03:28):
That's great for the listeners. Mishal and I met at
the very first Food on Demand conference, which was in
Dallas back in twenty eighteen. Your comments about who owns
customer data really calls the ruckus.
Speaker 2 (03:42):
It did it did, like, I still remember that Drinkydinky hotel,
that that small lobby that was supposed to be a
conference based food and demand has come a massive, massive
way since then. But you know, we started with that
mobile app Checkmate, and I was going door to door
selling to various restaurants and an operator said like, hey, listen,
(04:08):
what are you selling me? Seems like a nice to have,
but come here, come just come behind the counter and
I'll show you what the real problem is. And what
he showed me, I'm like, okay, this is a problem
worth solving. Where he had two POS systems and at
least nine other tablets, and a customer had to tower
(04:30):
over those tablets to place an order with the restaurants,
so they were literally creating a wall between their customers
and themselves. Like why do you exist in the first place? Right?
That's how you know we looked at that problem. We said,
this is a problem worth solving. We went down the
route of let's integrate these orders into the POS systems.
(04:52):
You know, in a startup, you usually make if you
make one hundred decisions, ninety eight of them, you're like,
why in God's name did I make those? But there
are a couple that stick with you through your journey. Right.
The one thing that we decided since day one is
we're not going to consolidate all of those orders into
yet another tablet. We'll go straight to the prs And
(05:14):
that was a harder route, but it has served us
so well and that's the entire foundation today on which
our business has been built. So that's how we got
the start with, you know, integrating third party platforms into
the POS systems. A couple of POSS they had APIs
with the third party platforms. We scraped emails and pushed
(05:36):
them through the POS system, became large enough for the
third party platforms to give us API access and then
grew from there.
Speaker 1 (05:47):
Yeah, it was that was a crazy time tablet hell
and people having to read off a tablet and punch
the order into the POS ordering accuracies or through the roof.
Speaker 2 (06:00):
Man.
Speaker 1 (06:00):
That was definitely a good problem for you to solve.
Speaker 2 (06:05):
Not just that though, not just that. The one thing
that always blew my mind whenever I walked into a
new restaurant here, especially in lunchtime, is all of those
tablets will be going off at the same time, right,
So imagine if you have a phone in your pocket,
it starts ringing. What's your first instinct, like, have to
shut it right? And I imagine you're a staff, you're
(06:27):
a deployee standing behind the counter, there's a line of
customers waiting, and you have six other mobile phones going
off at the same time. That always blew my mind.
So it was really fun to solve it.
Speaker 1 (06:40):
So you expanded your offering pretty significantly from there.
Speaker 2 (06:45):
What was next? So obviously it was the right problem
at the right time integrating third party orders into the
POS systems. Worked with five guys on next larger enterprise customers.
Rbs it's buyer Brands is also an investor in US,
and as we scaled that out, what we realized was
(07:07):
we can't survive if we are a one point solution,
which means if you're only doing the third party degradation,
they're going to last very long. So we had to
diversify and add products that were tangential to what we
were already providing. The next obvious stop was first party ordering.
We were working with brands like RB's Sonic, buffaloil Wings
(07:29):
five guys, so we had the enterprise capability and now
we wanted to add a first party ordering, and you know,
referencing back to that all time famous conference, it was
always a fight between of them versus us, first party
versus third party, right, and my stance since then has
(07:52):
always been, it's not them versus us, but a restaurant operator.
It's part of the same value chain to have both. Right,
Unless you're a Dominos or a subway, you're not going
to have the kind of marketing reach that a door
Dash or a grap or a new Breed has. Use
those platforms to gain customers, and when you've gotten some
(08:14):
loyal customers, allow them to order directly with you. So
it's part of the same bucket. We were only offering
a part of that bucket. So then we added a
first party solution to us. So we acquired a company
in March of twenty twenty three, right, very small company,
really solid product, and started offering first party web and
(08:36):
app solution and a very very strong catering platform as well.
With it first party catering, so if somebody came to
your site, you could audit catering from there. What we've
also done is built a Kiosk solution on top of
that platform to basically be able to provide the customers
(08:57):
a very holistic sense of their digital ordering channels, and
like I was saying earlier, the fundamental foundation of all
of this, the fundamental foundation has always been the POS integration, right,
because if we think back to the days of multiple
(09:17):
tablets on a tablet on a tabletop, what coused a
problem is these were all disintegrated, disjointed solutions. They were
providing the revenue, but at what cost. I'm earning one
hundred dollars, but it's costing me eighty dollars just to
maintain that revenue. Right, at first, that one hundred dollars
(09:39):
seemed good. When the accounting team got up, They're like,
it's not that good. So what a lot of the
enterprise customers started demanding was I just need a solution
that works with my core system. And my core system
is the POS. So we have the third party integration
built on top of the POS. The first party solution
(10:02):
just works out of the box, integrated with the POS.
Catering works with the POS. Kiosk you eighty six something
on a POS, it goes out to all of your channels.
Kiosk orders print to your POS. Right, So we're providing
this holistic digital ordering suite to the restaurant operators, primarily
(10:23):
to enterprise operators. As we continued moving on, the next
big opportunity that came to us was the drive through
AI right or in general voice AI solution. Again, as
we looked at the market and saw the rapid evolution
(10:46):
of AI, we realized a lot of the companies that
were developing these solutions were spending fifty percent of their
time and just doing POS integrations. That's when I, like
bubbe hit like, we already have this right week, so
why don't we do the other fifty So we acquired
a small team along with the you know, code that
(11:12):
they had developed and the software they developed, to start
down this journey of developing a very robust right through
AI and a voice AI solution again going to come
back to the same point or just integrated with your
POS it just works right out of the game. So
that's where the evolution of our journey has taken us
(11:34):
to focusing on continue to provide enterprise grade digital ordering
channels so that the restaurant operators can be omnipresent. All right,
good stuff.
Speaker 1 (11:48):
I'd like to dig into those verticals a little bit too.
What kind of average check increases are your kiosk customers
getting from the technology and how much of the improvement
is more consistent up selling versus giving customers more time
to browse the menu versus the fact that credit card
customers just tend to spend more.
Speaker 2 (12:09):
That was our hypothesis as well, right when we were
getting into kiosk, Right, that's what everyone claimed, like, hey,
we will increase your average check size by fifteen to
twenty percent. We're not necessarily seeing that right at the
end of the day, Like again, these I go back
to the statement that one of the initial prisoner had
(12:31):
told me, what's the nice to have versus what they
must have? Chiosks have made a comeback into having into
being a must have, whether it is going to increase
your average check size or not. Right when I've spoken
with enterprise brands walked into their restaurants, spends time on
the floor that have chaosks, their thought is it may
(12:55):
or may not increase check size, it may or may
not save labor, because those are the two biggest selling
points of chiosks. Right, but today customers have come to
expect a kiosk. So if you're not doing kiosk you're
taking away one of their preferred channels. So it's not
(13:19):
necessarily about like, hey, come here and spend more. It's like,
come use the channel that's more preferred to you. So
if you want to come in browse at leisure, you
don't want to have the social pressure of the person
in front of you or the light behind you. Use
a kiosk. Right. A couple of the brands that we
spoke with and actually went and saw, what they said
(13:43):
was we've just moved the labor from behind the counter
to the floor. You know what I'm saying. A customer
walks in the door, You greet the customer, you tell
them like, please order here. If you need assistance, I'm here.
Otherwise I will leave you. Right, So you're increasing that
touch point, you're taking away the barrier of that counter
(14:05):
and the pos So it's been very eye opening in
terms of how we are selling this. We did invent kiosks.
We're not going to revolutionize kiosks, but we want to
provide a channel that seamlessly just works out of the
box and provides a great user experience for the brands
and for the diners.
Speaker 1 (14:26):
Yeah, it definitely frees up employees to do more high
value jobs and just bring up a cash redit sure, right,
and i'd imagine you know, your clients are seeing, you know,
an impact on employee turnover and employee satisfaction.
Speaker 2 (14:42):
We are starting to roll this out with a couple
of pilot with one in rollout with another large enterprise
customer in the three hundred plus location range, and the
conversation with both of them started off is like, yeah,
I don't think so we need Kiosk. I said, how
do you know, why don't you try this out at
(15:05):
one two locations on our die and see if it works.
We won't charge anything, and if it doesn't work, you know,
keep the hardware or shape it back. We don't care, right,
And that's maybe starting to see more openness and adoption.
Take oh, our customers are actually coming in and using it,
and now can we have more options there? And can
we have pizza sliced in a few different ways there? Right?
(15:26):
So yeah, that's what we're seeing exciting things about it.
Speaker 1 (15:30):
Yeah, it's really interesting too how sometimes some of these
companies are maybe a little too early with technology. I
mean Jack in the Box installed Kiosks in their restaurants
a decade ago. Wow, uninstalled them and then went back.
Speaker 2 (15:45):
Did not know that? Wow?
Speaker 1 (15:47):
Okay, yeah, yeah, So it's it's interesting, man. I think
some can be a little too early. I know Brinkers
tried out robot bussers right and those, but who knows,
maybe a decade from now they will and things have.
Speaker 2 (16:04):
Changed so much the hardware what you can do with
the software.
Speaker 1 (16:10):
So yeah, and catering is another interesting vertical. A lot
of the companies I cover our working to expand their
catering business, including Chapaulae through their Hat and the Ring.
On their first quarter earnings call, are you seeing increasing
demand from your customers for a catering solution?
Speaker 2 (16:31):
Yeah, In addition to the drive through the a solution
that we're working on, catering is our biggest opportunity. We
have definitely seen that a lot of the brands are looky.
The funny thing about catering is it's it's like an iceberg.
Only twenty percent of it is visible above the surface.
Eighty percent of the work actually happens behind behind the scenes.
(16:54):
So if it's a restaurant operator, you know, manager for
a brand, their ability to take in orders, to schedule orders,
to provide a timeline, to provide a cutoff, to do
a minimum, to do a maximum, to reroute orders, to
do a house account. All of these functionalities are actually
(17:16):
behind the scenes. So the catering interface honestly is the
easier one. And that's why when we looked at the
catering market and then compare it with the solution that
we have, we were like, this is really good. And
we actually ran this by a few independent consultants as well,
and again that's where we are seeing a huge opportunity
and scope for growth because now this gives the brands
(17:39):
and ability to create a catering sales program around it
and to create targets because now they have the tools
and the solution that can empower them to do more. Right. So, yeah,
definitely seeing a lot of growth there.
Speaker 1 (17:57):
Very cool. Last year McDonald donalds they ended their AI
voice trial with IBM after some well publicized issues. On
the other hand, Taco Bell and Wendy's are ramping up
their trials. What have been some of the issues with
voice AI to date and when do you think it'll
be ubiquitous.
Speaker 2 (18:20):
When you think about voice AI, right, we're kind of
segregating it into two aspects. One is a phone ordering AI.
I think that's ubiquitous today, right if the people doing
that can get the menu right. Right, It's not about
the phone ordering, It's not about the AI anymore. It's
a huge comportit of that is the menu right. The
(18:42):
number of people I personally get approached by somebody saying, hey,
I have a phone AI startup and here's a demo,
and my only question to them is have you ever
connected this to a real pos and then have a
customer order? That's when the rubber hits the road, right
on the drive through AI side, which is where majority
(19:04):
of our focus and attention is right now, where we
also see the largest opportunity. We think that market is,
if not one, maybe two years out from being in
a place where you can easily roll out and support
hundreds and thousands of locations. Right now, what we are
(19:27):
focused on is just one or two brands and getting
the experience absolutely right for them. The long tail here, Mike,
is really really law right. Just think about the interface.
You open up your Uber Eats app and you want
(19:47):
to order a chicken burger. They will tell you exactly
how to order it. They are guiding the interface. You
think you are selecting, but they're telling you this is
the only way to order. You select one year, two year, three? Here,
how many modifiers, how many additions, divisions and submit? It's
very very defined. Drive through AI boys AI takes away
(20:12):
that interface, takes away those boundaries. So now like I
myself listen to over one hundred live calls from customers
every single week, my mind is the same order, how
many different ways can they be to order it? But
there are because every individual is different, and that is
(20:33):
what you know. Obviously, the technology is advanced massively and
we are catching up. So what maybe was a five
year time frame has become a one one and a
half year time frame. But that's how we are looking
at this is if we, as responsible restaurant technology solution providers,
want to provide solution that the brands can rely on,
(20:56):
that they can trust us with, we have to go
slough first. If we start saying like we haven't drive
through the ice solution that's at ninety five percent accuracy
and I can service twenty brands at the same time,
you're going to burn the entire industry down. No one's
ever going to trust anyone else ever again, right, So again,
(21:18):
it just feels like, you know, it's a new startup
all over again, and we are working on this problem,
being deep in the trenches and traveling next week to
be on site, to be to listen to actual customer interactions.
But such an exciting, such an exciting space to be
in and to solve problems for.
Speaker 1 (21:38):
Yeah, it's really interesting. I remember hearing a few years
ago that, you know, one of the major problems was
more about accents and dialects being understood but by the
voice AI. But now it sounds like it shifted more
to menu customization. So is that is that accent park
kind of solved?
Speaker 2 (21:58):
It's improved. You know, I have been told very clearly
by my engineering team never to use the word solved
or fixed when it comes to AI. You know how
kind of inherit like. It's now become inherited in how
I speak has become better. It's improved. It's not going
to be completely solved. And that's where I go back
to saying, the long tail here is really long. Right,
(22:22):
you can hit that eighty percent mark, That twenty percent
is going to be very It's not hard. But if
you're not dedicated and focused on it, and you have
your attention all over the place, then you're going to
be stuck between eighty and eighty two percent for the
rest of your life. But it has to be a
very concerted client by client effort to say, for your brand,
(22:45):
this is how your customers order. You know, again, it
comes from a place of listening to real customer calls
and recordings. The same person in three different chicken burger
brands the same order, their customers will speak it out
(23:08):
in a different way. The way you order a Chick
fil A versus Popeyes versus you know, your KFC. It's fairy,
very different. That's why it requires so much effort on
a per brand, per region basis to make sure you
get it right. And you know, we are even coming
(23:33):
across situations with the menu differs from region to region.
And it's a national brand. You know, you have thousands
of locations across the country, but just because of some people,
because of customers in a specific region ordering their chicken
in a specific way has forced that brand to make
(23:55):
a slightly more nuanced menu in that region. You have
to account for that, right, So that's where we're seeing
the challenges come up versus you know, rolling out a
third party integration solution at scale. Now, that's a solved problem, right,
you know the steps you have to take to get there,
but drive through. We're being very very cautious and how
(24:18):
what we promise and what we tell the brands.
Speaker 1 (24:21):
Yeah, it's really interesting. Staying on the topic of AI,
restaurant industries being inundated with AI solutions. I think some
of them were also known as big data solutions a
couple of years ago, but I think a lot of
them would fit into that nice to have category which
we spoke to earlier, excluding the areas you know you're
playing in. What restaurant pain points are AI best suited
(24:44):
to solve?
Speaker 2 (24:47):
Was watching an interview by Jeff Bezos, right, and he
made a statement that really stuck with me. Right, he said,
AI now is like electricity. It will make better everything
that it runs through. Right. That made me think. So
(25:08):
that was one part of the conversation. Right then, I
was interviewing another candidate and I was talking to him
about his application of AI and what he's doing, and
he's like Michell. Today, the restaurant operators, if they have
a problem, they literally call me and tell me like
I'm sorry, I forgot my password, right, So that's how
(25:29):
behind they are on tech adoption. How are you going
to make them adopt AI? I tried to combine these
two conversations, and I said, do you know how electricity works? Like?
Not really? I said, but you know when you switch
out the light, your bug goes on. That's what AI
(25:50):
should do the restaurant operators. We should basically help solve
the problems for the restaurant operators while AI works in
the background. That's how I'm thinking about the application of
AI in an industry that has always been to like, hey,
your tech backward. You know, by the way, I think
the restaurant industry is take backward. Is tech backward not
(26:13):
because of their fault, but because of our fault at
some level, because we take people have come and said
we'll solve all of your problems on heaven and Earth
and everything in between. So they've become skeptical. But we
need to understand what their problems were were that they
(26:33):
couldn't solve earlier. But now AI can solve, right, So
we have to approach it from a perspective of what's
your problem? Not how can I make you use AI?
That's not an answer right. I run seventy locations in Florida,
(26:54):
and I have no idea what happens. But suddenly, like
at any point in time, seven percent of my stores
are offline in on the third party platforms. That's the problem. Now,
let's solve that using AI, making it more intelligent, either
telling you when your stores are going offline or telling
you in advance. Hey, keep a lookout. These four stores
(27:17):
are a problem, and usually they go offline because of
high drive away time, So that's what you should be
looking for. So basically, AI is helping us find the
needle in the haystack, pinpoint the problem, and not worry
about your other sixty three stores, but just focus on
these seven stores. That's how we are approaching the application
(27:38):
of AI in the restaurant space. And by the way,
that password problem also solvable by AI. I mean you
don't have to use air for that, but get rid
of using a password for God's sake, not right, Like
I don't even input user in my password on my
Chase banking app. It's faciety. There's different solutions to the problems.
(28:02):
It's not always the I, but our goal is like
always come at it from a problem perspective.
Speaker 1 (28:09):
Good stuff, man, this was fun. Thanks for doing it.
It's a checkmate dot com right if you want to
find out more about that Checkmate.
Speaker 2 (28:18):
Thank you so much for you appreciate you having me
here on Mike.
Speaker 1 (28:21):
You got it man. I also want to thank the
audience for tuning in. If you like the discussion, please
share it with your friends and colleagues. Check back soon
for an interview with Felix Linn, the CEO of HF
Foods Group.
Host
Michael Halen
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