October 20, 2025 • 38 mins
In this episode of the Restaurant Technology Guys podcast, Jeremy Julian sits down with Brock Weeks, CEO of Savvy, to discuss groundbreaking AI video analytics transforming multi-site restaurant operations. Brock explains how Savvy helps brands unlock valuable insights from video data, covering speed of service, guest experiences, staff performance, and delivery efficiency. They delve into the evolution of video systems from liability tools to essential business intelligence assets, emphasizing the importance of integrating video data with other business systems for full operational visibility. By addressing common challenges such as fragmented data and leveraging AI for actionable insights, the episode provides a comprehensive guide for restaurant operators looking to enhance their operations with technology.
00:00 Savi
00:14 Introduction and Guest Introduction
02:18 Brock's Background and Savvy's Mission
03:18 The Evolution of Video Technology
03:40 Challenges in Offline Retail
05:50 The Power of AI and Video Data
09:55 Current State of Video Systems in Restaurants
17:30 Business Use Cases for Video Data
21:24 Understanding Data Centralization
21:50 Identifying and Solving Operational Issues
22:55 Enhancing Guest Experience with AI
24:30 Revolutionizing Store Operations with AI
26:26 The Future of AI in Retail
30:08 Implementing AI Solutions in Your Business
36:11 Connecting with Savvy for AI Solutions
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker (00:02):
This is the Restaurant Technology Guides podcast,
helping you run your restaurantbetter.
Hey everyone.
Welcome back to the RestaurantTechnology Guys podcast.
And today's episode is a reallycool technology that's a game
changer for operators that turnvideo into data that drives
(00:25):
business intelligence.
Today I am joined by BrockWeeks, who is the CEO of Savvy.
They have some really cool AIpowered.
Video analytics that's reallychanging the way operations can
happen within a multi,multi-site restaurant group.
He shares how savvy is helpingbrands move beyond just cameras
for liability and helping themto unlock speed of service,
(00:47):
insights, guest experience,insights, staff performance,
insights, even how to makedelivery.
Flow better.
We talk about how AI is not justa buzzword, but it's really
pinpointing the root causes ofbad reviews and opportunities to
coach your team so that they canget better, and you can
ultimately have the best guesssatisfaction in the industry if
(01:07):
you're wondering how to make itwork for you.
Just sit and watch this episodeall the way till the end where
he challenges us to look atscalable solutions that are
incredibly affordable and likelyare going to be something that
you're already paying for.
If you don't know me, my name isJeremy Julian, I'm the Chief
Revenue Officer of CBS NorthStar.
We wrote the North Star Point ofSale solution for multi-units.
(01:29):
Please check us.
At CBS northstar.com, if you'renot already a subscriber, please
do so on your favorite PODpodcast platform, including
YouTube, Spotify, and ApplePodcasts.
Have a great episode.
Jeremy Julian (01:42):
Welcome back to the Restaurant Technology Guys
podcast.
I thank everyone out there forjoining us.
As I like to say at the onset ofthese, you guys have got lots of
choices, so thanks for hangingout today.
I am joined by an industrycolleague that I've met before,
but really it's only been likethe last couple of weeks that he
and I have gotten, gotten toknow each other a little bit
better.
And, I love the timing quitefrankly'cause, what Brock's
gonna talk about here.
(02:03):
As to what they've been doing isreally gonna blow people's
minds, I think.
And I'm excited to, to have himshare.
But Brock, why don't youintroduce yourself to our
listeners.
Who's Brock?
what does he get a chance to doprofessionally?
And, long walks on the beach,romantic novels, all of that
kind of stuff.
Just to introduce yourself toour listeners out
Brock Weeks (02:18):
Yeah, no, thanks for having me on Jeremy.
And we can handle that.
outside of the long walks on thebeach, I'm fortunate to be the
co-founder and CEO of a companycalled Savvy.
Where we're working to unlockthe value of video data for
multi-site restaurant and retailoperators.
really just helping themunderstand what's going on in
their business so they canoperate more efficiently.
And, more important than all ofthat,'cause what I get to do
(02:40):
daily, right?
I get to work with a lot ofreally great people, and more
important than the people that Iget to work with.
This is my family.
I'm married to an amazing wife,Kelsey, that we're gonna be
celebrating 17 years, here,this, month actually.
Yeah, thank you.
And, 17 years, tons of memories.
Three kids now a nine 11 and13-year-old that are really like
(03:01):
the most important part of mylife and get to spend a lot of
time with them and love thespace that we're in, right?
There's nothing better than, thehospitality industry.
Not only just'cause of thepeople, but it's like brands
that we get to interact with.
Like my kids can be involvedwith what I do for work and get
excited about it.
So it's ton of fun.
Jeremy Julian (03:17):
I love that.
so Brooke, you I don't say you,you went through pretty quickly,
what is video and kind of talkto me a little bit about the
advent of video.
the company's not been around.
it's been around for a while.
you started and you guys havebeen doing things, but I think
there's.
Today and even really thehistory of kind of video.
There's been a lot ofadvancements.
So talk us through what is videoand why Cho?
(03:39):
Why choose offline retail?
Because when you and I talked acouple of weeks back when we
were preparing this, it was likethe problems that we have in
offline retail are a challenge.
Getting data, integrated back ona multi-site.
So I'd love for you to walkthrough what is savvy as far as
a product and then we can diginto what problems does it solve
that people haven't, haven't,haven't been, been doing in the
(03:59):
past.
Brock Weeks (04:00):
Yeah, no, absolutely.
I think to start, and mybackground is when video started
to be utilized, in spaces was Iwas fortunate to join a pretty
high growth, technology companythat was focused on the home
automation space right out ofgraduating from college.
where I gotta spend some time intheir sales teams and building
sales teams for'em.
And then, really informative to,they received some capital
(04:20):
investment from Blackstone to beable to go on the strategy side
and really look at howtechnology was changing.
And what we saw there, which ledto starting Savvy in the future,
was the fact that these securitysystems that had been installed
in homes and had a single pointpurpose.
Because of the dividend of thesmartphone wars and technology
(04:42):
and the processing power, reallygetting extremely affordable.
You started to see these sensorshave multi-use case and because
of the internet and them beingable to talk and communicate to
each other, that alarm systemnow could be used to do things
like control your door locks,control your lights, control
your thermostats.
(05:02):
So you were able to now start todo affordable automation systems
with hardware that used to justbe used to lock your doors and
set an alarm off.
Because of the advancements ofall of these other technologies,
these sensors now became veryvaluable to a homeowner.
And we saw the same thinghappening with video, which is
(05:24):
what led me to start savvy.
Which is, it really came intoprevalence in the early in 2000
tens.
IP video got really populararound 20 14, 20 15, and people
started changing from the oldDVR or VCR to tape-based systems
and putting in these reallyrobust, solid, recording
systems.
But it was still typically beingused for single purpose, which
(05:47):
was liability protection.
Jeremy Julian (05:49):
Yep.
Brock Weeks (05:50):
But as the rest of technology started to advance
cloud computing cost and storagecost and AI analysis, which
really at the end of the day, AIjust allows you to structure
large, massive amounts of dataand gain in and out of machine,
tell you the insights out ofthat data, right?
It structures it for you, soit's more useful.
(06:13):
And we saw that.
This industry above every otherindustry was distributed, which
meant it was really difficultfor teams that weren't
physically there.
To be able to understand whythey were receiving the results
they were re achieving, andthere was always variables
amongst the different stores inthe same geographical area.
(06:36):
You would talk to the managersand they knew what a good store
should look like, but they wouldget reviews.
It became really popular to get,let's interview all of our
customers.
if I go and have a badexperience, because I'm somewhat
lazy, like most people, all I'mgonna do is say service was
slow.
I am not gonna take the time tosay, Hey, you actually had
(06:56):
enough people in the restaurant.
They just weren't doing theright task.
One person was doing this, oneperson was doing that, and that
left me to have this experienceand I waited forever.
Here, no one does that, and bynature of that, operators are
left saying, okay, we know wehave a symptom.
What's the actual root cause?
(07:17):
Crazy difficult and timeconsuming to do that.
Jeremy Julian (07:20):
and historically what people will do is they'll
put people in stores and theythen secret shop and they spend
all of this time and all of thisenergy trying to figure out what
is the root cause of theseitems.
They'll move managers around,they'll do all of these
different things and to yourpoint, they have the data at
their fingertips.
If they have the right tech, itsounds
Brock Weeks (07:37):
A hundred percent.
The vi the actual interactionsare all recorded.
A lot of'em have audio, so theyhave the video and audio of
exactly what happened.
Our premise was though, is thedata video was unstructured,
meaning the only way you couldstructure it and search it was
based upon time.
We looked at it and said, okay,if AI is going to become as,
(07:59):
powerful and as accurate, and asaffordable as the technology
trends are showing.
What do you need to do withvideo so that it can be used by
these operators because theyhave unique needs based on the
fact that they're distributedand it was, they need to be able
to move.
Like any data set, it needs tobe moved to the cloud because if
(08:19):
it's reliant on customizedhardware, and that's kinda the
trend in any technology, itstarts off very specific, very
customized and expensive pieceof hardware that does one thing.
Over time, it gets better atdoing those things and more
affordable, which you've seen inthe hardware game.
you can get a phenomenal cameranow for anywhere from 80 to$200
(08:40):
a month that like, or not amonth.
it, that's it's cost the camera.
but if you had that happeningand you need to be able to move
it to the cloud, and you neededto be able to actually structure
it by your business data.
Not by time because you don'texactly know when all these
things happened.
You just got the guest review,but you don't know exactly when
(09:01):
their experience happened.
But if you have your otherbusiness systems and you could
tie that review right to thepoint in time and search your
video data by that review, nowyou can answer those questions
really fast.
Even if AI doesn't come there,but you're able to integrate it
to your other business systems,you can start to use it.
and the last piece, was that, itneeds to be able to be given in
(09:22):
a digestible way.
To the team because a storemanager's really good and a
district manager at runningtheir business, but they're not
financial analyst.
I'm not a financial analyst.
Like you can throw me aspreadsheet and it takes me a
while to digest it.
So it needed to become in adigestible way that you were
actually not removing the peopleto spend less time in the
stores, but helping them be moreeffective when they were in the
(09:46):
stores by giving them here isthe root cause.
Now you go coach, mentor becauseyou know how to do that better
than anyone.
Jeremy Julian (09:54):
I love that.
and so I'd love to, to walkthrough Brock, just what is the
state of brands that aren'tusing a tool like Savvy?
you talked about the history andagain, I go back to some of the
earlier video days where it wasa big DVR, it's in Iraq, it.
It's, single point.
You might be able to dial intoit over the internet and go
scroll through those things.
But it's not cloud enabled, it'snot event driven.
(10:16):
It's this big box that's there.
It's connected to theseproprietary cameras that, that,
have these proprietary lines.
That's historically what I'veseen.
And then I've got my home camerasystem, which is these wireless
devices that go all over thecloud.
Check my kids.
And what time did they get home?
Their curfew was this time I wasalready sleeping.
They should, your kids are youngenough that I got three
(10:36):
teenagers at home.
Dude, I, I gotta make sure thatthey're in bed when I get up at
five 30 in the morning and makesure that they got in during
curfew.
So I look at my wirelesscameras, but there's a big
diversions from what I seeoftentimes.
Inside the restaurant brands, isthat kind of still the state of
the majority of people, or are alot of people that you guys are
working with kind of at thatstate?
I'd love for you to talk throughprior to Savvy, what are you
(10:56):
seeing out there?
talk to our operators that aresitting here listening, going,
yes, this feels like me, and getcatch me up on the state of
where things are prior togetting to savvy.
Brock Weeks (11:05):
Yeah.
because it was typically just anexpense, right?
A liability expense, aninsurance policy.
It was pretty much okay, great,I'm just gonna go get a system
that records and that I can pullup and look at.
and the reality is, especiallyfrom the mid-market on down,
right brands, that's the statemost of'em are in, and they are
trying to solve that oneproblem.
(11:26):
And I would say that.
Jeremy Julian (11:27):
The slip and fall, the underage drinking,
the, these things.
that's what you said, and I justwant to, I wanna speak to that
operator that's out there thatthe only reason they use the
camera is not to make theirbusiness better, but it's to
make sure their insurancepolicy, if something were to
happen, they've got the footageto be able to do that.
is that what you're seeing outthere?
Brock Weeks (11:43):
A hundred percent.
And is that important?
Yes, it's very valuable, right?
It's one of the things.
But what we are seeing now thatai, I think it's pretty,
Ubiquitous across anyone's inthe industry.
It's here.
And the power of AI is like it'sreal.
There's a lot of refinement anda lot of learning how to use it,
and it's only gonna keep gettingbetter.
And at a rate that is justexponentially increasing, but
(12:07):
it's here.
when any new technology comesabout and we don't quite know
how to use it, we go to thedefault, easiest path, which is
the liability.
then the operators start to say,oh, great.
I know I can UI see the visionof how I can use video.
And what they instantly do is goto a product that solves an
existing problem that they have.
So it may be speed of service,right?
(12:29):
Either it's an iot device of aloop system, or they put in a
really customized camera systemto track drive through speed of
service or in retail locations,they do guest counts and
conversion.
And once again, really valuable.
But then they start to see allof these other different use
cases.
And so what we recommend tooperators, whether they work
with Savvy or anyone else, butit's how we approach the problem
(12:52):
is that this data set.
Has immense value to yourorganization and should no
longer be neglected.
And in order for this data setto provide value, there really
needs to be three things itneeds.
You need to get a really stablesystem that's gonna run for
years, right?
You're gonna get your ROIinvestment.
You probably don't want to gobuy a$20 system at Best Buy or
(13:15):
Sam's Club, that's consumergrade for a home'cause it's
gonna be used differently.
But really affordably, you cango get just a good, economical,
reliable system.
It's gonna last us seven to 10years.
Make sure that you're coveringthe areas that you would have
business use.
Case around, not liability,right?
Business use case.
And liability.
(13:36):
Come up with a brand standard,figure out exactly how you want
to do that because a sensor is ahundred bucks.
It's more expensive to havesomeone go set it up and when
they're there, they'll do itreally affordably.
If you're having to come backevery time, you're gonna cost a
yourself a lot of money.
And because they approach theproblem back to your question of
(13:56):
what we see to just solve aproduct, we see them have.
Between two to four differenttypes of cameras or sensors with
two to four different servers,all storing video data and all
processing and analyzing videodata for different points of the
business with differentfunctionality.
(14:19):
All of them need to be managedas a separate vendor, as a
separate piece of hardware, as aseparate portal, and the data is
stored separately and siloed andfragmented.
Jeremy Julian (14:28):
That sounds awful.
Sorry.
I'm like, you're not getting mumuch business value unless you
are just the person that's therisk manager or you're just
this, or you're just that.
If you're having to do that, I'msorry to cut you off, but it's
like that blows me away to thinkthat they would have that, but.
It's not uncommon for people tosolve, they've got a, they've
got a pain on their finger.
They're gonna solve the pain intheir finger.
They got a pain in their foot,they're gonna go to a different,
(14:49):
so I love that analogy'cause Ididn't realize that was, that it
was so disparate.
'cause you never are gonna havesomebody that's gonna have one
POSI mean, we work in the p osspace.
They're not gonna put a POS inthe drive-through, in a
different one at the frontcounter.
But it sounds like they're doingsimilar things.
They're gonna have one for theirdrive through.
They're gonna have one for theirfront counter.
They're gonna have one for theback walk-in.
that's insane to me.
But I'll let you keep goingbecause it's
Brock Weeks (15:08):
No, you're, it's back to the days, right?
Of the different iPads for allthe different third party
deliveries.
And it's no one, anyone couldjust look at that and say, this
is not a good idea.
Like so many fell points.
And if you're looking at itvideo, because it does answer
all of these questions well,even if the AI is as powerful as
could be.
It is only as powerful as thedata set it's applied against.
(15:30):
So if it's always only lookingat this fragmented
Jeremy Julian (15:32):
Yeah.
If it's only a pars parsed pieceof data, then it makes it really
tough to deal with
Brock Weeks (15:36):
Correct.
It's like when you go into abrand and the drive through's
humming because they'remeasuring the speed of service,
but you stand in the lobby for15 minutes going I got an ice
cream addiction.
Like I just want a frosty folks.
let's take
Jeremy Julian (15:46):
Yeah.
Yeah, exactly.
I'm gonna go get in my car andgo get it faster to sit back
down in the dining room.
Brock Weeks (15:52):
Yeah, because once again, if you only look at one
piece, you don't get theholistic view.
So that really is what we'reseeing, and it's happening at
small brands and it's happeningin large brands.
And so whether it's with Savvyor anyone, it's.
Look at this as a techno, a keypiece of your tech stack and a
key data point.
If what we've talked about, likeyou're like, yeah, I would love
(16:13):
to know those things in mybusiness.
Great.
The data needs to be aggregatedand you typically, you've seen
this in point of sale.
Where the hardware hasessentially become separated
from the software.
If you looked years ago, you hadto buy this whole package where
everything worked together.
It was very hardware focused.
Then cloud computing and all ofthat allowed the software to
(16:34):
separate from the hardware tonow most of the point of sale
vendors, their hardware is notproprietary.
It's right.
Then they may be interchangingdifferent hardware and different
software companies.
I think you need to take thesame approach because.
The most expensive part ofadopting any technology is
disrupting the store and havingto change it.
(16:54):
And if every two years you'rehaving to do like a rip and
replace disruption, it's gonnaget difficult.
So get a great hardware layer,centralize the data set, and
look at it as a, a piece of, atrue piece of the data stack and
as a dataset rather than aproduct.
And then you'll be in a reallygood position.
Jeremy Julian (17:12):
Yeah.
I love that, that thought.
So Brock, I'm gonna, twist itaround just a little bit.
You talked a little bit aboutwhere things started.
We talked a little bit about theevolution of, some of the
hardware stuff and just how mucheasier it's gotten to deploy.
Talk to me a little bit aboutkind of some of the big business
use cases you're seeing outsideof using AI to ask the questions
that you need.
Risk management, whereeverything started, but you're,
(17:33):
you talked about some thingsthat I think our listeners may
not have considered that you areseeing.
Drive business value to theirbusiness as they implement
savvy?
Is it speed of service?
Is it, guest satisfaction?
Is it staff member stuff?
I, you and I talked offline andI'd love for you to share two or
three examples of things thatyou see so few operators doing,
(17:54):
and then when they get it, itjust drives monumental results
inside of their business.
Brock Weeks (17:59):
Yeah.
we'll start with, that guestexperience.
We chose to take that as one ofthe first kind of key things we
wanted to tackle because as welooked at reviews of
restaurants.
Three quarters of all negativereviews reference the speed of
service, the interaction withthe employees.
Or cleanliness of therestaurant.
(18:20):
Those were like the key pillarcornerstones of most negative
reviews.
It wasn't actually the qualityof the food, it wasn't those
things.
and so we looked at and said,Hey, can video actually move the
lever here to improve thequality of the operator's lives
and answer these questions?
And the question, the answer wasyes.
So speed of service, not only,there's a couple different
brands where we've got the casestudies published on our
(18:41):
website.
That, before they were spendinganywhere from six to$15,000 a
store to install a differenttype of loop system to measure
the drive-through speed ofservice.
studies show those are in thehigh 70% accurate.
It's basically vehicle in,vehicle out, and if anything
gets off, it resets every 30minutes so that it can
recalibrate.
as everyone knows, reallyexpensive, only showed a part of
(19:04):
the journey.
and so employees, better orworse, when you start to measure
things, they start to try togame the system.
And we've all been there whereyou've been held up beginning to
the menu board to actuallyorder, because that's when the
timer's gonna start.
Or you've gone to pay and yourorder's not ready yet.
And they're like, yep, can youjust pull forward over to there?
And then you get forgot aboutand left.
(19:24):
You have to get outta your car.
Like we, we've all had theseexperiences.
And what we're saying is most ofthese brands have installed
cameras out there for theliability protection.
AI can now accurately andaffordably track the entire
guest experience, and you canactually segment it by just
drawing regions of interestdigitally on the camera and
(19:45):
start tracking not only theholistic view of when they enter
the lot and when they leave thelot.
But also the actual differentsteps within that process.
So you can start to reallyrefine where do I have
bottlenecks?
Because it's really justmanufacturing capacity and
throughput capacity.
And so when you start to provideyour team more insights and
(20:06):
visual data by measuring thesethings, and it's done in a way
that it cannot be gained, thefocus moves to actual process
improvement instead of crisismanagement historically.
Jeremy Julian (20:18):
Or I'm gonna get yelled at.
'cause I moved this car up andthen they got pissed and then
they gave me a bad review.
It's what caused me, what orderdid they place that caused our
kitchen to get backed up?
What is happening there?
And I love that you said that's,because that's.
That is, and again, historicallywith a time-based system, you'd
have to look through hours andhours of tape to figure out what
happened there.
Whereas now with some of thisadvent, it's Hey, what, I guess
(20:40):
I'd love that query, what isthat question that you can ask
the AI that says how manyorders?
I, just share it with us and Ipromise you, because you and I
talked prior, I hit the recordbutton.
Some of our listeners are gonnabe like, what?
You can do that today?
Brock Weeks (20:53):
Yeah, it's once again, measuring time and
segmenting it.
That's, once again, it's morejust giving you the baseline.
you can just hit a button and belike, show me the five longest
wait times, and then watch theentire process of that.
Jeremy Julian (21:06):
Yeah.
And people are gonna be blownaway, Hey, what, who's anybody
that's been over four minutes inthe drive through, six minutes
in the drive through, eightminutes in the drive through,
and you just look at that, it'snow I can see all of the videos
and it's Hey, on Tuesday we hada really crappy shift.
We on Wednesday we did great.
And so I, it's so much simplerthan people make it out to be
and I appreciate you sharingthat.
Brock Weeks (21:24):
And because you've centralized the data of your
business systems while you'rewatching that experience, you
have the transaction data.
So you know.
Was it just a really large orderthat threw us off?
Because that happens, right?
And you can't, or was it, Hey,we actually got the order wrong,
and so we were issuing a refund.
But while we were doing that, weheld up all these other guests.
Could we actually have moved?
(21:45):
That might be.
Jeremy Julian (21:46):
did we run outta stock between the time they
ordered it and the time that,that you had to fulfill the
order?
there's so many differentopportunities, but back to your
point, once they know where thedata problem is, they can
operationally go solve it,rather than being in crisis
management of, I'm gonna get introuble, or I'm not gonna hit my
bonus because my wait times aretoo
Brock Weeks (22:02):
Yeah.
'cause before it was just, oh,it's red and it's, they've been
here too long.
Ah, what do I do?
And that was all you werelooking at was the fire where
it's no, let's, and how do thesestages compare cross locations?
Because when you're looking atthat holistic view, you can
really start to go and coach andsay, Hey, is this a company-wide
process problem?
Is this just a store managerproblem and training problem?
(22:25):
Is this a shift lead problem?
It really allows you to getsuper.
Jeremy Julian (22:28):
Is this a menu mix problem for that store?
do they order too many saladsand they take too long to
produce out of this store versusburgers at another store?
Yeah, so many different waysthat would take hours and really
data analyst tools and peoplesitting there analyzing these
things.
What's another use case, Brock,that people are using this for,
that you think would blowpeople's minds to go.
(22:48):
How, how have we been doing thisso manually and now at our
fingertips in an aggregated way?
We can just knock it out prettyquickly.
Brock Weeks (22:55):
Yeah.
before diving into that, I wannamention do the same thing on get
measuring guest speed of servicein the store.
Why do we only care about acertain segment of the customer?
let's track so that we know ifthe drive through's home and an
in store is not, we want both.
the second.
Jeremy Julian (23:10):
It'd be interesting to actually ask that
question even on third party,because I see the third party
problem being a huge issue.
'cause so many brands weren'tdesigned with third party in
mind and they've got the regularguests and then they've got the
third party guests and theyoftentimes will screw up a guest
experience because I've got myDoorDash drivers waiting in the
same space.
sorry.
I'll let
Brock Weeks (23:27):
No, and you can track that now, right?
Because they typically arepicking up at different areas
and the AI is good enough.
Now it uses a Reid technologythat basically says, Hey, I'm
not gonna facial analyze Brock,but I'm gonna say he's in a
maroon shirt.
He's right this big.
He's the, he's got this colorhair, all these attributes.
And then I know what areas ofthe store he went into.
So I can say, Hey.
(23:48):
I've got all these DoorDashpeople just show me the people
that just followed this flow.
That's why we call it customerflow ai, this flow.
What was their experience andhow long were they in the
different areas?
'cause we have, it's, and Iempathize with these frontline
employees where you're in thereand I've got my family and I'm
trying to order in store.
No one else is in line, butthey're just back there humming
(24:09):
on third party delivery orders.
What I'm
Jeremy Julian (24:12):
And the DoorDash driver's sitting there with his
phone going, I need my order.
I need my order.
And you're like, you're tryingto get your kids to go through
the line ordering and it's a badguest experience for both sides,
right?
Brock Weeks (24:21):
So it's okay, now let's measure this.
Let's identify it, see exactlywhat the baselines, and now we
made a change.
How did it impact?
And the second piece, back toyour, what other technology?
we call it site check ai, buthistorically, when you had to.
Train ai.
It was really just a computervision model.
It wasn't ai, it was machinelearning.
And it was, I'm gonna train iton seeing a maroon shirt,'cause
(24:42):
that's your uniform.
So I'm gonna train this data setand it's gonna get really good
at looking at maroon shirts.
now AI is just getting to whereit looks at an image and says,
Hey, I've been trained on all ofthese large models.
What is it you want me to pickout?
And so you think about thethings that a secret shopper or
a district manager does whenthey're in the store from a
cleanliness standpoint.
(25:02):
Is table turn happening?
Is the floor is being cleaned?
Have we put out the floor matsfrom a safety standpoint?
Are the employees wearing theiruniform are personal self
Jeremy Julian (25:10):
line checks?
Are they making sure thatthey're doing the temp checks?
All of those kind of things.
Brock Weeks (25:14):
the two stopped?
Jeremy Julian (25:15):
many things that continue to happen.
Sorry.
Brock Weeks (25:17):
No, you're on the, do you just start to go.
Wow, there's a lot there.
And though it's gonna continueto even get better right now,
think about it, if I visuallycould stand there from the angle
of the camera and look at itlike, is it gonna be able to
read the serial number off of adollar bill?
No.
But is it gonna be able to tellyou like, Hey, you got a bunch
of tables that are sitting therewith trash on there and no guest
(25:39):
and they've been sitting thereforever.
Yeah.
Spills, employee uniform,personal cell phone device,
safety issues like boxes,covering entrances, things of
that nature.
But it's gonna happen all day atright at intervals of time
because the affordability's notquite there to run it.
24 hours a day yet, but you cansay, Hey, every 20 minutes at
periodic times, run these checksand just give me a compliance
(26:03):
score and then quickly show mewhere I'm at compliance.
So I can look and say, you knowwhat?
I'm at 97%, I'm good.
No one's perfect.
Or, Hey, I'm at 70%.
Why?
And it will quickly take youright to that point in time
where you just hover over thered mark and it's here's the
image in the video of whathappened.
So you're not saying once again,oh, why am I having this
(26:23):
compliance?
It's, oh, look what's happening.
And the reason why we focused onthose two key products and
there's more coming.
It was when they started to lookat the customer speed of
service.
The customer flow started toincrease, meaning they weren't
getting as many people through.
They were decreasing theirthroughput.
There was other problems goingon in the restaurant.
Jeremy Julian (26:45):
Yep.
Brock Weeks (26:45):
and so they're correlated together.
And so if you can affect, onceagain, those are two of the core
pillar things that affectnegative reviews at its core.
It now allows you, when you'rein the store to not spend time
researching, but spend timecoaching and mentoring.
Jeremy Julian (27:01):
Yeah.
those two use cases areincredible and I love that you
chatted through, through thatthe power of the software is a
pretty big piece, I guess Brock,'cause you can go to Costco, you
can go to Best Buy and go buycameras.
you talked about.
I guess I'd love for you to talkto our listeners about those
people that think they have itall figured out.
'cause they've, gone and boughtthem at Best Buy and they're
(27:21):
sitting on their couch at night,while their wife's watching The
Bachelorette, reading through,watching through all of these
videos on their phone.
But really at the end of theday, that's a huge waste of
time.
'cause now software's sitting ontop of these things.
For those people that kind ofwent super consumer what.
where are the opportunities andwhat is the delta even in the
price of the hardware and thesoftware to get to something
that's more professional gradeand more commercial grade, to be
(27:43):
able to do what it is that theyneed to do and save them so much
time and so much
Brock Weeks (27:47):
Yeah, it's so much closer than it used to be.
I do need to point out Savvy'scompletely hardware agnostic.
To deploy our system, you plugin a little device smaller than
my cell phone, and that's it.
It just compresses and encryptsthe data and sends it to the
cloud.
Jeremy Julian (28:02):
So you can use any IP camera.
Brock Weeks (28:03):
Any IP camera, we don't care what the cameras, as
long as it's commercial grade.
Back to that.
In order for our analytics torun the camera needs to be
continuing to run the deltabetween a consumer grade camera
and a commercial grade camera isprobably less than 20% now, like
it's
Jeremy Julian (28:20):
Percent.
Brock Weeks (28:21):
hundred percent.
It's so close.
Like fantastic brands like AWAand Access and Vivo, taking the,
they're building phenomenalcameras at really affordable
prices, especially for thisindustry.
Where you can go and do that,and there's so many, great
resources out there and MSPs andintegrators that are offering
these at really affordablerates.
The key thing becomes is, what'sthe, what does the technology
(28:44):
need to do, which is it needs tocapture the image so it needs
good light management and goodresolution.
Do.
Do you need eight K at arestaurant?
Looking at a lobby?
No.
Go get just a good camera thathas good light management and is
gonna last and is reliable onceyou're there, we say like the
magic should happen in thesoftware because it's gonna
(29:04):
change.
Technology's gonna advance.
Just if I had, I have an iPhonehere.
I wanted to use AppleIntelligence, but I didn't.
I had the 14 pro, and so it, itwasn't capable on my hardware.
If you approach everything,there's certain things that
hardware and software should be100% married together, but if
you do that, you limit theecosystem that you can play in.
(29:27):
The power of what I do with myiPhone is, yes, it's enabled by
the processing power, but it isthe creativity that has been
unlocked from the App Store thatI can then download and use from
a software standpoint.
And so our recommendation isfind open systems.
You should, if savvy was notperformant, you shouldn't be
(29:47):
locked to me and be outthousands and thousands of
dollars.
You should be able to pivot asan organization fairly quickly
and so good.
Jeremy Julian (29:56):
So I am wholeheartedly agree.
We talk about the freedom ofchoice all the time at CBS and
it's just, it's so critical.
'cause again, it puts the onus,onus on us to do it right.
And like you, it sounds likeyou're leading the team in that
way.
Brock, for those that aresitting here going, you know
what?
I need this now.
What does it even look like?
Can you use existing systems andlayer this stuff on?
Do they need to go run cables toeverywhere that they need these
(30:19):
things?
Can you start small and grow, Iguess help walk through what it
would look like if people aresitting there going, I need this
in my life.
I haven't had this.
How do I get there?
Brock Weeks (30:28):
Yeah, Where you have 10 stores, a hundred stores
really look at it and say, okay,we do a virtual site audit,
which is looking at the, whatthe current camera models are
and what the angles of view are.
Are they just, do they need tobe repositioned?
Are they in the right spot or dothey need to be added?
From there, we literally dropship our device.
(30:49):
You plug it in on the network,it needs to be on the same VLAN
as the camera sensors, and ifit's integrated to the security
sensors and other things, needsto be on that same vlan.
N it encrypts, sends the data toour cloud, goes and says, Hey,
you need to give me thecredentials.
I'm in charge now.
Send the data.
And then right through most ofthe forward thinking point of
sale systems and great ones outthere like you all as well.
(31:10):
It's just a backend APIintegration.
You hit the button, the datastarts flowing, you map the
cameras.
And honestly from saying, Iwould love to do this, if
everything's in good shape andthe hardware works there, you're
up and running in a coupleweeks.
Like the actual time on site isanywhere from 10 minutes to, two
hours if they need to adjustangles of cameras.
(31:30):
And most of that's just climbingup and down a ladder and looking
at the angle adjustment, right?
Jeremy Julian (31:35):
Yeah.
two things real quick there.
You, we didn't really, dig deepinto kind of the other
technologies that are in thestore and integrating those.
You alluded to point of sale, isthat your guys's primary, I
guess talk through the use caseon why would you integrate with
point of sale, and what doesthat do for you?
Brock Weeks (31:50):
Yeah.
Point of sale labor systems area really important one, so you
can understand like that ratioof speed of service to labor.
unfortunately employee timetheft does exist, and so you
wanna be able to audit and havethe system run and verify those
checks, the alarm sensors andsystems smart safes.
Think about what are the keypieces of technology.
(32:11):
That something's happening andinteracting with that, I would
want to know.
Why I got that result, right?
Discrepancy in cash deposit,something rang up at the
transaction and the way weintegrate it there is it's
actually we put it all in thecloud and flatten it out so you
can search your video data byit.
So whether it's a lossprevention use case of saying,
(32:34):
show me every time that a cashrefund was done that a guest
wasn't present, right?
That's build an audit workflow,the exception based workflow, it
just throws it in a quick digestfor you.
You click through it in a fewseconds and answer the
questions.
But your product team, and menuteam, they might wanna look
through and be like, Hey, showme who's buying this item,
(32:54):
right?
Or, show me when there's acustomer complaint comp, or
Jeremy Julian (32:58):
Yeah, gimme every transaction that was over 150
bucks.
'cause did we go out and do atable touch when it was a high
value customer?
whatever.
Brock Weeks (33:05):
All of those things, there's questions around
it.
Really, it's just allowing youto get to that point in time
with the context.
'cause when you're watching, youwanna have full context, so with
the full context so that you canactually look at it.
Diagnose the problem and then gotake action.
That's how it exists today.
Where I see it going, Jeremy, iswhat gets really exciting.
(33:26):
I don't think in a few yearspeople are really gonna look at
video.
What's gonna happen is you'regonna have these AI agents,
right now we're doing this, thestructure, all the data
together, aggregate it, sochecks Abby's doing that.
Second, we're applying specificmodels to specific use cases.
Speed of service, guestexperience.
That's site check.
That's almost like a filteringlayer and the integrations to
(33:48):
the sensors and all that arefiltering layers.
But when this happened and I sawa discrepancy, then an agent
goes and watches the video,analyzes it and says, no, you're
good.
This was right.
Or No, this was potentially bad.
Surfaces it into, here's yourchecklist of action items you
need to take.
If you wanna click on the link,it's gonna take the same way
that AI works right now.
Jeremy Julian (34:07):
You would now, but it, but you know what,
you'll have peace of mind thatsays, you know what, I put my 40
or 50 or 60 use cases in thereand it's really only delivering
me the two or three.
That might be a problem that arecoaching opportunities or
whatever else I.
Brock Weeks (34:19):
Yeah, those high impact things that you want it
to be doing, and it's right, itdoesn't replace anyone.
What it does is amplify people.
To spend less time doing themundane and more time connecting
with their teams and connectingwith, Those people that they
want to coach, that they wannamentor, that they, From a loss
prevention standpoint was justhaving lunch yesterday with a
(34:39):
franchisee who, once again, whyI love the hospitality industry.
He was just all about hispeople.
He's got 60, almost 60 stores,right?
And he's just all about the teamand how he helps, and we were
talking about loss preventionand he was like, yeah, I used to
look at it as big brother.
Like I don't wanna be that.
And, but he's I've had the.
times over my career wherepeople have stolen significant
amounts and we've had toprosecute and why did, what if
(35:00):
you caught that person the veryfirst time they did it and just
said, Hey, this is a pro.
Like you can't do this.
This is theft.
'cause a lot of times it doesn'tstart out that way.
It's just some innocentdiscounts, some innocent gifts,
some friends, some things catch'em that time instead of having
to prosecute and end up withsomething on their record and
really disrupt their lives.
It's all of these different usecases, which is really just.
(35:21):
Highlight good behaviors,replicate those, coach on them,
and find those correctivebehaviors so that you can
address them.
Jeremy Julian (35:30):
I love that you went there'cause that was my
next line of questioning is whatdo you say to those people that
are like, I don't need BigBrother, I don't need all of
this stuff.
I don't, all of the privacythings.
I guess it sounds like you guyshave already it ultimately again
goes back to how do I make mybusiness better?
How do I make my team better?
How do I make my customerexperience better?
Is really where you guys are fofocusing so much of your time
and energy in the tools that youguys are building.
(35:52):
Is that, is that correct?
Brock Weeks (35:53):
A hundred percent.
that's where the impact is at.
If I, simple analogy in my life,my big brother definitely hasn't
been there to point out and,crack this, the whip at me, he's
been there to correct me on,Hey, you might be getting a
little off here.
I'm seeing this right?
let's bring you back.
that's truly what it should beused for in our.
Jeremy Julian (36:10):
Love it.
so Brock, how do people learnmore?
How do people get, you talkedabout, from time to, to even
knowing what we're doing togetting up and running it, it
can be done in as little as acouple of weeks.
So how would they learn more?
How would they get in touch?
How would they move forward?
because again, I.
I look at what you guys aredoing and I'm just, I was blown
away.
I was so excited when you sharedit with me.
I was like running around I waslike a little kid, on Christmas
(36:30):
morning.
Super excited about all of wherethings have gone because my
history really goes back to someof the old days when I last
looked at this tech.
And so it's amazing how far it'scome.
for our listeners out there thatare excited and wanna learn
more, how do they do that?
Brock Weeks (36:43):
Yeah, we're, I'm personally active on LinkedIn.
Would love to, chat with you andintroduce you to some members of
our team who can even, dive indeeper with you.
get savvy.com and it's SAVI, isour website.
We'll also post a link, in herethat has a specific one for
this, this show.
And then at the differentconferences, we're gonna be at
QSR, evolution, the Fast CasualExecutive Conference, FS Tech,
(37:05):
and a bunch of others coming uphere this fall.
Would love to chance to interactwith you all.
Jeremy Julian (37:10):
Awesome.
Brock, I genuinely, I was blownaway with some of the stuff that
you shared with me just in in abrief demo.
And so I think, and I say thisto listeners all the time, if
you're not doing it, guess whois your neighbor that's beaten
you to your left and yourneighbor that's beaten you to
your right is using thistechnology as a business driver
to change the conversation.
(37:30):
And so I would really encourageall of you guys to go check out,
get Savvy.
check out Brock's stuff.
they do an amazing job ofhelping you learn how to get to
this place.
And so thank you for taking thetime, Brock, to share.
To our listeners, guys, we knowthat you guys got lots of
choices, so thanks for hangingout.
If you haven't alreadysubscribed, please do so on your
favorite podcast, tool and orYouTube and make it a great day.
Brock Weeks (37:50):
Awesome.
Thanks Jeremy.
Speaker 2 (37:53):
Thanks for listening to The Restaurant Technology
Guys podcast.
Visit restaurant technologyguys.com for tips, industry
insights, and more to help yourun your restaurant better.
This is the Restaurant Technology Guides podcast,
helping you run your restaurantbetter.
Hey everyone.
Welcome back to the RestaurantTechnology Guys podcast.
And today's episode is a reallycool technology that's a game
changer for operators that turnvideo into data that drives
(00:25):
business intelligence.
Today I am joined by BrockWeeks, who is the CEO of Savvy.
They have some really cool AIpowered.
Video analytics that's reallychanging the way operations can
happen within a multi,multi-site restaurant group.
He shares how savvy is helpingbrands move beyond just cameras
for liability and helping themto unlock speed of service,
(00:47):
insights, guest experience,insights, staff performance,
insights, even how to makedelivery.
Flow better.
We talk about how AI is not justa buzzword, but it's really
pinpointing the root causes ofbad reviews and opportunities to
coach your team so that they canget better, and you can
ultimately have the best guesssatisfaction in the industry if
(01:07):
you're wondering how to make itwork for you.
Just sit and watch this episodeall the way till the end where
he challenges us to look atscalable solutions that are
incredibly affordable and likelyare going to be something that
you're already paying for.
If you don't know me, my name isJeremy Julian, I'm the Chief
Revenue Officer of CBS NorthStar.
We wrote the North Star Point ofSale solution for multi-units.
(01:29):
Please check us.
At CBS northstar.com, if you'renot already a subscriber, please
do so on your favorite PODpodcast platform, including
YouTube, Spotify, and ApplePodcasts.
Have a great episode.
Jeremy Julian (01:42):
Welcome back to the Restaurant Technology Guys
podcast.
I thank everyone out there forjoining us.
As I like to say at the onset ofthese, you guys have got lots of
choices, so thanks for hangingout today.
I am joined by an industrycolleague that I've met before,
but really it's only been likethe last couple of weeks that he
and I have gotten, gotten toknow each other a little bit
better.
And, I love the timing quitefrankly'cause, what Brock's
gonna talk about here.
(02:03):
As to what they've been doing isreally gonna blow people's
minds, I think.
And I'm excited to, to have himshare.
But Brock, why don't youintroduce yourself to our
listeners.
Who's Brock?
what does he get a chance to doprofessionally?
And, long walks on the beach,romantic novels, all of that
kind of stuff.
Just to introduce yourself toour listeners out
Brock Weeks (02:18):
Yeah, no, thanks for having me on Jeremy.
And we can handle that.
outside of the long walks on thebeach, I'm fortunate to be the
co-founder and CEO of a companycalled Savvy.
Where we're working to unlockthe value of video data for
multi-site restaurant and retailoperators.
really just helping themunderstand what's going on in
their business so they canoperate more efficiently.
And, more important than all ofthat,'cause what I get to do
(02:40):
daily, right?
I get to work with a lot ofreally great people, and more
important than the people that Iget to work with.
This is my family.
I'm married to an amazing wife,Kelsey, that we're gonna be
celebrating 17 years, here,this, month actually.
Yeah, thank you.
And, 17 years, tons of memories.
Three kids now a nine 11 and13-year-old that are really like
(03:01):
the most important part of mylife and get to spend a lot of
time with them and love thespace that we're in, right?
There's nothing better than, thehospitality industry.
Not only just'cause of thepeople, but it's like brands
that we get to interact with.
Like my kids can be involvedwith what I do for work and get
excited about it.
So it's ton of fun.
Jeremy Julian (03:17):
I love that.
so Brooke, you I don't say you,you went through pretty quickly,
what is video and kind of talkto me a little bit about the
advent of video.
the company's not been around.
it's been around for a while.
you started and you guys havebeen doing things, but I think
there's.
Today and even really thehistory of kind of video.
There's been a lot ofadvancements.
So talk us through what is videoand why Cho?
(03:39):
Why choose offline retail?
Because when you and I talked acouple of weeks back when we
were preparing this, it was likethe problems that we have in
offline retail are a challenge.
Getting data, integrated back ona multi-site.
So I'd love for you to walkthrough what is savvy as far as
a product and then we can diginto what problems does it solve
that people haven't, haven't,haven't been, been doing in the
(03:59):
past.
Brock Weeks (04:00):
Yeah, no, absolutely.
I think to start, and mybackground is when video started
to be utilized, in spaces was Iwas fortunate to join a pretty
high growth, technology companythat was focused on the home
automation space right out ofgraduating from college.
where I gotta spend some time intheir sales teams and building
sales teams for'em.
And then, really informative to,they received some capital
(04:20):
investment from Blackstone to beable to go on the strategy side
and really look at howtechnology was changing.
And what we saw there, which ledto starting Savvy in the future,
was the fact that these securitysystems that had been installed
in homes and had a single pointpurpose.
Because of the dividend of thesmartphone wars and technology
(04:42):
and the processing power, reallygetting extremely affordable.
You started to see these sensorshave multi-use case and because
of the internet and them beingable to talk and communicate to
each other, that alarm systemnow could be used to do things
like control your door locks,control your lights, control
your thermostats.
(05:02):
So you were able to now start todo affordable automation systems
with hardware that used to justbe used to lock your doors and
set an alarm off.
Because of the advancements ofall of these other technologies,
these sensors now became veryvaluable to a homeowner.
And we saw the same thinghappening with video, which is
(05:24):
what led me to start savvy.
Which is, it really came intoprevalence in the early in 2000
tens.
IP video got really populararound 20 14, 20 15, and people
started changing from the oldDVR or VCR to tape-based systems
and putting in these reallyrobust, solid, recording
systems.
But it was still typically beingused for single purpose, which
(05:47):
was liability protection.
Jeremy Julian (05:49):
Yep.
Brock Weeks (05:50):
But as the rest of technology started to advance
cloud computing cost and storagecost and AI analysis, which
really at the end of the day, AIjust allows you to structure
large, massive amounts of dataand gain in and out of machine,
tell you the insights out ofthat data, right?
It structures it for you, soit's more useful.
(06:13):
And we saw that.
This industry above every otherindustry was distributed, which
meant it was really difficultfor teams that weren't
physically there.
To be able to understand whythey were receiving the results
they were re achieving, andthere was always variables
amongst the different stores inthe same geographical area.
(06:36):
You would talk to the managersand they knew what a good store
should look like, but they wouldget reviews.
It became really popular to get,let's interview all of our
customers.
if I go and have a badexperience, because I'm somewhat
lazy, like most people, all I'mgonna do is say service was
slow.
I am not gonna take the time tosay, Hey, you actually had
(06:56):
enough people in the restaurant.
They just weren't doing theright task.
One person was doing this, oneperson was doing that, and that
left me to have this experienceand I waited forever.
Here, no one does that, and bynature of that, operators are
left saying, okay, we know wehave a symptom.
What's the actual root cause?
(07:17):
Crazy difficult and timeconsuming to do that.
Jeremy Julian (07:20):
and historically what people will do is they'll
put people in stores and theythen secret shop and they spend
all of this time and all of thisenergy trying to figure out what
is the root cause of theseitems.
They'll move managers around,they'll do all of these
different things and to yourpoint, they have the data at
their fingertips.
If they have the right tech, itsounds
Brock Weeks (07:37):
A hundred percent.
The vi the actual interactionsare all recorded.
A lot of'em have audio, so theyhave the video and audio of
exactly what happened.
Our premise was though, is thedata video was unstructured,
meaning the only way you couldstructure it and search it was
based upon time.
We looked at it and said, okay,if AI is going to become as,
(07:59):
powerful and as accurate, and asaffordable as the technology
trends are showing.
What do you need to do withvideo so that it can be used by
these operators because theyhave unique needs based on the
fact that they're distributedand it was, they need to be able
to move.
Like any data set, it needs tobe moved to the cloud because if
(08:19):
it's reliant on customizedhardware, and that's kinda the
trend in any technology, itstarts off very specific, very
customized and expensive pieceof hardware that does one thing.
Over time, it gets better atdoing those things and more
affordable, which you've seen inthe hardware game.
you can get a phenomenal cameranow for anywhere from 80 to$200
(08:40):
a month that like, or not amonth.
it, that's it's cost the camera.
but if you had that happeningand you need to be able to move
it to the cloud, and you neededto be able to actually structure
it by your business data.
Not by time because you don'texactly know when all these
things happened.
You just got the guest review,but you don't know exactly when
(09:01):
their experience happened.
But if you have your otherbusiness systems and you could
tie that review right to thepoint in time and search your
video data by that review, nowyou can answer those questions
really fast.
Even if AI doesn't come there,but you're able to integrate it
to your other business systems,you can start to use it.
and the last piece, was that, itneeds to be able to be given in
(09:22):
a digestible way.
To the team because a storemanager's really good and a
district manager at runningtheir business, but they're not
financial analyst.
I'm not a financial analyst.
Like you can throw me aspreadsheet and it takes me a
while to digest it.
So it needed to become in adigestible way that you were
actually not removing the peopleto spend less time in the
stores, but helping them be moreeffective when they were in the
(09:46):
stores by giving them here isthe root cause.
Now you go coach, mentor becauseyou know how to do that better
than anyone.
Jeremy Julian (09:54):
I love that.
and so I'd love to, to walkthrough Brock, just what is the
state of brands that aren'tusing a tool like Savvy?
you talked about the history andagain, I go back to some of the
earlier video days where it wasa big DVR, it's in Iraq, it.
It's, single point.
You might be able to dial intoit over the internet and go
scroll through those things.
But it's not cloud enabled, it'snot event driven.
(10:16):
It's this big box that's there.
It's connected to theseproprietary cameras that, that,
have these proprietary lines.
That's historically what I'veseen.
And then I've got my home camerasystem, which is these wireless
devices that go all over thecloud.
Check my kids.
And what time did they get home?
Their curfew was this time I wasalready sleeping.
They should, your kids are youngenough that I got three
(10:36):
teenagers at home.
Dude, I, I gotta make sure thatthey're in bed when I get up at
five 30 in the morning and makesure that they got in during
curfew.
So I look at my wirelesscameras, but there's a big
diversions from what I seeoftentimes.
Inside the restaurant brands, isthat kind of still the state of
the majority of people, or are alot of people that you guys are
working with kind of at thatstate?
I'd love for you to talk throughprior to Savvy, what are you
(10:56):
seeing out there?
talk to our operators that aresitting here listening, going,
yes, this feels like me, and getcatch me up on the state of
where things are prior togetting to savvy.
Brock Weeks (11:05):
Yeah.
because it was typically just anexpense, right?
A liability expense, aninsurance policy.
It was pretty much okay, great,I'm just gonna go get a system
that records and that I can pullup and look at.
and the reality is, especiallyfrom the mid-market on down,
right brands, that's the statemost of'em are in, and they are
trying to solve that oneproblem.
(11:26):
And I would say that.
Jeremy Julian (11:27):
The slip and fall, the underage drinking,
the, these things.
that's what you said, and I justwant to, I wanna speak to that
operator that's out there thatthe only reason they use the
camera is not to make theirbusiness better, but it's to
make sure their insurancepolicy, if something were to
happen, they've got the footageto be able to do that.
is that what you're seeing outthere?
Brock Weeks (11:43):
A hundred percent.
And is that important?
Yes, it's very valuable, right?
It's one of the things.
But what we are seeing now thatai, I think it's pretty,
Ubiquitous across anyone's inthe industry.
It's here.
And the power of AI is like it'sreal.
There's a lot of refinement anda lot of learning how to use it,
and it's only gonna keep gettingbetter.
And at a rate that is justexponentially increasing, but
(12:07):
it's here.
when any new technology comesabout and we don't quite know
how to use it, we go to thedefault, easiest path, which is
the liability.
then the operators start to say,oh, great.
I know I can UI see the visionof how I can use video.
And what they instantly do is goto a product that solves an
existing problem that they have.
So it may be speed of service,right?
(12:29):
Either it's an iot device of aloop system, or they put in a
really customized camera systemto track drive through speed of
service or in retail locations,they do guest counts and
conversion.
And once again, really valuable.
But then they start to see allof these other different use
cases.
And so what we recommend tooperators, whether they work
with Savvy or anyone else, butit's how we approach the problem
(12:52):
is that this data set.
Has immense value to yourorganization and should no
longer be neglected.
And in order for this data setto provide value, there really
needs to be three things itneeds.
You need to get a really stablesystem that's gonna run for
years, right?
You're gonna get your ROIinvestment.
You probably don't want to gobuy a$20 system at Best Buy or
(13:15):
Sam's Club, that's consumergrade for a home'cause it's
gonna be used differently.
But really affordably, you cango get just a good, economical,
reliable system.
It's gonna last us seven to 10years.
Make sure that you're coveringthe areas that you would have
business use.
Case around, not liability,right?
Business use case.
And liability.
(13:36):
Come up with a brand standard,figure out exactly how you want
to do that because a sensor is ahundred bucks.
It's more expensive to havesomeone go set it up and when
they're there, they'll do itreally affordably.
If you're having to come backevery time, you're gonna cost a
yourself a lot of money.
And because they approach theproblem back to your question of
(13:56):
what we see to just solve aproduct, we see them have.
Between two to four differenttypes of cameras or sensors with
two to four different servers,all storing video data and all
processing and analyzing videodata for different points of the
business with differentfunctionality.
(14:19):
All of them need to be managedas a separate vendor, as a
separate piece of hardware, as aseparate portal, and the data is
stored separately and siloed andfragmented.
Jeremy Julian (14:28):
That sounds awful.
Sorry.
I'm like, you're not getting mumuch business value unless you
are just the person that's therisk manager or you're just
this, or you're just that.
If you're having to do that, I'msorry to cut you off, but it's
like that blows me away to thinkthat they would have that, but.
It's not uncommon for people tosolve, they've got a, they've
got a pain on their finger.
They're gonna solve the pain intheir finger.
They got a pain in their foot,they're gonna go to a different,
(14:49):
so I love that analogy'cause Ididn't realize that was, that it
was so disparate.
'cause you never are gonna havesomebody that's gonna have one
POSI mean, we work in the p osspace.
They're not gonna put a POS inthe drive-through, in a
different one at the frontcounter.
But it sounds like they're doingsimilar things.
They're gonna have one for theirdrive through.
They're gonna have one for theirfront counter.
They're gonna have one for theback walk-in.
that's insane to me.
But I'll let you keep goingbecause it's
Brock Weeks (15:08):
No, you're, it's back to the days, right?
Of the different iPads for allthe different third party
deliveries.
And it's no one, anyone couldjust look at that and say, this
is not a good idea.
Like so many fell points.
And if you're looking at itvideo, because it does answer
all of these questions well,even if the AI is as powerful as
could be.
It is only as powerful as thedata set it's applied against.
(15:30):
So if it's always only lookingat this fragmented
Jeremy Julian (15:32):
Yeah.
If it's only a pars parsed pieceof data, then it makes it really
tough to deal with
Brock Weeks (15:36):
Correct.
It's like when you go into abrand and the drive through's
humming because they'remeasuring the speed of service,
but you stand in the lobby for15 minutes going I got an ice
cream addiction.
Like I just want a frosty folks.
let's take
Jeremy Julian (15:46):
Yeah.
Yeah, exactly.
I'm gonna go get in my car andgo get it faster to sit back
down in the dining room.
Brock Weeks (15:52):
Yeah, because once again, if you only look at one
piece, you don't get theholistic view.
So that really is what we'reseeing, and it's happening at
small brands and it's happeningin large brands.
And so whether it's with Savvyor anyone, it's.
Look at this as a techno, a keypiece of your tech stack and a
key data point.
If what we've talked about, likeyou're like, yeah, I would love
(16:13):
to know those things in mybusiness.
Great.
The data needs to be aggregatedand you typically, you've seen
this in point of sale.
Where the hardware hasessentially become separated
from the software.
If you looked years ago, you hadto buy this whole package where
everything worked together.
It was very hardware focused.
Then cloud computing and all ofthat allowed the software to
(16:34):
separate from the hardware tonow most of the point of sale
vendors, their hardware is notproprietary.
It's right.
Then they may be interchangingdifferent hardware and different
software companies.
I think you need to take thesame approach because.
The most expensive part ofadopting any technology is
disrupting the store and havingto change it.
(16:54):
And if every two years you'rehaving to do like a rip and
replace disruption, it's gonnaget difficult.
So get a great hardware layer,centralize the data set, and
look at it as a, a piece of, atrue piece of the data stack and
as a dataset rather than aproduct.
And then you'll be in a reallygood position.
Jeremy Julian (17:12):
Yeah.
I love that, that thought.
So Brock, I'm gonna, twist itaround just a little bit.
You talked a little bit aboutwhere things started.
We talked a little bit about theevolution of, some of the
hardware stuff and just how mucheasier it's gotten to deploy.
Talk to me a little bit aboutkind of some of the big business
use cases you're seeing outsideof using AI to ask the questions
that you need.
Risk management, whereeverything started, but you're,
(17:33):
you talked about some thingsthat I think our listeners may
not have considered that you areseeing.
Drive business value to theirbusiness as they implement
savvy?
Is it speed of service?
Is it, guest satisfaction?
Is it staff member stuff?
I, you and I talked offline andI'd love for you to share two or
three examples of things thatyou see so few operators doing,
(17:54):
and then when they get it, itjust drives monumental results
inside of their business.
Brock Weeks (17:59):
Yeah.
we'll start with, that guestexperience.
We chose to take that as one ofthe first kind of key things we
wanted to tackle because as welooked at reviews of
restaurants.
Three quarters of all negativereviews reference the speed of
service, the interaction withthe employees.
Or cleanliness of therestaurant.
(18:20):
Those were like the key pillarcornerstones of most negative
reviews.
It wasn't actually the qualityof the food, it wasn't those
things.
and so we looked at and said,Hey, can video actually move the
lever here to improve thequality of the operator's lives
and answer these questions?
And the question, the answer wasyes.
So speed of service, not only,there's a couple different
brands where we've got the casestudies published on our
(18:41):
website.
That, before they were spendinganywhere from six to$15,000 a
store to install a differenttype of loop system to measure
the drive-through speed ofservice.
studies show those are in thehigh 70% accurate.
It's basically vehicle in,vehicle out, and if anything
gets off, it resets every 30minutes so that it can
recalibrate.
as everyone knows, reallyexpensive, only showed a part of
(19:04):
the journey.
and so employees, better orworse, when you start to measure
things, they start to try togame the system.
And we've all been there whereyou've been held up beginning to
the menu board to actuallyorder, because that's when the
timer's gonna start.
Or you've gone to pay and yourorder's not ready yet.
And they're like, yep, can youjust pull forward over to there?
And then you get forgot aboutand left.
(19:24):
You have to get outta your car.
Like we, we've all had theseexperiences.
And what we're saying is most ofthese brands have installed
cameras out there for theliability protection.
AI can now accurately andaffordably track the entire
guest experience, and you canactually segment it by just
drawing regions of interestdigitally on the camera and
(19:45):
start tracking not only theholistic view of when they enter
the lot and when they leave thelot.
But also the actual differentsteps within that process.
So you can start to reallyrefine where do I have
bottlenecks?
Because it's really justmanufacturing capacity and
throughput capacity.
And so when you start to provideyour team more insights and
(20:06):
visual data by measuring thesethings, and it's done in a way
that it cannot be gained, thefocus moves to actual process
improvement instead of crisismanagement historically.
Jeremy Julian (20:18):
Or I'm gonna get yelled at.
'cause I moved this car up andthen they got pissed and then
they gave me a bad review.
It's what caused me, what orderdid they place that caused our
kitchen to get backed up?
What is happening there?
And I love that you said that's,because that's.
That is, and again, historicallywith a time-based system, you'd
have to look through hours andhours of tape to figure out what
happened there.
Whereas now with some of thisadvent, it's Hey, what, I guess
(20:40):
I'd love that query, what isthat question that you can ask
the AI that says how manyorders?
I, just share it with us and Ipromise you, because you and I
talked prior, I hit the recordbutton.
Some of our listeners are gonnabe like, what?
You can do that today?
Brock Weeks (20:53):
Yeah, it's once again, measuring time and
segmenting it.
That's, once again, it's morejust giving you the baseline.
you can just hit a button and belike, show me the five longest
wait times, and then watch theentire process of that.
Jeremy Julian (21:06):
Yeah.
And people are gonna be blownaway, Hey, what, who's anybody
that's been over four minutes inthe drive through, six minutes
in the drive through, eightminutes in the drive through,
and you just look at that, it'snow I can see all of the videos
and it's Hey, on Tuesday we hada really crappy shift.
We on Wednesday we did great.
And so I, it's so much simplerthan people make it out to be
and I appreciate you sharingthat.
Brock Weeks (21:24):
And because you've centralized the data of your
business systems while you'rewatching that experience, you
have the transaction data.
So you know.
Was it just a really large orderthat threw us off?
Because that happens, right?
And you can't, or was it, Hey,we actually got the order wrong,
and so we were issuing a refund.
But while we were doing that, weheld up all these other guests.
Could we actually have moved?
(21:45):
That might be.
Jeremy Julian (21:46):
did we run outta stock between the time they
ordered it and the time that,that you had to fulfill the
order?
there's so many differentopportunities, but back to your
point, once they know where thedata problem is, they can
operationally go solve it,rather than being in crisis
management of, I'm gonna get introuble, or I'm not gonna hit my
bonus because my wait times aretoo
Brock Weeks (22:02):
Yeah.
'cause before it was just, oh,it's red and it's, they've been
here too long.
Ah, what do I do?
And that was all you werelooking at was the fire where
it's no, let's, and how do thesestages compare cross locations?
Because when you're looking atthat holistic view, you can
really start to go and coach andsay, Hey, is this a company-wide
process problem?
Is this just a store managerproblem and training problem?
(22:25):
Is this a shift lead problem?
It really allows you to getsuper.
Jeremy Julian (22:28):
Is this a menu mix problem for that store?
do they order too many saladsand they take too long to
produce out of this store versusburgers at another store?
Yeah, so many different waysthat would take hours and really
data analyst tools and peoplesitting there analyzing these
things.
What's another use case, Brock,that people are using this for,
that you think would blowpeople's minds to go.
(22:48):
How, how have we been doing thisso manually and now at our
fingertips in an aggregated way?
We can just knock it out prettyquickly.
Brock Weeks (22:55):
Yeah.
before diving into that, I wannamention do the same thing on get
measuring guest speed of servicein the store.
Why do we only care about acertain segment of the customer?
let's track so that we know ifthe drive through's home and an
in store is not, we want both.
the second.
Jeremy Julian (23:10):
It'd be interesting to actually ask that
question even on third party,because I see the third party
problem being a huge issue.
'cause so many brands weren'tdesigned with third party in
mind and they've got the regularguests and then they've got the
third party guests and theyoftentimes will screw up a guest
experience because I've got myDoorDash drivers waiting in the
same space.
sorry.
I'll let
Brock Weeks (23:27):
No, and you can track that now, right?
Because they typically arepicking up at different areas
and the AI is good enough.
Now it uses a Reid technologythat basically says, Hey, I'm
not gonna facial analyze Brock,but I'm gonna say he's in a
maroon shirt.
He's right this big.
He's the, he's got this colorhair, all these attributes.
And then I know what areas ofthe store he went into.
So I can say, Hey.
(23:48):
I've got all these DoorDashpeople just show me the people
that just followed this flow.
That's why we call it customerflow ai, this flow.
What was their experience andhow long were they in the
different areas?
'cause we have, it's, and Iempathize with these frontline
employees where you're in thereand I've got my family and I'm
trying to order in store.
No one else is in line, butthey're just back there humming
(24:09):
on third party delivery orders.
What I'm
Jeremy Julian (24:12):
And the DoorDash driver's sitting there with his
phone going, I need my order.
I need my order.
And you're like, you're tryingto get your kids to go through
the line ordering and it's a badguest experience for both sides,
right?
Brock Weeks (24:21):
So it's okay, now let's measure this.
Let's identify it, see exactlywhat the baselines, and now we
made a change.
How did it impact?
And the second piece, back toyour, what other technology?
we call it site check ai, buthistorically, when you had to.
Train ai.
It was really just a computervision model.
It wasn't ai, it was machinelearning.
And it was, I'm gonna train iton seeing a maroon shirt,'cause
(24:42):
that's your uniform.
So I'm gonna train this data setand it's gonna get really good
at looking at maroon shirts.
now AI is just getting to whereit looks at an image and says,
Hey, I've been trained on all ofthese large models.
What is it you want me to pickout?
And so you think about thethings that a secret shopper or
a district manager does whenthey're in the store from a
cleanliness standpoint.
(25:02):
Is table turn happening?
Is the floor is being cleaned?
Have we put out the floor matsfrom a safety standpoint?
Are the employees wearing theiruniform are personal self
Jeremy Julian (25:10):
line checks?
Are they making sure thatthey're doing the temp checks?
All of those kind of things.
Brock Weeks (25:14):
the two stopped?
Jeremy Julian (25:15):
many things that continue to happen.
Sorry.
Brock Weeks (25:17):
No, you're on the, do you just start to go.
Wow, there's a lot there.
And though it's gonna continueto even get better right now,
think about it, if I visuallycould stand there from the angle
of the camera and look at itlike, is it gonna be able to
read the serial number off of adollar bill?
No.
But is it gonna be able to tellyou like, Hey, you got a bunch
of tables that are sitting therewith trash on there and no guest
(25:39):
and they've been sitting thereforever.
Yeah.
Spills, employee uniform,personal cell phone device,
safety issues like boxes,covering entrances, things of
that nature.
But it's gonna happen all day atright at intervals of time
because the affordability's notquite there to run it.
24 hours a day yet, but you cansay, Hey, every 20 minutes at
periodic times, run these checksand just give me a compliance
(26:03):
score and then quickly show mewhere I'm at compliance.
So I can look and say, you knowwhat?
I'm at 97%, I'm good.
No one's perfect.
Or, Hey, I'm at 70%.
Why?
And it will quickly take youright to that point in time
where you just hover over thered mark and it's here's the
image in the video of whathappened.
So you're not saying once again,oh, why am I having this
(26:23):
compliance?
It's, oh, look what's happening.
And the reason why we focused onthose two key products and
there's more coming.
It was when they started to lookat the customer speed of
service.
The customer flow started toincrease, meaning they weren't
getting as many people through.
They were decreasing theirthroughput.
There was other problems goingon in the restaurant.
Jeremy Julian (26:45):
Yep.
Brock Weeks (26:45):
and so they're correlated together.
And so if you can affect, onceagain, those are two of the core
pillar things that affectnegative reviews at its core.
It now allows you, when you'rein the store to not spend time
researching, but spend timecoaching and mentoring.
Jeremy Julian (27:01):
Yeah.
those two use cases areincredible and I love that you
chatted through, through thatthe power of the software is a
pretty big piece, I guess Brock,'cause you can go to Costco, you
can go to Best Buy and go buycameras.
you talked about.
I guess I'd love for you to talkto our listeners about those
people that think they have itall figured out.
'cause they've, gone and boughtthem at Best Buy and they're
(27:21):
sitting on their couch at night,while their wife's watching The
Bachelorette, reading through,watching through all of these
videos on their phone.
But really at the end of theday, that's a huge waste of
time.
'cause now software's sitting ontop of these things.
For those people that kind ofwent super consumer what.
where are the opportunities andwhat is the delta even in the
price of the hardware and thesoftware to get to something
that's more professional gradeand more commercial grade, to be
(27:43):
able to do what it is that theyneed to do and save them so much
time and so much
Brock Weeks (27:47):
Yeah, it's so much closer than it used to be.
I do need to point out Savvy'scompletely hardware agnostic.
To deploy our system, you plugin a little device smaller than
my cell phone, and that's it.
It just compresses and encryptsthe data and sends it to the
cloud.
Jeremy Julian (28:02):
So you can use any IP camera.
Brock Weeks (28:03):
Any IP camera, we don't care what the cameras, as
long as it's commercial grade.
Back to that.
In order for our analytics torun the camera needs to be
continuing to run the deltabetween a consumer grade camera
and a commercial grade camera isprobably less than 20% now, like
it's
Jeremy Julian (28:20):
Percent.
Brock Weeks (28:21):
hundred percent.
It's so close.
Like fantastic brands like AWAand Access and Vivo, taking the,
they're building phenomenalcameras at really affordable
prices, especially for thisindustry.
Where you can go and do that,and there's so many, great
resources out there and MSPs andintegrators that are offering
these at really affordablerates.
The key thing becomes is, what'sthe, what does the technology
(28:44):
need to do, which is it needs tocapture the image so it needs
good light management and goodresolution.
Do.
Do you need eight K at arestaurant?
Looking at a lobby?
No.
Go get just a good camera thathas good light management and is
gonna last and is reliable onceyou're there, we say like the
magic should happen in thesoftware because it's gonna
(29:04):
change.
Technology's gonna advance.
Just if I had, I have an iPhonehere.
I wanted to use AppleIntelligence, but I didn't.
I had the 14 pro, and so it, itwasn't capable on my hardware.
If you approach everything,there's certain things that
hardware and software should be100% married together, but if
you do that, you limit theecosystem that you can play in.
(29:27):
The power of what I do with myiPhone is, yes, it's enabled by
the processing power, but it isthe creativity that has been
unlocked from the App Store thatI can then download and use from
a software standpoint.
And so our recommendation isfind open systems.
You should, if savvy was notperformant, you shouldn't be
(29:47):
locked to me and be outthousands and thousands of
dollars.
You should be able to pivot asan organization fairly quickly
and so good.
Jeremy Julian (29:56):
So I am wholeheartedly agree.
We talk about the freedom ofchoice all the time at CBS and
it's just, it's so critical.
'cause again, it puts the onus,onus on us to do it right.
And like you, it sounds likeyou're leading the team in that
way.
Brock, for those that aresitting here going, you know
what?
I need this now.
What does it even look like?
Can you use existing systems andlayer this stuff on?
Do they need to go run cables toeverywhere that they need these
(30:19):
things?
Can you start small and grow, Iguess help walk through what it
would look like if people aresitting there going, I need this
in my life.
I haven't had this.
How do I get there?
Brock Weeks (30:28):
Yeah, Where you have 10 stores, a hundred stores
really look at it and say, okay,we do a virtual site audit,
which is looking at the, whatthe current camera models are
and what the angles of view are.
Are they just, do they need tobe repositioned?
Are they in the right spot or dothey need to be added?
From there, we literally dropship our device.
(30:49):
You plug it in on the network,it needs to be on the same VLAN
as the camera sensors, and ifit's integrated to the security
sensors and other things, needsto be on that same vlan.
N it encrypts, sends the data toour cloud, goes and says, Hey,
you need to give me thecredentials.
I'm in charge now.
Send the data.
And then right through most ofthe forward thinking point of
sale systems and great ones outthere like you all as well.
(31:10):
It's just a backend APIintegration.
You hit the button, the datastarts flowing, you map the
cameras.
And honestly from saying, Iwould love to do this, if
everything's in good shape andthe hardware works there, you're
up and running in a coupleweeks.
Like the actual time on site isanywhere from 10 minutes to, two
hours if they need to adjustangles of cameras.
(31:30):
And most of that's just climbingup and down a ladder and looking
at the angle adjustment, right?
Jeremy Julian (31:35):
Yeah.
two things real quick there.
You, we didn't really, dig deepinto kind of the other
technologies that are in thestore and integrating those.
You alluded to point of sale, isthat your guys's primary, I
guess talk through the use caseon why would you integrate with
point of sale, and what doesthat do for you?
Brock Weeks (31:50):
Yeah.
Point of sale labor systems area really important one, so you
can understand like that ratioof speed of service to labor.
unfortunately employee timetheft does exist, and so you
wanna be able to audit and havethe system run and verify those
checks, the alarm sensors andsystems smart safes.
Think about what are the keypieces of technology.
(32:11):
That something's happening andinteracting with that, I would
want to know.
Why I got that result, right?
Discrepancy in cash deposit,something rang up at the
transaction and the way weintegrate it there is it's
actually we put it all in thecloud and flatten it out so you
can search your video data byit.
So whether it's a lossprevention use case of saying,
(32:34):
show me every time that a cashrefund was done that a guest
wasn't present, right?
That's build an audit workflow,the exception based workflow, it
just throws it in a quick digestfor you.
You click through it in a fewseconds and answer the
questions.
But your product team, and menuteam, they might wanna look
through and be like, Hey, showme who's buying this item,
(32:54):
right?
Or, show me when there's acustomer complaint comp, or
Jeremy Julian (32:58):
Yeah, gimme every transaction that was over 150
bucks.
'cause did we go out and do atable touch when it was a high
value customer?
whatever.
Brock Weeks (33:05):
All of those things, there's questions around
it.
Really, it's just allowing youto get to that point in time
with the context.
'cause when you're watching, youwanna have full context, so with
the full context so that you canactually look at it.
Diagnose the problem and then gotake action.
That's how it exists today.
Where I see it going, Jeremy, iswhat gets really exciting.
(33:26):
I don't think in a few yearspeople are really gonna look at
video.
What's gonna happen is you'regonna have these AI agents,
right now we're doing this, thestructure, all the data
together, aggregate it, sochecks Abby's doing that.
Second, we're applying specificmodels to specific use cases.
Speed of service, guestexperience.
That's site check.
That's almost like a filteringlayer and the integrations to
(33:48):
the sensors and all that arefiltering layers.
But when this happened and I sawa discrepancy, then an agent
goes and watches the video,analyzes it and says, no, you're
good.
This was right.
Or No, this was potentially bad.
Surfaces it into, here's yourchecklist of action items you
need to take.
If you wanna click on the link,it's gonna take the same way
that AI works right now.
Jeremy Julian (34:07):
You would now, but it, but you know what,
you'll have peace of mind thatsays, you know what, I put my 40
or 50 or 60 use cases in thereand it's really only delivering
me the two or three.
That might be a problem that arecoaching opportunities or
whatever else I.
Brock Weeks (34:19):
Yeah, those high impact things that you want it
to be doing, and it's right, itdoesn't replace anyone.
What it does is amplify people.
To spend less time doing themundane and more time connecting
with their teams and connectingwith, Those people that they
want to coach, that they wannamentor, that they, From a loss
prevention standpoint was justhaving lunch yesterday with a
(34:39):
franchisee who, once again, whyI love the hospitality industry.
He was just all about hispeople.
He's got 60, almost 60 stores,right?
And he's just all about the teamand how he helps, and we were
talking about loss preventionand he was like, yeah, I used to
look at it as big brother.
Like I don't wanna be that.
And, but he's I've had the.
times over my career wherepeople have stolen significant
amounts and we've had toprosecute and why did, what if
(35:00):
you caught that person the veryfirst time they did it and just
said, Hey, this is a pro.
Like you can't do this.
This is theft.
'cause a lot of times it doesn'tstart out that way.
It's just some innocentdiscounts, some innocent gifts,
some friends, some things catch'em that time instead of having
to prosecute and end up withsomething on their record and
really disrupt their lives.
It's all of these different usecases, which is really just.
(35:21):
Highlight good behaviors,replicate those, coach on them,
and find those correctivebehaviors so that you can
address them.
Jeremy Julian (35:30):
I love that you went there'cause that was my
next line of questioning is whatdo you say to those people that
are like, I don't need BigBrother, I don't need all of
this stuff.
I don't, all of the privacythings.
I guess it sounds like you guyshave already it ultimately again
goes back to how do I make mybusiness better?
How do I make my team better?
How do I make my customerexperience better?
Is really where you guys are fofocusing so much of your time
and energy in the tools that youguys are building.
(35:52):
Is that, is that correct?
Brock Weeks (35:53):
A hundred percent.
that's where the impact is at.
If I, simple analogy in my life,my big brother definitely hasn't
been there to point out and,crack this, the whip at me, he's
been there to correct me on,Hey, you might be getting a
little off here.
I'm seeing this right?
let's bring you back.
that's truly what it should beused for in our.
Jeremy Julian (36:10):
Love it.
so Brock, how do people learnmore?
How do people get, you talkedabout, from time to, to even
knowing what we're doing togetting up and running it, it
can be done in as little as acouple of weeks.
So how would they learn more?
How would they get in touch?
How would they move forward?
because again, I.
I look at what you guys aredoing and I'm just, I was blown
away.
I was so excited when you sharedit with me.
I was like running around I waslike a little kid, on Christmas
(36:30):
morning.
Super excited about all of wherethings have gone because my
history really goes back to someof the old days when I last
looked at this tech.
And so it's amazing how far it'scome.
for our listeners out there thatare excited and wanna learn
more, how do they do that?
Brock Weeks (36:43):
Yeah, we're, I'm personally active on LinkedIn.
Would love to, chat with you andintroduce you to some members of
our team who can even, dive indeeper with you.
get savvy.com and it's SAVI, isour website.
We'll also post a link, in herethat has a specific one for
this, this show.
And then at the differentconferences, we're gonna be at
QSR, evolution, the Fast CasualExecutive Conference, FS Tech,
(37:05):
and a bunch of others coming uphere this fall.
Would love to chance to interactwith you all.
Jeremy Julian (37:10):
Awesome.
Brock, I genuinely, I was blownaway with some of the stuff that
you shared with me just in in abrief demo.
And so I think, and I say thisto listeners all the time, if
you're not doing it, guess whois your neighbor that's beaten
you to your left and yourneighbor that's beaten you to
your right is using thistechnology as a business driver
to change the conversation.
(37:30):
And so I would really encourageall of you guys to go check out,
get Savvy.
check out Brock's stuff.
they do an amazing job ofhelping you learn how to get to
this place.
And so thank you for taking thetime, Brock, to share.
To our listeners, guys, we knowthat you guys got lots of
choices, so thanks for hangingout.
If you haven't alreadysubscribed, please do so on your
favorite podcast, tool and orYouTube and make it a great day.
Brock Weeks (37:50):
Awesome.
Thanks Jeremy.
Speaker 2 (37:53):
Thanks for listening to The Restaurant Technology
Guys podcast.
Visit restaurant technologyguys.com for tips, industry
insights, and more to help yourun your restaurant better.
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