August 21, 2024 • 48 mins
In this episode, Steve interviews Fred Voccola, CEO of Kaseya, discussing the growth and strategy behind Kaseya's numerous acquisitions and the development of their ITComplete platform. Fred elaborates on Kaseya's mission to improve MSP (Managed Service Providers) profitability and efficiency using integrated platforms and AI-driven automation tools like Cooper Insights and Cooper Bots.
The conversation also touches on common concerns from MSPs regarding acquisitions, billing issues, and the rationale behind the Kaseya Center arena. Fred emphasizes the importance of building brand recognition and supporting customer needs while safeguarding data through stringent cybersecurity measures. The episode concludes with a teaser for an upcoming major announcement at DattoCon and a nod to a friendly rivalry.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Steve (00:00):
So, Fred, welcome.
Fred (00:01):
Thanks, Steve.
Great to be here.
Steve (00:03):
I'm glad to have you here, man.
So, uh, this has been somethingthat I've been wanting to do
for about a year, if not longer.
So, I'm honestly, I'm really excitedthat I get to do this with you today.
So, so truly, thank you for comingon and letting me interview you.
Fred (00:20):
Well, like I said, thanks for having me.
We're super pumped to be here,and this should be a lot of fun.
Steve (00:24):
Good.
So, uh, you know, this is a show for MSPs.
So, if, if you, listener, haven't heard ofKaseya by now, I don't, I don't know what
to tell you, because Kaseya is huge, and,and you should know who they are by now.
They probably own at least oneof the tools you're working with.
Um, Fred, I, I gotta ask, uh, what, whatis your strategy when it comes to like,
(00:53):
uh, thinking about new acquisitions?
Because I, I know you guys, youguys acquire a lot of things and
there's, there's probably things thatyou guys have acquired that people
don't know you've acquired too.
Fred (01:06):
Yeah, there's some of those.
Um, so maybe, Steve, the wayI can address it is I'll talk
about what our strategy is.
Because acquisitions are part of it.
But the question is why, andthe problems we're solving.
So it's actually pretty fun.
And it's, it's, it's been, uh, forme personally, it's been 10 years
since I've been in the industrynow, it's been awesome, man.
(01:27):
I, I've loved the lastdecade in this industry.
In the MSP industry.
So about 11 years ago, ormaybe 10 and a half years ago.
We started looking at, uh, at Kaseyaand what we saw in looking at Kaseya
was the opportunity to build aplatform that could fundamentally
(01:50):
change the MSP industry forever.
That's a bold statement and maybea crazy kind of statement to make,
but we thought we could do itby changing the unit economics.
of the MSP industry in favor of the MSP.
(02:11):
And by doing that, just free up awhole world of possibilities for MSPs.
So let me tell you what I mean by that,and then where acquisitions fit into it.
So, Kaseya's purpose, we build a platform.
Our platform is called ITComplete.
(02:31):
ITComplete contains all of thefunctionality That an MSP needs to
deliver all of the managed servicesthat their customers require, as
well as all of the internal systems,like PSA and IT documentation and
things, for the MSP to effectivelyand efficiently run their business.
(02:55):
We provide all that in oneplatform, one screen, if you will,
or one series of integrations.
And by providing it all in one place,a couple of interesting things happen.
Because Kaseya owns all of the differentplatforms, Are all the different pieces
of software it allows us to integratethem in a very meaningful way and
(03:22):
allows us to build them as one product.
And why that's important is whenmultiple technologies that are
required to do a given task, when theyare deeply integrated, is when that
process or that task can be automated.
(03:44):
And as you know, Steve,automation is the name of the game
Steve (03:47):
Mm hmm.
Fred (03:49):
It allows engineers to do more and it allows fewer mistakes.
Now, add on top of that, thepower that AI bring, both large
language model AI or machinelearning type AI, As well as GenAI.
So when we apply the AI capabilitiesto a fully integrated platform,
(04:17):
the ability for that platform toautomate upwards of 50 percent of
what an MSP has to do is tremendous.
And what that does foran MSP is astronomical.
An MSP can automate even a third,if not half, of the tasks that
(04:38):
their engineers do on a daily basis.
That MSP is substantially more profitable,effective, and makes fewer mistakes.
Now, when we talk about what our journeyis, Kaseya's journey, like I mentioned,
is to change the unit economics ofthis industry in favor of the MSP.
(05:04):
So, Steve, here's a couple of statistics.
When you think about most MSPs,most MSPs are serving companies
of 100 employees or less.
So, if an MSP has 70 customers, maybe twoor three are co managed customers where
they have 1, 000 or 2, 000 employees,but the majority of their customers
(05:28):
have between 25 and 100 employees.
Architecture firms, doctors offices,dental practices, et cetera, law firms.
Now, the business service providers.
That are providing outsourcedservices to the customers of MSPs
are predominantly law firms, as wellas like tax and financial people.
(05:55):
Profit margins of law firmsrun in the 30 percent range.
The profit margins of financial and taxfolks run in about the 30 percent range.
Did you know the average MSP inthe Western world has an average
profit margin of just under 10%?
10%.
Steve (06:15):
I didn't realize it was that low.
I thought it was probablyin the 15 percent range, but
that doesn't surprise me.
Fred (06:21):
Yeah, the ranges are all over, but the average, and we have about
54, 000 MSP partners and customers,call it 10 percent shade under.
And if you think about what the MSPsdo, number one, it's much harder.
See, in the last seven, eightyears, Most of these small to mid
(06:43):
sized businesses, they've digitallytransformed, or the business and
industrial systems and applicationsthat they use drive their business.
So if their systems aren't alwaysavailable and always secure,
they're, they're not functioning.
So the job of an MSP isexponentially more important and
(07:09):
more valuable to their clients.
Then the law firms and thetax prep firms that are making
three times the profit margin.
On top of that, if we look at society,I've seen data that tells us that upwards
of 70 percent of new job growth, ofeconomic job growth is happening from
(07:32):
small to mid sized businesses, right?
New hires, opportunities, et cetera.
Particularly in at risk areas, we'veseen small companies just, just the
business of small companies exploding.
And these small to mid sized businessesare able to compete because of advances in
(07:53):
business systems and industrial systems.
And keeping those systems alwaysavailable and always secure is keeping
the most important, high growth,and soon to be largest businesses.
Part of our economic enginerunning, and that's what MSPs do.
And MSPs are making one thirdthe profit margin of the other
(08:17):
business service providers.
So at Kaseya, we constructedthis platform that provides all
the functionality in one place.
We automate it throughintegration and tremendous AI.
So these engineers, these MSPengineers can be much more efficient.
And we charge one third as much as whatthe MSP would pay if they bought nine
(08:43):
products from nine different vendors.
So we believe by doing that, we've,we have literally put the foundation
in place to change the uniteconomics for the entire industry.
And now MSPs are receiving thefinancial rewards, you know,
25 30 percent profit margin.
(09:05):
for listening.
that they should.
Quite frankly, they should be highergiven the value that they provide,
but MSPs struggle a little bit, andour industry struggles a little bit,
because a lot of the customers of MSPs,they don't necessarily understand all
the risks of cybersecurity threatsand the importance and the costs
of making sure they're available.
(09:26):
So that's our strategy, and as we'veconstructed ITComplete, we've made 17
acquisitions over the last 11 years.
We spent over 12 billion buying thesecompanies and, you know, the thousands
of engineers we have that are integratingthem and building it into one platform.
(09:48):
Our platform must be complete becauseif our platform's not complete.
We have a tough time delivering on thepromise of everything in one place.
So that's our strategy andthat's, you know, Steve, that's,
that's how M& A fits into it.
And again, our mission is MSPspowered by Kaseya should have profit
margins three times the industry sothey can invest in their business.
(10:12):
To better deliver for their customersand to, quite frankly, make the
money that they deserve to make.
Steve (10:19):
I really like that.
You know, you mentioned that mostof your customers, and you said,
I think you said you've got 54,000 MSPs you're working with?
That's a whole lot of MSPs.
Of the 54, 000, do you, off the topof your head, happen to know, um,
how many of those MSPs are generatingless than 250, 000 of annual revenue?
Fred (10:45):
Annual revenue?
I'd say probably 10 of themare two employees or less.
So, we measure by numberof employees, Steve.
Steve (10:56):
Sure,
Fred (10:57):
I would assume that number there's also quite a few MSPs,
That aren't, you know, we haveMSPs as large as Thrive Networks.
You know, they're abillion dollar business.
We have MSPs as small asSteve's part time gig, right?
Where, you know, you, you, you haveyour day job and you manage your
buddy's dental practice and yourbuddy's law firm at night, and you
(11:19):
make an extra five or 10, 000 a month,which is great money, uh, doing that.
So we have all sorts, but I believe.
The number of two or lessis right around 10, 000.
Steve (11:32):
And, So, so that's a fifth, if not a quarter of your customer
Fred (11:40):
Yeah, about a fifth.
Steve (11:41):
So, I, I would argue that, um, five or fewer is probably
half of your customer base.
Uh, and, and that's just based onthe, the information that I've,
I've gathered over the years, uh,understanding the MSP industry.
(12:02):
So, one of, one of the questions I haveis when, when you make these acquisitions,
Traditionally, there's been a lot offrustration I've seen on the forums and
I, I, I haven't run an MSP for a fewyears, so I don't have any skin in
the game, Fred, but there's been a lotof frustration in the forums because
(12:24):
it seems like you guys have, uh, kindof your, your play where, um, you
know, you, you acquire a company, youchange everything to be three year
contracts, you raise the prices, yougot the, the, um, The dev team, and
then the product becomes stagnant.
That's, that's the frustration that I hearfrom the, the people who want to be loud.
(12:49):
So what would you say to those people?
Fred (12:52):
I mean, I'd say I Thank you for the feedback, you know, like
it's, feedback is a gift, man.
And even if you don't like it, youtake it and you try to learn from it.
We, when we bought Datto, we,we, we heard a lot of that.
And one of the things that we did,and it's still published, is we
published, we called it Just the Facts.
(13:15):
And we published the investment in R& D.
of every single acquisition that we'vedone, you know, right before we bought
them and then after we bought them.
You know, IDAgent, RapidFireTools,ITGlue, RocketCyber, Graphis,
you know, you name them.
And the numbers are pretty staggering.
(13:37):
And I think the average was we doubledthe R& D team within six months.
Every single acquisition thatwe've done, Steve, every.
Not like all but one,you know what I mean?
Like an absolute every we'velowered the price when we
bought the company, everyone.
So the idea that we raise pricesis simply not factually true.
(14:02):
Everyone, even data, every single one.
And it's, again, it's all, we'veall made all this information public
and the team can share it with you.
It's on the websites and everywhere.
Steve (14:12):
But by lowering, are you lowering the prices, but extending
the, the length of the agreement?
Fred (14:19):
um, we always offer one and three year agreements for
every product that we sell.
The three year agreements are thebest price by far, but even on the
one year agreements, the pricesare lower than when we bought them.
Steve (14:33):
Do you, do you ever offer month to month terms for people that, And obviously
that would be at a, at a premium, right?
But do you ever offer monthto month terms for people that
just don't want a contract?
Fred (14:44):
we offer month to month terms in one case, and that case is when people
are coming off of, so if someone buys aBCDR appliance, like a DattoBox, right,
um, say it's a, they sign up for a one ora three year agreement for that DattoBox
and that contract ends, they have theoption of extending that DattoBox month
(15:04):
to month, one year or a three year option.
No, we do not offer as a standard part of.
New business other than the DattoBCDR business month to month degree.
Steve (15:14):
Okay.
Um, so, so you mentionedthe Datto acquisition.
Um, I feel like you've probably learneda lot over, over the years with all
these acquisitions that Kaseya's made.
Um, the, the biggest thing that, youknow, people complained about with the
(15:35):
Datto acquisition was the billing issues.
And If we look at, again, a fifth toa quarter of your, your customer base
is two people or fewer, um, billingissues really hurt, you know what
I mean, like, when, when it's, whenit's a multi billion dollar company
like yours, you know, if, if somebodyaccidentally accidentally, Bills you
(15:58):
five times what they're supposed to.
Usually for you, that's just a roundingerror until the bill gets corrected.
But for these smaller MSPs,um, these invoices can be
just, they can destroy a business,especially if, if you guys start
shutting off services because theinvoice isn't paid, even though,
(16:21):
even though the invoice was wrong.
So.
What, what did you learn, uh, from,from the integration of Datto and
from, from all of the billing issuesthat you've, uh, overcome, and, and
how are you going to deploy that, uh,learning into your next acquisition?
Fred (16:44):
Yeah.
So Datto was a so thelearnings I could write a book.
Literally, I could write a book.
And I mean that like not in a funnyway, but in a real way, because
I think it could help a lot ofpeople maybe not make some of the
mistakes that I made or that we made.
Um, so a little background.
Datto, as you know, and mostof your listeners probably
know, is a public company.
(17:04):
Um, and they were our biggest competitor.
So, you know, we acquired them.
And it's not a secret that themanagement team of Datto I wasn't
overly enthusiastic about beinginquired by one of their competitors.
So it made for a, ainteresting cultural time.
Um, which, which is notuncommon in acquisitions.
(17:28):
Now many of the acquisitions thatwe made prior weren't competitive.
You know, it was, theyweren't competitive.
Dato, um, there were a couple ofareas that we competed with them.
I think, looking back at the acquisition,uh, it's, it's been a financial success.
We've made a lot of bumps.
I think when you look at a hundredacquisitions of that size, scope, and
(17:51):
complexity, we're probably in the, youknow, the, now that we're two, believe it
or not, we're over two years past that.
Can you believe that?
It's crazy.
Uh, we're, we're 4%.
of, like, success in allthe ways you measure it.
Customer retention, customersatisfaction, revenue, profit, all the
different ways that that gets measured.
(18:12):
But the direct answer to your question,the first part of your question, is on
the billing side, and we made mistakes.
There's no way around it, and,and, to your point directly, If
I'm a two part, I mean, I've, I'vestarted four companies myself.
I'm an entrepreneur who typicallystarted companies without venture
(18:33):
money and mommy and daddy's money.
It was always, you know, doing it myselfand I've been in situations where I've
struggled to make payroll early on.
You're a two person MSP, you get abill from a vendor, and that bill's
wrong, and it's wrong by a lot.
You know, the bill's not getting resolvedfor various reasons, and you're worried
(18:57):
about having disruption of service, andwhat does that mean to your customers?
These are serious things.
These are very seriousthings for the customers.
One of the decisions that we took atDatto or Kaseya during this process was
relatively early on during the billingchallenges, we decided to take our foot
(19:22):
off the gas in terms of collections.
You know, so if our system tells usthat Steve's MSP owes us 25, 000.
And Steve says he owes us 5, 000.
In normal times, Stevewould pay us 5, 000.
We would, you know, causeSteve believes he owes 5, 000.
(19:42):
And we would keep the systems onand we'd work to settle what is,
let's, let's dig into and lookat the remaining 20, 000, right?
That's, that's how mostbusinesses operate.
Steve (19:52):
Mm
Fred (19:52):
Um, and we took the approach for a while where we would even say, you know
what, Steve has an issue, it's 25, 000.
Don't pay us anything.
Let's go and figure out what it is.
To error on that side.
And I think it took us a good five monthsto work through all of the challenges.
(20:13):
You know, we're through it now.
I think we have, I have the data,the data won't mean anything to your
listeners, all the KPIs that we track,but we're back to levels that are
better than the pre data acquisition.
And it's the kind of place,the kind of thing where.
If you mess up one customer or onepartner, that's like one too many.
(20:34):
You don't want to mess anyone up.
You know, we've, we've done a fairlygood job of trying to put customer first.
Now there's people that take advantageof situations like that, things like
that happen, but I think the lessonthat we learned was over communication
(20:54):
is better, and sometimes overcommunication about hard realities that
partners may not like is better than
trying to deliver something thatmay be impossible in a time frame.
But it's, it's, it was definitely notlost on Kaseya about the challenges that
(21:18):
that poses, especially on the small.
Smaller MSPs and we've adjusted.
I mean, even today, we'vemade a lot of adjustments.
We're past the problems, but we madea lot of adjustments today where MSPs
of, of certain complexity or, or,or sophistication, you know, like if
you're a two person MSP, you don't havea dedicated account payable person.
(21:39):
You just don't, right?
I mean, that's the reality.
So, the engineer who's supporting theirseven clients and their, you know, 200
endpoints has to deal with a bill andan invoice and it's a pain in the butt
and maybe the partner's on vacationand it gets, that's real life and we're
attuned to it and we're spending a lotof time and a lot of money to streamline
(22:00):
as many processes as we can and provideautomation for as much as we can in
that like commercial interaction space.
You know, it's, it's, uh, like a lotof things, like our, like our security
incident we had three, four years ago,you learn a lot and you just do your best
to apply them, try to be transparent andbe better every day if we can be better.
(22:22):
And I, I still believe, actually, Ibelieve now more than ever, especially
with the release of Kaseya 365.
Our customers, our partners, we usethe word partner and customer kind
of interchangeably, our partnersare more profitable than the
majority, than the MSPs that arenot our partners in the industry.
(22:43):
And that's what we're shooting for.
Steve (22:46):
Okay, I, I respect that answer.
Um, earlier you mentioned AI, uh,in passing, and I know, um, AI is
one of the topics that was, wasfloated as, as something that you
wanted to talk about, so I suspect
Fred (23:04):
That's what I wanted to talk about.
Steve (23:07):
your, your PR team, when, when you reached out, so AI was one of those
topics that was floated, and that leads meto believe that Kaseya is going to start
ramping up, uh, discussion, mention of,of AI, machine learning, large language
models, et cetera, uh, within its product.
(23:27):
I'm, I'm seeing a lot of companiesstarting to talk about AI.
Uh, how, how their platformshave AI and machine learning.
And I, I think, I think MSPs are startingto feel, uh, burnt out already on AI
Fred (23:46):
It's like cloud was in the past, right?
Well, here's cloud,cloud, cloud, and yeah.
Steve (23:50):
Yeah, because, because everyone, you know, every, it's like a buzzword.
I mean, you know, if I, if Ihear somebody talk about the, the
synergies in AI, I'm, I'm You wantto go postal somewhere, right?
So, um,
Fred (24:02):
from Miami.
Steve (24:03):
yeah,
it's everywhere, man.
It's everywhere.
So, so all that to say, I, I'm of themindset that, um, AI can be good, can
be useful, but a perfect example of, ofwhere it can go really wrong really quick.
I just saw, uh, a Proof of concept wheresomebody was using Microsoft Copilot
(24:30):
and the person not authenticated to thespace was able to ask the AI chatbot
about, um, uh, downsizing and what,what employees are going to be affected.
And it just started answering.
So that obviously.
(24:50):
is, is a, you know, data governanceissue for that particular proof of
Fred (24:55):
Yeah.
Yeah.
Steve (24:56):
So, gosh, I got one of these little flies bugging me.
Um, so, all that to say, I, Isuspect Kaseya is going to get into
the AI game soon, if not already.
What are you guys going to do to putup guardrails to protect customer
(25:18):
A from seeing customer B's data?
Fred (25:26):
And what was the second part?
Steve (25:29):
Um, Well, let's, let's start there.
What, what are you guys gonnado to, to protect customer
A from seeing customer B'S
Fred (25:36):
Yeah, so let me start by talking about our AI and I'm
going to show you something.
I don't know if you can see this.
See that little guy there, thatdog on the back of my phone?
Steve (25:45):
Yeah.
Fred (25:46):
That's Cooper.
Cooper is my dog.
He's in a boxing outfit there.
I can see it.
And Cooper is our AI engine.
So it's the Cooper Intelligence,Cooper Artificial Intelligence Engine.
We launched Cooper three years ago.
So we've been in this game for a while.
Not that that's good or bad.
(26:07):
'cause I agree with you.
I think AI is a great word.
A lot of companies put AI in their,in their corporate summary, and they
get a 10% increase in their valuationjust because the words AI are in there.
You know, it's, it's, it's crazier.
You go to a party andyou say, what do you do?
I work in ai.
Everyone thinks you're smart.
Um, so our approach to AI is very simple.
(26:29):
So let's look at the fundamentals of ai.
There's two types of ai.
Gen and, and, and, uh, languagemodel or, or, or machine learning.
Let's break it into those two.
So the most common for productivity usagein sophisticated workflows isn't Gen AI.
It's really language models andprocessing and, and the, um,
(26:54):
machine learning type of AI.
So machine learning and the models that,that are associated with it are all
dependent upon how good and voluminousthe data sources are that can be analyzed.
So, if you think about Kaseya, we haveabout, let's make the math easy and
say 50, 000 MSPs to round the math.
(27:16):
And say the average MSP has20 employees or 20 engineers.
Some have 1, 000, some have 1.
So let's say 20 is the average.
That means I believe there'sabout a million employees.
We have a million engineers usingour products, MSP, a million MSPs
using our platform every day.
So, we get a tremendous amount ofdata, denormalized data, non uniquely
(27:43):
identified data, so we're not trackingwhat Bill Smith does, we're tracking
what MSPs do in aggregate, right?
And looking at what theydo, how they use technology.
How many keystrokes do they do for this?
What, what workflows are they doingto accomplish a particular objective?
How do they respond to particularinstances or other types
(28:07):
of things that take place?
We have all that data in our model.
Inside of cooper.
So that data allows us to really model outwhat MSPs are doing, what they're not, how
effective they are, how to make them moreeffective, what steps can be done, what
(28:27):
pieces can be built, how to leverage that
huge source of information.
We also have Upwards of 50 millionendpoints that we're managing.
I don't know how many hundredsof petabytes that we're managing.
We do millions of compliance scansa month, millions of security scans,
hundreds of millions of documentation.
(28:48):
So much stuff, so much data that we have.
And we plug that in and we builttwo applications out of that.
Two tools, because I believeAI, we believe AI is a tool.
Very, it can be an effective tool.
To help people be more productive andfrom a machine learning piece, the
(29:09):
two, the first two applications webuilt, one we released about three
years ago was called Cooper Insights.
All this is available in ourplatform and has been for years.
What Cooper Insights is,is Cooper is watching you.
Let's say you're using our RMM product.
Cooper is watching you.
(29:30):
That sounds kind of creepy, right?
Cooper's in the background, sniffingaround, seeing what you're doing.
And if he notices that you're doingsomething that may not be optimal, or
if you're not leveraging an integrationor leveraging a feature that most
people like you are using, or ifyou have a security setting that's
(29:50):
not properly done, Cooper will giveyou what's called a Cooper Alert.
Now, It's not clippy.
Never that clippy crap from Microsoft.
It's not annoying clippy.
I
Steve (30:01):
Why the, uh, okay, hold on a second.
Clippy.
I mean, now, today, Clippy is cool.
I wish I, I wish somebody wouldmake like a new version of Clippy
Fred (30:14):
Yes, we did.
Steve (30:16):
if I had a little AI dog on my, on my
Fred (30:18):
That's what it is, baby.
It's Cooper.
It's Cooper, Cooper.
I don't know if you can see.
You see the little, yousee the little, uh, Cooper.
It's hard to see it, but he has a pound.
When you do what he says,he gives you a pound.
But Cooper's insights tellyou, hey, you're not getting
the most out of your IT glue.
You're not, you know, you'resetting whatever you're
integrating right with your RMM.
Why are you doing three steps?
You could do two, use thisshortcut, all that stuff.
(30:42):
And here's the cool thing.
Um, about 60 percent of Cooper'sinsights were actually actioned upon.
60%.
Clippy, it was turn the damnthing off back in the day.
So it's super, it's super powerfulbecause MSP, the technicians and
the engineers, they're overwhelmed.
(31:03):
And these guys got somuch to do every day.
It's not, it's not like they're, they'reworking at Citibank and they're working
hard, but they have a lot of time to,you know, drink coffee and hang out.
MSPs get beat up.
It's tough.
They have a lot to do.
So that's the firstpiece of Cooper Insights.
Then, last year, at DattoCon,we launched Cooper Bots.
(31:27):
So, as the marketing says, Cooperhad some kids, and those kids
are the little Cooper Bots.
It's so cute, you gotta see it.
I love my dog.
But, Cooper Bots.
These represent end to end multi processor multi function business workflows, and
those Cooperbots are taking advantage ofthe deep integrations that we have between
(31:52):
the different modules in our platform.
So a workflow.
That may go across different technologiescan be automated by a CooperBot.
Um, some people call this RPA.
It's a free RPA module, but the RPAisn't being done by just sharing APIs.
It's done because the products.
Inside the application layer are builtand indexed and the databases are merged.
(32:17):
I'll give you an example.
For those in your audience, most ofyou folks probably know what security
awareness training is and simulationsare and anti phishing technologies.
Well, one of the chal so hopefullyeveryone's doing security awareness
training for their customers.
And then you'll do simulation testsand you'll simulate a phishing attempt.
(32:41):
And you'll monitor what usersfall for it and what users don't
in your report on it, right?
And the bad people get, you know, getpaddled a little bit in the backside,
and the good people get a littlecertificate saying how smart they are.
Hopefully you and I are neverone of those that click on a
link and enter our credentials.
God help us.
So, it takes a lot of time to tell, tohave your simulation technology Thank you.
(33:09):
Talk to your anti phishing technology tosay, turn off the banner that's going to
come across on your screen because thisphishing attempt is really a simulation
and we don't want to warn the user, right?
Pretty common thing.
Takes about an hour to do thatwith most products because these
(33:30):
products aren't integrated together.
So you got to really get in.
You really, if you're using KnowBe4for your security awareness training
and you're using MimeCast for your Youknow, for your phishing, you really
got to know those products well.
They don't have a nativecapability that does that.
You'll get it done, youknow, one out of three times.
You might mess it up and have todo it again, but it takes time.
With Kaseya, it's allpre configured and done.
(33:52):
There's a Cooper bot for that.
It's called Drop A Phish.
You press it, automaticallyconfigures every event to it,
done, your results come out.
It takes two seconds, fourseconds, like some number.
That's an example of a CooperBotbecause the CooperBot took the data and
it understood what people are doing.
(34:13):
People being the engineers.
What are the engineersor the technicians doing?
And it automated it.
And because these modules areall integrated, it allowed a
single workflow to get done.
There's about 230.
Cooper bots in the platform.
So that's super, super cool.
Now, the next phase of AI thatwe're doing, and we released some
(34:35):
of this at our conference in Miami,uh, when we announced Kaseya 365,
and this is called Cooper Copilot.
This is the Gen AI stuff.
Now, my personal belief is I do notthink that Uh, the Terminator times
are coming and I don't think that AIis gonna, you know, Skynet's not gonna
(34:58):
come and like, take over the world.
I don't know, maybe it will.
If it happens, you and I, it won'tmatter anyway, you know, we'll
Steve (35:05):
Now, you know, somebody, somebody said, you know, everybody's
worried about it being Skynet,but look at what AI does today.
It's, if anything, it's more like minions.
Fred (35:16):
Yes!
Steve (35:18):
So, so yeah, I'm, I'm
Fred (35:20):
That's really
Steve (35:21):
in the
Fred (35:21):
I might, Steve, I might steal that from you.
That's actually really good.
Steve (35:25):
I didn't create it, so I don't care.
Fred (35:27):
Yeah, so, but so when we think about the Cooper Copilot stuff, if you
look at closing tickets automaticallyor preemptively proposing solutions, so
from our PSA, our ticketing solution,being able to open up the RMM and
push a change out that'll close aticket automatically, we have that
capability and that capability is beingbuilt pretty aggressively and it's
(35:48):
getting smarter because we're tyingin our Gen AI with our language model
so we can see what's being driven.
Now, and we can also pre write responsesso the technician, instead of them
having to write an email back, maybeGen AI pushes the email out to them
and the communication is done andit saves, if an engineer, instead of
writing a hundred quick little emailsto a user, if they don't have to write
(36:10):
any, that saves 45 seconds per email.
That saves them 60 minutes a day.
That's an hour a day.
There's lots of that in our platform.
I will say this.
It is, it is our belief that in August,you know, where we are right now in 2024,
I personally am not fully comfortableturning Gen AI on to handle things
(36:33):
like security permissions, IT settings.
I think Gen AI is not asaccurate as, as automated humans.
Non automated humansmake a lot of mistakes.
Automated humans, you knowwhat I mean, like through
automation, that's, I think, safe.
I think that, you know, I think eachcompany has to determine do they want
(36:57):
their Gen AI to be fully autonomous?
Or Human Intervened Partial Autonomy.
But as it applies to Kaseya, we'rethree years, we're 50 people for three
years, so 150 person years, I guess.
Into this we have some super badass AIdriven applications in the form of Cooper
(37:17):
Insights, Cooper Bots, and the CooperCopilot stuff is, it's pretty cool.
And I think, you know, I thinkthat when you look at what, uh,
what MSPs have to do, you can makethem 9 percent more efficient.
It continues to change the unit economics.
(37:38):
So an MSP, instead of having ahundred endpoints managed or a
hundred users managed per, perengineer, it gets to 140 or 150.
That combined with paying, theaverage MSP right now pays 14.
For all the kit that goes on an endpointand 8 for all the kit that goes in a
(37:58):
user, if they pay 5 for all of thatwith Kaseya for more automation, that
changes the unit economics and it allowsMSPs to have more financial resources.
To invest and to do things intheir business they otherwise
just aren't able to do.
If you run a business at 8 percentprofit margin, you can't make a mistake.
(38:22):
You know, like, you can't make a mistake.
It's really hard.
That's why gas stations that run at like5 percent profit margin, it's really
hard to steal gas from a gas station.
You know, because if they, ifsomeone goes and steals the gas, it
takes away the whole day's profits.
That's, that's kind ofwhat we're doing there.
Steve (38:41):
I'm, I'm really impressed with what you guys are, are building
with Cooper and, and all of thedifferent AI and machine learning
stuff that you're working on.
Um, you know, the one last thing thatI want to ask you about, uh, another
one of those things that I alwayssee people, uh, jabbing Kaseya when,
(39:01):
when you guys aren't even looking,
what's with the, the stadium, what,
Fred (39:10):
Oh, the arena.
Steve (39:11):
Yeah, the arena.
What was the thought process behind that?
Fred (39:15):
Yeah.
Wow.
So, so two.
primary drivers.
So, you're a lot younger than Iam, so you might not remember this.
Steve (39:27):
I don't think I'm a lot younger.
Fred (39:30):
You're a lot younger than me, brother.
I'm an old, I'm old as shit.
Um, I don't know if you remember, andif your listeners will remember, and
it's a great, Business case study.
Like it's like a Harvard business casestudy, a famous corn fairy case study.
Intel, Intel just got whacked recently.
Their stock got crushed, but Intel is oneof the great, they're a great company.
(39:54):
Innovator.
Great.
So if you go back to the beginning of thePC revolution, like the late eighties and
particularly the early nineties, 92 to 96,
The average human being, average American,didn't really know what a computer was.
So in 1992, I believe thestatistic is one out of every five
(40:15):
office workers had a computer.
You go to an office and there wereno computers on people's desks.
They didn't have them.
1996, it was like 1.
2 computers for every,every knowledge worker.
But Intel, Intel producedthe chips, right?
The microprocessorsand, and they're Intel.
(40:36):
We know Intel is a giant company today,but back then nobody knew Intel because
no one knew what a freaking processor was.
Like, what the, what is a processor?
You know, like a keyboard I get,I don't know what a processor is.
So Intel was brilliant.
Intel was selling to Dell, you know,IBM, Gateway, Acer, Asus, I don't
even remember all these, Toshiba,all these old computer manufacturers.
Steve (41:00):
hmm.
Fred (41:00):
And so Gateway wanted people to realize how good their processor was.
So they went to a direct to consumeradvertising campaign called Intel Inside.
I don't know if you've everseen the commercials, like,
Steve (41:18):
I remember
Fred (41:18):
Intel Inside.
And it was basically, what theysaid is, if your computer doesn't
have Intel Inside, it's shit.
If your computer hasIntel Inside, it's great.
Safe bet.
So, I can remember my mother going,my mom and I went computer shopping.
You know, I had a good summer job,so we had a little bit of money.
(41:39):
So I went computer shopping,because I was a computer science
guy and I needed a computer.
And I remember we were at EggheadSoftware, and then we went to Sears,
because those are the two placesthat sold computers back in the day.
Neither one of those companies.
And I remember my mother saying, andmy mother, bless her soul, is one of
the sweetest women you'll ever meet.
(41:59):
I mean, she's just a, she was a saint.
And she's like, Fred, just makesure you get Intel in your computer.
And she had no idea whatIntel was, no idea what a, I
mean, no idea about anything.
So Intel did such a good job.
And everyone associateda good computer's Intel.
(42:19):
So, fast forward to us.
I am not comparing my company toIntel because I would love to be
thought of as good as Intel someday ifwe're ever blessed and lucky enough.
But here's what we want to do.
We want to build the brandof Kaseya beyond just MSPs.
(42:40):
We want business owners and businesstechnology decision makers To hear the
name and be familiar with the name Kaseya.
Kaseya is Native Americanto defend and protect.
That's actually where itcomes from and what it means.
It's pretty badass.
So we want, it's a weird word.
It's not a common word.
So if people are familiar with the wordKaseya, and an MSP comes knocking on
(43:06):
your door, and says, Hey, we're an MSP,we want to manage your IT and security,
and we're powered by Kaseya, We wantthat business owner, that dentist,
the lawyer, the architect, the ITmanager at a, at a small bank to say,
Oh, okay, you're powered by Kaseya.
You're the best.
(43:27):
You're safe.
It's a seven year planto build that brand.
And we started it with the Kaseya Center.
Uh, the, the brand recognition ofthe word Kaseya is exponentially
higher since we've done it.
And we believe that poweredby Kaseya has a meaning.
(43:51):
Where if you are powered by Kaseya,you're powered by a name brand that
provides protection and security foryour IT and security, you know, posture.
And MSPs that are doing it, not only arethey the most profitable, not only do
they have the most successful, but they'reusing kit that everyone has heard of.
(44:15):
It's a seven year plan.
We're in year two of it.
And so far, it's working pretty well.
I mean, hell, we got really lucky.
The first year we did it, theMiami Heat went to the NBA Finals.
You know, like, so, that helped a lot.
The, um, there's a distant secondbenefit, and that is, we're headquartered
in Miami, the Kaseya Center, and thebuilding behind me, one of our buildings
(44:35):
here in Miami, it's a Kaseya building.
You know, we're looking to hireanother three, four thousand
people here the next five years.
We want to get the best in the world.
And most people don't know IT andsecurity companies, you know what I mean?
They're not like name brandsand we want to be one.
So when you get really smartpeople, they say, Oh, I would love
(44:58):
to work at a company like Kaseya.
So those are the tworeasons we've done it.
And so far it's, it's going pretty well.
I can tell you right now, I'vebeen to the Kaseya Center twice.
I went to both UFC fightsthat were held there.
Big UFC fan, big fan of Dana.
I think he's built a great company there.
Um, but I, I, you know, it's nota, someone asked me, you did it
(45:19):
for the executives to go to games.
We give all of our tickets awayto either customers, um, you
know, employees that win contests.
And we do a lot for like the localkids, you know, cause we have a box
and a bunch of seats when we get that.
So it gives us theopportunity to give back.
But, uh, the main reason iswe are building that brand.
And we want MSPs powered by Kaseyato be the best and for people
(45:42):
to want to be powered by Kaseya.
We've probably distributed over a thousandleads to MSPs because people now hit our
website saying, Oh, I want MSP servicesbecause they associate Kaseya with it.
Steve (45:58):
Fred, I gotta say, you are a hell of a businessman.
Fred (46:02):
I just got a really smart people around me, man.
I just, I just tell me, I just speak andtell, I just say what they tell me to say,
Steve (46:08):
Well, but, but let's, let's be honest.
You are smart enough to, to find peoplethat are smarter than you to surround
yourself with, with those people who are,are experts at that one little thing.
And, and you're smart enough toset, you know, surround yourself by
all those people, uh, in order tocome up with all these great ideas.
(46:28):
So, you're still, you're,you're a hell of a businessman.
Fred (46:32):
No, I appreciate it.
I appreciate it.
Thank you.
And, and I think that the, the peoplein the company appreciate it cause it's
really them and they're freaking awesome.
Very, very lucky.
Very blessed.
Got a cool crew.
Steve (46:42):
Oh,
Fred (46:43):
So when are you coming down to Miami to visit?
Check out a basketball game if you want,
Steve (46:46):
You know, that sounds like a great time.
I will definitely, uh, I'll, Igotta talk to the boss, the, the
wife, and, and figure out, yeah, Igotta figure out when I can do it.
Fred (46:57):
one of the cool things about the Kaseya Center is there's so
many pictures of Cooper in therebecause, you know, we get to.
Do it.
So we're, now we do a lot ofwork for animal charities and dog
charities, and that's a big personalcause of mine and our companies,
and it's, it's a great experience.
So we'd love to have you downand, and really appreciate the
opportunity to be on your show.
Steve (47:16):
I would love that.
I, I so much for coming on.
Uh, thank you for being a guest, and I, Ilook forward to what Kaseya has to come.
I think you guys have a bigannouncement later this year.
Fred (47:26):
Yeah, we have, uh, we have a big customer conference in Miami at DattoCon,
and I assure all your listeners, The,the announcement that we're going to
make will be the largest announcementimpacting the most MSPs, impacting
(47:46):
the profitability of the most MSPspossible, and there'll be some nice,
there'll be an acquisition with thisone as well, so this'll be a lot of fun.
Steve (47:57):
Awesome.
You, you know, everybody'sspeculating it's ConnectWise.
Fred (48:02):
ConnectWise is a great company.
Uh, Jason McGee is a great guy.
I'll tell you a story about Jason McGee.
This is going back a long time ago.
He and I were both in New YorkCity in the late nineties,
like just starting our careers.
We were like young whippersnappers.
And Jason was my younger brother'sfirst boss, uh, at a company
called Interactive Futures.
(48:22):
It was a, it was a VAR run bya guy named Steve Scherr and,
and McGee was really good then.
He's, he's a talented guy and hewas so good to my younger brother.
I will never forget that.
So yeah.
ConnectWise, great company.
I'd love to work with Jay again.
Steve (48:39):
Well, thank you so much, Fred.
Uh, I, I really appreciateyou coming on the show.
Fred (48:44):
Awesome.
Thanks for having me.
Take care.
Bye bye.
So, Fred, welcome.
Fred (00:01):
Thanks, Steve.
Great to be here.
Steve (00:03):
I'm glad to have you here, man.
So, uh, this has been somethingthat I've been wanting to do
for about a year, if not longer.
So, I'm honestly, I'm really excitedthat I get to do this with you today.
So, so truly, thank you for comingon and letting me interview you.
Fred (00:20):
Well, like I said, thanks for having me.
We're super pumped to be here,and this should be a lot of fun.
Steve (00:24):
Good.
So, uh, you know, this is a show for MSPs.
So, if, if you, listener, haven't heard ofKaseya by now, I don't, I don't know what
to tell you, because Kaseya is huge, and,and you should know who they are by now.
They probably own at least oneof the tools you're working with.
Um, Fred, I, I gotta ask, uh, what, whatis your strategy when it comes to like,
(00:53):
uh, thinking about new acquisitions?
Because I, I know you guys, youguys acquire a lot of things and
there's, there's probably things thatyou guys have acquired that people
don't know you've acquired too.
Fred (01:06):
Yeah, there's some of those.
Um, so maybe, Steve, the wayI can address it is I'll talk
about what our strategy is.
Because acquisitions are part of it.
But the question is why, andthe problems we're solving.
So it's actually pretty fun.
And it's, it's, it's been, uh, forme personally, it's been 10 years
since I've been in the industrynow, it's been awesome, man.
(01:27):
I, I've loved the lastdecade in this industry.
In the MSP industry.
So about 11 years ago, ormaybe 10 and a half years ago.
We started looking at, uh, at Kaseyaand what we saw in looking at Kaseya
was the opportunity to build aplatform that could fundamentally
(01:50):
change the MSP industry forever.
That's a bold statement and maybea crazy kind of statement to make,
but we thought we could do itby changing the unit economics.
of the MSP industry in favor of the MSP.
(02:11):
And by doing that, just free up awhole world of possibilities for MSPs.
So let me tell you what I mean by that,and then where acquisitions fit into it.
So, Kaseya's purpose, we build a platform.
Our platform is called ITComplete.
(02:31):
ITComplete contains all of thefunctionality That an MSP needs to
deliver all of the managed servicesthat their customers require, as
well as all of the internal systems,like PSA and IT documentation and
things, for the MSP to effectivelyand efficiently run their business.
(02:55):
We provide all that in oneplatform, one screen, if you will,
or one series of integrations.
And by providing it all in one place,a couple of interesting things happen.
Because Kaseya owns all of the differentplatforms, Are all the different pieces
of software it allows us to integratethem in a very meaningful way and
(03:22):
allows us to build them as one product.
And why that's important is whenmultiple technologies that are
required to do a given task, when theyare deeply integrated, is when that
process or that task can be automated.
(03:44):
And as you know, Steve,automation is the name of the game
Steve (03:47):
Mm hmm.
Fred (03:49):
It allows engineers to do more and it allows fewer mistakes.
Now, add on top of that, thepower that AI bring, both large
language model AI or machinelearning type AI, As well as GenAI.
So when we apply the AI capabilitiesto a fully integrated platform,
(04:17):
the ability for that platform toautomate upwards of 50 percent of
what an MSP has to do is tremendous.
And what that does foran MSP is astronomical.
An MSP can automate even a third,if not half, of the tasks that
(04:38):
their engineers do on a daily basis.
That MSP is substantially more profitable,effective, and makes fewer mistakes.
Now, when we talk about what our journeyis, Kaseya's journey, like I mentioned,
is to change the unit economics ofthis industry in favor of the MSP.
(05:04):
So, Steve, here's a couple of statistics.
When you think about most MSPs,most MSPs are serving companies
of 100 employees or less.
So, if an MSP has 70 customers, maybe twoor three are co managed customers where
they have 1, 000 or 2, 000 employees,but the majority of their customers
(05:28):
have between 25 and 100 employees.
Architecture firms, doctors offices,dental practices, et cetera, law firms.
Now, the business service providers.
That are providing outsourcedservices to the customers of MSPs
are predominantly law firms, as wellas like tax and financial people.
(05:55):
Profit margins of law firmsrun in the 30 percent range.
The profit margins of financial and taxfolks run in about the 30 percent range.
Did you know the average MSP inthe Western world has an average
profit margin of just under 10%?
10%.
Steve (06:15):
I didn't realize it was that low.
I thought it was probablyin the 15 percent range, but
that doesn't surprise me.
Fred (06:21):
Yeah, the ranges are all over, but the average, and we have about
54, 000 MSP partners and customers,call it 10 percent shade under.
And if you think about what the MSPsdo, number one, it's much harder.
See, in the last seven, eightyears, Most of these small to mid
(06:43):
sized businesses, they've digitallytransformed, or the business and
industrial systems and applicationsthat they use drive their business.
So if their systems aren't alwaysavailable and always secure,
they're, they're not functioning.
So the job of an MSP isexponentially more important and
(07:09):
more valuable to their clients.
Then the law firms and thetax prep firms that are making
three times the profit margin.
On top of that, if we look at society,I've seen data that tells us that upwards
of 70 percent of new job growth, ofeconomic job growth is happening from
(07:32):
small to mid sized businesses, right?
New hires, opportunities, et cetera.
Particularly in at risk areas, we'veseen small companies just, just the
business of small companies exploding.
And these small to mid sized businessesare able to compete because of advances in
(07:53):
business systems and industrial systems.
And keeping those systems alwaysavailable and always secure is keeping
the most important, high growth,and soon to be largest businesses.
Part of our economic enginerunning, and that's what MSPs do.
And MSPs are making one thirdthe profit margin of the other
(08:17):
business service providers.
So at Kaseya, we constructedthis platform that provides all
the functionality in one place.
We automate it throughintegration and tremendous AI.
So these engineers, these MSPengineers can be much more efficient.
And we charge one third as much as whatthe MSP would pay if they bought nine
(08:43):
products from nine different vendors.
So we believe by doing that, we've,we have literally put the foundation
in place to change the uniteconomics for the entire industry.
And now MSPs are receiving thefinancial rewards, you know,
25 30 percent profit margin.
(09:05):
for listening.
that they should.
Quite frankly, they should be highergiven the value that they provide,
but MSPs struggle a little bit, andour industry struggles a little bit,
because a lot of the customers of MSPs,they don't necessarily understand all
the risks of cybersecurity threatsand the importance and the costs
of making sure they're available.
(09:26):
So that's our strategy, and as we'veconstructed ITComplete, we've made 17
acquisitions over the last 11 years.
We spent over 12 billion buying thesecompanies and, you know, the thousands
of engineers we have that are integratingthem and building it into one platform.
(09:48):
Our platform must be complete becauseif our platform's not complete.
We have a tough time delivering on thepromise of everything in one place.
So that's our strategy andthat's, you know, Steve, that's,
that's how M& A fits into it.
And again, our mission is MSPspowered by Kaseya should have profit
margins three times the industry sothey can invest in their business.
(10:12):
To better deliver for their customersand to, quite frankly, make the
money that they deserve to make.
Steve (10:19):
I really like that.
You know, you mentioned that mostof your customers, and you said,
I think you said you've got 54,000 MSPs you're working with?
That's a whole lot of MSPs.
Of the 54, 000, do you, off the topof your head, happen to know, um,
how many of those MSPs are generatingless than 250, 000 of annual revenue?
Fred (10:45):
Annual revenue?
I'd say probably 10 of themare two employees or less.
So, we measure by numberof employees, Steve.
Steve (10:56):
Sure,
Fred (10:57):
I would assume that number there's also quite a few MSPs,
That aren't, you know, we haveMSPs as large as Thrive Networks.
You know, they're abillion dollar business.
We have MSPs as small asSteve's part time gig, right?
Where, you know, you, you, you haveyour day job and you manage your
buddy's dental practice and yourbuddy's law firm at night, and you
(11:19):
make an extra five or 10, 000 a month,which is great money, uh, doing that.
So we have all sorts, but I believe.
The number of two or lessis right around 10, 000.
Steve (11:32):
And, So, so that's a fifth, if not a quarter of your customer
Fred (11:40):
Yeah, about a fifth.
Steve (11:41):
So, I, I would argue that, um, five or fewer is probably
half of your customer base.
Uh, and, and that's just based onthe, the information that I've,
I've gathered over the years, uh,understanding the MSP industry.
(12:02):
So, one of, one of the questions I haveis when, when you make these acquisitions,
Traditionally, there's been a lot offrustration I've seen on the forums and
I, I, I haven't run an MSP for a fewyears, so I don't have any skin in
the game, Fred, but there's been a lotof frustration in the forums because
(12:24):
it seems like you guys have, uh, kindof your, your play where, um, you
know, you, you acquire a company, youchange everything to be three year
contracts, you raise the prices, yougot the, the, um, The dev team, and
then the product becomes stagnant.
That's, that's the frustration that I hearfrom the, the people who want to be loud.
(12:49):
So what would you say to those people?
Fred (12:52):
I mean, I'd say I Thank you for the feedback, you know, like
it's, feedback is a gift, man.
And even if you don't like it, youtake it and you try to learn from it.
We, when we bought Datto, we,we, we heard a lot of that.
And one of the things that we did,and it's still published, is we
published, we called it Just the Facts.
(13:15):
And we published the investment in R& D.
of every single acquisition that we'vedone, you know, right before we bought
them and then after we bought them.
You know, IDAgent, RapidFireTools,ITGlue, RocketCyber, Graphis,
you know, you name them.
And the numbers are pretty staggering.
(13:37):
And I think the average was we doubledthe R& D team within six months.
Every single acquisition thatwe've done, Steve, every.
Not like all but one,you know what I mean?
Like an absolute every we'velowered the price when we
bought the company, everyone.
So the idea that we raise pricesis simply not factually true.
(14:02):
Everyone, even data, every single one.
And it's, again, it's all, we'veall made all this information public
and the team can share it with you.
It's on the websites and everywhere.
Steve (14:12):
But by lowering, are you lowering the prices, but extending
the, the length of the agreement?
Fred (14:19):
um, we always offer one and three year agreements for
every product that we sell.
The three year agreements are thebest price by far, but even on the
one year agreements, the pricesare lower than when we bought them.
Steve (14:33):
Do you, do you ever offer month to month terms for people that, And obviously
that would be at a, at a premium, right?
But do you ever offer monthto month terms for people that
just don't want a contract?
Fred (14:44):
we offer month to month terms in one case, and that case is when people
are coming off of, so if someone buys aBCDR appliance, like a DattoBox, right,
um, say it's a, they sign up for a one ora three year agreement for that DattoBox
and that contract ends, they have theoption of extending that DattoBox month
(15:04):
to month, one year or a three year option.
No, we do not offer as a standard part of.
New business other than the DattoBCDR business month to month degree.
Steve (15:14):
Okay.
Um, so, so you mentionedthe Datto acquisition.
Um, I feel like you've probably learneda lot over, over the years with all
these acquisitions that Kaseya's made.
Um, the, the biggest thing that, youknow, people complained about with the
(15:35):
Datto acquisition was the billing issues.
And If we look at, again, a fifth toa quarter of your, your customer base
is two people or fewer, um, billingissues really hurt, you know what
I mean, like, when, when it's, whenit's a multi billion dollar company
like yours, you know, if, if somebodyaccidentally accidentally, Bills you
(15:58):
five times what they're supposed to.
Usually for you, that's just a roundingerror until the bill gets corrected.
But for these smaller MSPs,um, these invoices can be
just, they can destroy a business,especially if, if you guys start
shutting off services because theinvoice isn't paid, even though,
(16:21):
even though the invoice was wrong.
So.
What, what did you learn, uh, from,from the integration of Datto and
from, from all of the billing issuesthat you've, uh, overcome, and, and
how are you going to deploy that, uh,learning into your next acquisition?
Fred (16:44):
Yeah.
So Datto was a so thelearnings I could write a book.
Literally, I could write a book.
And I mean that like not in a funnyway, but in a real way, because
I think it could help a lot ofpeople maybe not make some of the
mistakes that I made or that we made.
Um, so a little background.
Datto, as you know, and mostof your listeners probably
know, is a public company.
(17:04):
Um, and they were our biggest competitor.
So, you know, we acquired them.
And it's not a secret that themanagement team of Datto I wasn't
overly enthusiastic about beinginquired by one of their competitors.
So it made for a, ainteresting cultural time.
Um, which, which is notuncommon in acquisitions.
(17:28):
Now many of the acquisitions thatwe made prior weren't competitive.
You know, it was, theyweren't competitive.
Dato, um, there were a couple ofareas that we competed with them.
I think, looking back at the acquisition,uh, it's, it's been a financial success.
We've made a lot of bumps.
I think when you look at a hundredacquisitions of that size, scope, and
(17:51):
complexity, we're probably in the, youknow, the, now that we're two, believe it
or not, we're over two years past that.
Can you believe that?
It's crazy.
Uh, we're, we're 4%.
of, like, success in allthe ways you measure it.
Customer retention, customersatisfaction, revenue, profit, all the
different ways that that gets measured.
(18:12):
But the direct answer to your question,the first part of your question, is on
the billing side, and we made mistakes.
There's no way around it, and,and, to your point directly, If
I'm a two part, I mean, I've, I'vestarted four companies myself.
I'm an entrepreneur who typicallystarted companies without venture
(18:33):
money and mommy and daddy's money.
It was always, you know, doing it myselfand I've been in situations where I've
struggled to make payroll early on.
You're a two person MSP, you get abill from a vendor, and that bill's
wrong, and it's wrong by a lot.
You know, the bill's not getting resolvedfor various reasons, and you're worried
(18:57):
about having disruption of service, andwhat does that mean to your customers?
These are serious things.
These are very seriousthings for the customers.
One of the decisions that we took atDatto or Kaseya during this process was
relatively early on during the billingchallenges, we decided to take our foot
(19:22):
off the gas in terms of collections.
You know, so if our system tells usthat Steve's MSP owes us 25, 000.
And Steve says he owes us 5, 000.
In normal times, Stevewould pay us 5, 000.
We would, you know, causeSteve believes he owes 5, 000.
(19:42):
And we would keep the systems onand we'd work to settle what is,
let's, let's dig into and lookat the remaining 20, 000, right?
That's, that's how mostbusinesses operate.
Steve (19:52):
Mm
Fred (19:52):
Um, and we took the approach for a while where we would even say, you know
what, Steve has an issue, it's 25, 000.
Don't pay us anything.
Let's go and figure out what it is.
To error on that side.
And I think it took us a good five monthsto work through all of the challenges.
(20:13):
You know, we're through it now.
I think we have, I have the data,the data won't mean anything to your
listeners, all the KPIs that we track,but we're back to levels that are
better than the pre data acquisition.
And it's the kind of place,the kind of thing where.
If you mess up one customer or onepartner, that's like one too many.
(20:34):
You don't want to mess anyone up.
You know, we've, we've done a fairlygood job of trying to put customer first.
Now there's people that take advantageof situations like that, things like
that happen, but I think the lessonthat we learned was over communication
(20:54):
is better, and sometimes overcommunication about hard realities that
partners may not like is better than
trying to deliver something thatmay be impossible in a time frame.
But it's, it's, it was definitely notlost on Kaseya about the challenges that
(21:18):
that poses, especially on the small.
Smaller MSPs and we've adjusted.
I mean, even today, we'vemade a lot of adjustments.
We're past the problems, but we madea lot of adjustments today where MSPs
of, of certain complexity or, or,or sophistication, you know, like if
you're a two person MSP, you don't havea dedicated account payable person.
(21:39):
You just don't, right?
I mean, that's the reality.
So, the engineer who's supporting theirseven clients and their, you know, 200
endpoints has to deal with a bill andan invoice and it's a pain in the butt
and maybe the partner's on vacationand it gets, that's real life and we're
attuned to it and we're spending a lotof time and a lot of money to streamline
(22:00):
as many processes as we can and provideautomation for as much as we can in
that like commercial interaction space.
You know, it's, it's, uh, like a lotof things, like our, like our security
incident we had three, four years ago,you learn a lot and you just do your best
to apply them, try to be transparent andbe better every day if we can be better.
(22:22):
And I, I still believe, actually, Ibelieve now more than ever, especially
with the release of Kaseya 365.
Our customers, our partners, we usethe word partner and customer kind
of interchangeably, our partnersare more profitable than the
majority, than the MSPs that arenot our partners in the industry.
(22:43):
And that's what we're shooting for.
Steve (22:46):
Okay, I, I respect that answer.
Um, earlier you mentioned AI, uh,in passing, and I know, um, AI is
one of the topics that was, wasfloated as, as something that you
wanted to talk about, so I suspect
Fred (23:04):
That's what I wanted to talk about.
Steve (23:07):
your, your PR team, when, when you reached out, so AI was one of those
topics that was floated, and that leads meto believe that Kaseya is going to start
ramping up, uh, discussion, mention of,of AI, machine learning, large language
models, et cetera, uh, within its product.
(23:27):
I'm, I'm seeing a lot of companiesstarting to talk about AI.
Uh, how, how their platformshave AI and machine learning.
And I, I think, I think MSPs are startingto feel, uh, burnt out already on AI
Fred (23:46):
It's like cloud was in the past, right?
Well, here's cloud,cloud, cloud, and yeah.
Steve (23:50):
Yeah, because, because everyone, you know, every, it's like a buzzword.
I mean, you know, if I, if Ihear somebody talk about the, the
synergies in AI, I'm, I'm You wantto go postal somewhere, right?
So, um,
Fred (24:02):
from Miami.
Steve (24:03):
yeah,
it's everywhere, man.
It's everywhere.
So, so all that to say, I, I'm of themindset that, um, AI can be good, can
be useful, but a perfect example of, ofwhere it can go really wrong really quick.
I just saw, uh, a Proof of concept wheresomebody was using Microsoft Copilot
(24:30):
and the person not authenticated to thespace was able to ask the AI chatbot
about, um, uh, downsizing and what,what employees are going to be affected.
And it just started answering.
So that obviously.
(24:50):
is, is a, you know, data governanceissue for that particular proof of
Fred (24:55):
Yeah.
Yeah.
Steve (24:56):
So, gosh, I got one of these little flies bugging me.
Um, so, all that to say, I, Isuspect Kaseya is going to get into
the AI game soon, if not already.
What are you guys going to do to putup guardrails to protect customer
(25:18):
A from seeing customer B's data?
Fred (25:26):
And what was the second part?
Steve (25:29):
Um, Well, let's, let's start there.
What, what are you guys gonnado to, to protect customer
A from seeing customer B'S
Fred (25:36):
Yeah, so let me start by talking about our AI and I'm
going to show you something.
I don't know if you can see this.
See that little guy there, thatdog on the back of my phone?
Steve (25:45):
Yeah.
Fred (25:46):
That's Cooper.
Cooper is my dog.
He's in a boxing outfit there.
I can see it.
And Cooper is our AI engine.
So it's the Cooper Intelligence,Cooper Artificial Intelligence Engine.
We launched Cooper three years ago.
So we've been in this game for a while.
Not that that's good or bad.
(26:07):
'cause I agree with you.
I think AI is a great word.
A lot of companies put AI in their,in their corporate summary, and they
get a 10% increase in their valuationjust because the words AI are in there.
You know, it's, it's, it's crazier.
You go to a party andyou say, what do you do?
I work in ai.
Everyone thinks you're smart.
Um, so our approach to AI is very simple.
(26:29):
So let's look at the fundamentals of ai.
There's two types of ai.
Gen and, and, and, uh, languagemodel or, or, or machine learning.
Let's break it into those two.
So the most common for productivity usagein sophisticated workflows isn't Gen AI.
It's really language models andprocessing and, and the, um,
(26:54):
machine learning type of AI.
So machine learning and the models that,that are associated with it are all
dependent upon how good and voluminousthe data sources are that can be analyzed.
So, if you think about Kaseya, we haveabout, let's make the math easy and
say 50, 000 MSPs to round the math.
(27:16):
And say the average MSP has20 employees or 20 engineers.
Some have 1, 000, some have 1.
So let's say 20 is the average.
That means I believe there'sabout a million employees.
We have a million engineers usingour products, MSP, a million MSPs
using our platform every day.
So, we get a tremendous amount ofdata, denormalized data, non uniquely
(27:43):
identified data, so we're not trackingwhat Bill Smith does, we're tracking
what MSPs do in aggregate, right?
And looking at what theydo, how they use technology.
How many keystrokes do they do for this?
What, what workflows are they doingto accomplish a particular objective?
How do they respond to particularinstances or other types
(28:07):
of things that take place?
We have all that data in our model.
Inside of cooper.
So that data allows us to really model outwhat MSPs are doing, what they're not, how
effective they are, how to make them moreeffective, what steps can be done, what
(28:27):
pieces can be built, how to leverage that
huge source of information.
We also have Upwards of 50 millionendpoints that we're managing.
I don't know how many hundredsof petabytes that we're managing.
We do millions of compliance scansa month, millions of security scans,
hundreds of millions of documentation.
(28:48):
So much stuff, so much data that we have.
And we plug that in and we builttwo applications out of that.
Two tools, because I believeAI, we believe AI is a tool.
Very, it can be an effective tool.
To help people be more productive andfrom a machine learning piece, the
(29:09):
two, the first two applications webuilt, one we released about three
years ago was called Cooper Insights.
All this is available in ourplatform and has been for years.
What Cooper Insights is,is Cooper is watching you.
Let's say you're using our RMM product.
Cooper is watching you.
(29:30):
That sounds kind of creepy, right?
Cooper's in the background, sniffingaround, seeing what you're doing.
And if he notices that you're doingsomething that may not be optimal, or
if you're not leveraging an integrationor leveraging a feature that most
people like you are using, or ifyou have a security setting that's
(29:50):
not properly done, Cooper will giveyou what's called a Cooper Alert.
Now, It's not clippy.
Never that clippy crap from Microsoft.
It's not annoying clippy.
I
Steve (30:01):
Why the, uh, okay, hold on a second.
Clippy.
I mean, now, today, Clippy is cool.
I wish I, I wish somebody wouldmake like a new version of Clippy
Fred (30:14):
Yes, we did.
Steve (30:16):
if I had a little AI dog on my, on my
Fred (30:18):
That's what it is, baby.
It's Cooper.
It's Cooper, Cooper.
I don't know if you can see.
You see the little, yousee the little, uh, Cooper.
It's hard to see it, but he has a pound.
When you do what he says,he gives you a pound.
But Cooper's insights tellyou, hey, you're not getting
the most out of your IT glue.
You're not, you know, you'resetting whatever you're
integrating right with your RMM.
Why are you doing three steps?
You could do two, use thisshortcut, all that stuff.
(30:42):
And here's the cool thing.
Um, about 60 percent of Cooper'sinsights were actually actioned upon.
60%.
Clippy, it was turn the damnthing off back in the day.
So it's super, it's super powerfulbecause MSP, the technicians and
the engineers, they're overwhelmed.
(31:03):
And these guys got somuch to do every day.
It's not, it's not like they're, they'reworking at Citibank and they're working
hard, but they have a lot of time to,you know, drink coffee and hang out.
MSPs get beat up.
It's tough.
They have a lot to do.
So that's the firstpiece of Cooper Insights.
Then, last year, at DattoCon,we launched Cooper Bots.
(31:27):
So, as the marketing says, Cooperhad some kids, and those kids
are the little Cooper Bots.
It's so cute, you gotta see it.
I love my dog.
But, Cooper Bots.
These represent end to end multi processor multi function business workflows, and
those Cooperbots are taking advantage ofthe deep integrations that we have between
(31:52):
the different modules in our platform.
So a workflow.
That may go across different technologiescan be automated by a CooperBot.
Um, some people call this RPA.
It's a free RPA module, but the RPAisn't being done by just sharing APIs.
It's done because the products.
Inside the application layer are builtand indexed and the databases are merged.
(32:17):
I'll give you an example.
For those in your audience, most ofyou folks probably know what security
awareness training is and simulationsare and anti phishing technologies.
Well, one of the chal so hopefullyeveryone's doing security awareness
training for their customers.
And then you'll do simulation testsand you'll simulate a phishing attempt.
(32:41):
And you'll monitor what usersfall for it and what users don't
in your report on it, right?
And the bad people get, you know, getpaddled a little bit in the backside,
and the good people get a littlecertificate saying how smart they are.
Hopefully you and I are neverone of those that click on a
link and enter our credentials.
God help us.
So, it takes a lot of time to tell, tohave your simulation technology Thank you.
(33:09):
Talk to your anti phishing technology tosay, turn off the banner that's going to
come across on your screen because thisphishing attempt is really a simulation
and we don't want to warn the user, right?
Pretty common thing.
Takes about an hour to do thatwith most products because these
(33:30):
products aren't integrated together.
So you got to really get in.
You really, if you're using KnowBe4for your security awareness training
and you're using MimeCast for your Youknow, for your phishing, you really
got to know those products well.
They don't have a nativecapability that does that.
You'll get it done, youknow, one out of three times.
You might mess it up and have todo it again, but it takes time.
With Kaseya, it's allpre configured and done.
(33:52):
There's a Cooper bot for that.
It's called Drop A Phish.
You press it, automaticallyconfigures every event to it,
done, your results come out.
It takes two seconds, fourseconds, like some number.
That's an example of a CooperBotbecause the CooperBot took the data and
it understood what people are doing.
(34:13):
People being the engineers.
What are the engineersor the technicians doing?
And it automated it.
And because these modules areall integrated, it allowed a
single workflow to get done.
There's about 230.
Cooper bots in the platform.
So that's super, super cool.
Now, the next phase of AI thatwe're doing, and we released some
(34:35):
of this at our conference in Miami,uh, when we announced Kaseya 365,
and this is called Cooper Copilot.
This is the Gen AI stuff.
Now, my personal belief is I do notthink that Uh, the Terminator times
are coming and I don't think that AIis gonna, you know, Skynet's not gonna
(34:58):
come and like, take over the world.
I don't know, maybe it will.
If it happens, you and I, it won'tmatter anyway, you know, we'll
Steve (35:05):
Now, you know, somebody, somebody said, you know, everybody's
worried about it being Skynet,but look at what AI does today.
It's, if anything, it's more like minions.
Fred (35:16):
Yes!
Steve (35:18):
So, so yeah, I'm, I'm
Fred (35:20):
That's really
Steve (35:21):
in the
Fred (35:21):
I might, Steve, I might steal that from you.
That's actually really good.
Steve (35:25):
I didn't create it, so I don't care.
Fred (35:27):
Yeah, so, but so when we think about the Cooper Copilot stuff, if you
look at closing tickets automaticallyor preemptively proposing solutions, so
from our PSA, our ticketing solution,being able to open up the RMM and
push a change out that'll close aticket automatically, we have that
capability and that capability is beingbuilt pretty aggressively and it's
(35:48):
getting smarter because we're tyingin our Gen AI with our language model
so we can see what's being driven.
Now, and we can also pre write responsesso the technician, instead of them
having to write an email back, maybeGen AI pushes the email out to them
and the communication is done andit saves, if an engineer, instead of
writing a hundred quick little emailsto a user, if they don't have to write
(36:10):
any, that saves 45 seconds per email.
That saves them 60 minutes a day.
That's an hour a day.
There's lots of that in our platform.
I will say this.
It is, it is our belief that in August,you know, where we are right now in 2024,
I personally am not fully comfortableturning Gen AI on to handle things
(36:33):
like security permissions, IT settings.
I think Gen AI is not asaccurate as, as automated humans.
Non automated humansmake a lot of mistakes.
Automated humans, you knowwhat I mean, like through
automation, that's, I think, safe.
I think that, you know, I think eachcompany has to determine do they want
(36:57):
their Gen AI to be fully autonomous?
Or Human Intervened Partial Autonomy.
But as it applies to Kaseya, we'rethree years, we're 50 people for three
years, so 150 person years, I guess.
Into this we have some super badass AIdriven applications in the form of Cooper
(37:17):
Insights, Cooper Bots, and the CooperCopilot stuff is, it's pretty cool.
And I think, you know, I thinkthat when you look at what, uh,
what MSPs have to do, you can makethem 9 percent more efficient.
It continues to change the unit economics.
(37:38):
So an MSP, instead of having ahundred endpoints managed or a
hundred users managed per, perengineer, it gets to 140 or 150.
That combined with paying, theaverage MSP right now pays 14.
For all the kit that goes on an endpointand 8 for all the kit that goes in a
(37:58):
user, if they pay 5 for all of thatwith Kaseya for more automation, that
changes the unit economics and it allowsMSPs to have more financial resources.
To invest and to do things intheir business they otherwise
just aren't able to do.
If you run a business at 8 percentprofit margin, you can't make a mistake.
(38:22):
You know, like, you can't make a mistake.
It's really hard.
That's why gas stations that run at like5 percent profit margin, it's really
hard to steal gas from a gas station.
You know, because if they, ifsomeone goes and steals the gas, it
takes away the whole day's profits.
That's, that's kind ofwhat we're doing there.
Steve (38:41):
I'm, I'm really impressed with what you guys are, are building
with Cooper and, and all of thedifferent AI and machine learning
stuff that you're working on.
Um, you know, the one last thing thatI want to ask you about, uh, another
one of those things that I alwayssee people, uh, jabbing Kaseya when,
(39:01):
when you guys aren't even looking,
what's with the, the stadium, what,
Fred (39:10):
Oh, the arena.
Steve (39:11):
Yeah, the arena.
What was the thought process behind that?
Fred (39:15):
Yeah.
Wow.
So, so two.
primary drivers.
So, you're a lot younger than Iam, so you might not remember this.
Steve (39:27):
I don't think I'm a lot younger.
Fred (39:30):
You're a lot younger than me, brother.
I'm an old, I'm old as shit.
Um, I don't know if you remember, andif your listeners will remember, and
it's a great, Business case study.
Like it's like a Harvard business casestudy, a famous corn fairy case study.
Intel, Intel just got whacked recently.
Their stock got crushed, but Intel is oneof the great, they're a great company.
(39:54):
Innovator.
Great.
So if you go back to the beginning of thePC revolution, like the late eighties and
particularly the early nineties, 92 to 96,
The average human being, average American,didn't really know what a computer was.
So in 1992, I believe thestatistic is one out of every five
(40:15):
office workers had a computer.
You go to an office and there wereno computers on people's desks.
They didn't have them.
1996, it was like 1.
2 computers for every,every knowledge worker.
But Intel, Intel producedthe chips, right?
The microprocessorsand, and they're Intel.
(40:36):
We know Intel is a giant company today,but back then nobody knew Intel because
no one knew what a freaking processor was.
Like, what the, what is a processor?
You know, like a keyboard I get,I don't know what a processor is.
So Intel was brilliant.
Intel was selling to Dell, you know,IBM, Gateway, Acer, Asus, I don't
even remember all these, Toshiba,all these old computer manufacturers.
Steve (41:00):
hmm.
Fred (41:00):
And so Gateway wanted people to realize how good their processor was.
So they went to a direct to consumeradvertising campaign called Intel Inside.
I don't know if you've everseen the commercials, like,
Steve (41:18):
I remember
Fred (41:18):
Intel Inside.
And it was basically, what theysaid is, if your computer doesn't
have Intel Inside, it's shit.
If your computer hasIntel Inside, it's great.
Safe bet.
So, I can remember my mother going,my mom and I went computer shopping.
You know, I had a good summer job,so we had a little bit of money.
(41:39):
So I went computer shopping,because I was a computer science
guy and I needed a computer.
And I remember we were at EggheadSoftware, and then we went to Sears,
because those are the two placesthat sold computers back in the day.
Neither one of those companies.
And I remember my mother saying, andmy mother, bless her soul, is one of
the sweetest women you'll ever meet.
(41:59):
I mean, she's just a, she was a saint.
And she's like, Fred, just makesure you get Intel in your computer.
And she had no idea whatIntel was, no idea what a, I
mean, no idea about anything.
So Intel did such a good job.
And everyone associateda good computer's Intel.
(42:19):
So, fast forward to us.
I am not comparing my company toIntel because I would love to be
thought of as good as Intel someday ifwe're ever blessed and lucky enough.
But here's what we want to do.
We want to build the brandof Kaseya beyond just MSPs.
(42:40):
We want business owners and businesstechnology decision makers To hear the
name and be familiar with the name Kaseya.
Kaseya is Native Americanto defend and protect.
That's actually where itcomes from and what it means.
It's pretty badass.
So we want, it's a weird word.
It's not a common word.
So if people are familiar with the wordKaseya, and an MSP comes knocking on
(43:06):
your door, and says, Hey, we're an MSP,we want to manage your IT and security,
and we're powered by Kaseya, We wantthat business owner, that dentist,
the lawyer, the architect, the ITmanager at a, at a small bank to say,
Oh, okay, you're powered by Kaseya.
You're the best.
(43:27):
You're safe.
It's a seven year planto build that brand.
And we started it with the Kaseya Center.
Uh, the, the brand recognition ofthe word Kaseya is exponentially
higher since we've done it.
And we believe that poweredby Kaseya has a meaning.
(43:51):
Where if you are powered by Kaseya,you're powered by a name brand that
provides protection and security foryour IT and security, you know, posture.
And MSPs that are doing it, not only arethey the most profitable, not only do
they have the most successful, but they'reusing kit that everyone has heard of.
(44:15):
It's a seven year plan.
We're in year two of it.
And so far, it's working pretty well.
I mean, hell, we got really lucky.
The first year we did it, theMiami Heat went to the NBA Finals.
You know, like, so, that helped a lot.
The, um, there's a distant secondbenefit, and that is, we're headquartered
in Miami, the Kaseya Center, and thebuilding behind me, one of our buildings
(44:35):
here in Miami, it's a Kaseya building.
You know, we're looking to hireanother three, four thousand
people here the next five years.
We want to get the best in the world.
And most people don't know IT andsecurity companies, you know what I mean?
They're not like name brandsand we want to be one.
So when you get really smartpeople, they say, Oh, I would love
(44:58):
to work at a company like Kaseya.
So those are the tworeasons we've done it.
And so far it's, it's going pretty well.
I can tell you right now, I'vebeen to the Kaseya Center twice.
I went to both UFC fightsthat were held there.
Big UFC fan, big fan of Dana.
I think he's built a great company there.
Um, but I, I, you know, it's nota, someone asked me, you did it
(45:19):
for the executives to go to games.
We give all of our tickets awayto either customers, um, you
know, employees that win contests.
And we do a lot for like the localkids, you know, cause we have a box
and a bunch of seats when we get that.
So it gives us theopportunity to give back.
But, uh, the main reason iswe are building that brand.
And we want MSPs powered by Kaseyato be the best and for people
(45:42):
to want to be powered by Kaseya.
We've probably distributed over a thousandleads to MSPs because people now hit our
website saying, Oh, I want MSP servicesbecause they associate Kaseya with it.
Steve (45:58):
Fred, I gotta say, you are a hell of a businessman.
Fred (46:02):
I just got a really smart people around me, man.
I just, I just tell me, I just speak andtell, I just say what they tell me to say,
Steve (46:08):
Well, but, but let's, let's be honest.
You are smart enough to, to find peoplethat are smarter than you to surround
yourself with, with those people who are,are experts at that one little thing.
And, and you're smart enough toset, you know, surround yourself by
all those people, uh, in order tocome up with all these great ideas.
(46:28):
So, you're still, you're,you're a hell of a businessman.
Fred (46:32):
No, I appreciate it.
I appreciate it.
Thank you.
And, and I think that the, the peoplein the company appreciate it cause it's
really them and they're freaking awesome.
Very, very lucky.
Very blessed.
Got a cool crew.
Steve (46:42):
Oh,
Fred (46:43):
So when are you coming down to Miami to visit?
Check out a basketball game if you want,
Steve (46:46):
You know, that sounds like a great time.
I will definitely, uh, I'll, Igotta talk to the boss, the, the
wife, and, and figure out, yeah, Igotta figure out when I can do it.
Fred (46:57):
one of the cool things about the Kaseya Center is there's so
many pictures of Cooper in therebecause, you know, we get to.
Do it.
So we're, now we do a lot ofwork for animal charities and dog
charities, and that's a big personalcause of mine and our companies,
and it's, it's a great experience.
So we'd love to have you downand, and really appreciate the
opportunity to be on your show.
Steve (47:16):
I would love that.
I, I so much for coming on.
Uh, thank you for being a guest, and I, Ilook forward to what Kaseya has to come.
I think you guys have a bigannouncement later this year.
Fred (47:26):
Yeah, we have, uh, we have a big customer conference in Miami at DattoCon,
and I assure all your listeners, The,the announcement that we're going to
make will be the largest announcementimpacting the most MSPs, impacting
(47:46):
the profitability of the most MSPspossible, and there'll be some nice,
there'll be an acquisition with thisone as well, so this'll be a lot of fun.
Steve (47:57):
Awesome.
You, you know, everybody'sspeculating it's ConnectWise.
Fred (48:02):
ConnectWise is a great company.
Uh, Jason McGee is a great guy.
I'll tell you a story about Jason McGee.
This is going back a long time ago.
He and I were both in New YorkCity in the late nineties,
like just starting our careers.
We were like young whippersnappers.
And Jason was my younger brother'sfirst boss, uh, at a company
called Interactive Futures.
(48:22):
It was a, it was a VAR run bya guy named Steve Scherr and,
and McGee was really good then.
He's, he's a talented guy and hewas so good to my younger brother.
I will never forget that.
So yeah.
ConnectWise, great company.
I'd love to work with Jay again.
Steve (48:39):
Well, thank you so much, Fred.
Uh, I, I really appreciateyou coming on the show.
Fred (48:44):
Awesome.
Thanks for having me.
Take care.
Bye bye.
Popular Podcasts
Stuff You Should Know
If you've ever wanted to know about champagne, satanism, the Stonewall Uprising, chaos theory, LSD, El Nino, true crime and Rosa Parks, then look no further. Josh and Chuck have you covered.
The Joe Rogan Experience
The official podcast of comedian Joe Rogan.
Dateline NBC
Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Special Summer Offer: Exclusively on Apple Podcasts, try our Dateline Premium subscription completely free for one month! With Dateline Premium, you get every episode ad-free plus exclusive bonus content.