[music]
>> Matt Bloomberg, one of
my distinguished guests on Pale Blue
Nexus, has joined me today. Matt, I
haven't figured out where you live from
geography-wise, but it looks like maybe
the northeast, but it well welcome
welcome to the show and kindly give
yourself an
introduction.
>> Thanks, Johan. Good to see you. I live
just outside New York City. So, good
call on the northeast.
You would not know from my backyard that
I live 7 miles from New York City.
>> [gasps]
>> I don't know what it was. I think it
might have been the evergreens cuz I
they're very familiar to me.
>> Yes, it is that it is that time of the
year.
>> Yeah. [laughter]
So, well, welcome. Glad to see a fellow
northeasterner. I'm up here in Toronto.
So, um good good to have you on the on
the show today. Tell us about Mark up
and and your role in it and it's it's
it's an older company, isn't it?
>> It is. Yeah, it's a really interesting
story. So, I'm the CEO of the company's
called Mark up AI.
Um and I've only been at the business
for about
a year and a half. The company is 25
years old.
And it has a really really interesting
story. Um we
got started
in 2002
um as a carve out
from something called the Berlin
Artificial Intelligence Institute.
>> Wow.
>> 2002 is a long time ago and there was an
academic institution in Germany
called the AI Institute.
Um and that's where the [clears throat]
company's original technology was built.
Um the company got carved out. It was
called Acrolinx, and over the course of
I don't know, 20-some odd years, built a
really, really compelling business on
top of a unique natural language
processing stack. So, in fact, it was
AI, but it was AI before large language
models.
>> [snorts]
>> Um and um
the company made a decision in uh 2024
that um almost all of its customers were
in the US. Uh and that the business
really needed to pivot and become a
contemporary agentic AI business. Um so,
the board uh went through a search
process and found me. Um and I joined in
early 2025. I brought in
um a lot of folks uh that I've worked
with over the last uh 15 or 20 years
across multiple companies uh in the tech
space.
And basically uh we uh built and
actually just last week launched our new
platform. Uh so, we renamed the company
and the new platform is called Markup
AI. Um it's a really powerful uh agentic
AI platform
uh to help the enterprises keep their
content safe
uh and ready to publish.
Um so, we have agents that do brand,
uh accuracy, compliance, and AI search
visibility.
Um and that's our platform. That's our
business.
Uh we cover any surface imaginable uh
because we're available through MCP
server, through API,
uh and through a Chrome extension that
integrates with just about every
application you can imagine.
Um so, [clears throat] we work with
writers, we work with editors, we work
with large companies across all
verticals.
Uh and again, the the the the story
behind the business really is
um content is the next code.
Um the infrastructure layer around
coding assistance is pretty well
developed at this point. Content is
where most enterprises are now turning
their attention in terms of getting
their true power of large language
models
um and the productivity benefits that
that come with them.
But like the early days of LLMs with
coding,
um
there are lots of guardrails missing.
>> [snorts]
>> Um so that's what we're building and
that's what we launched last week. And
we serve about 120 enterprise customers.
Mostly large Fortune 500 Global 2000. Um
that we're now migrating from our NLP
stack over the Aigentic stack. Um and we
are uh open for business for smaller
companies as well. The new stack is
super easy self-serve. A single user can
onboard and get going in minutes.
>> Wow. So So tell me some of the benefits
that your customers are experiencing for
from using
Markup in the Aigentic stack?
>> Yeah, it's it's there is a productivity
benefit. Um there is a um um we saw a
very clear ROI benefit. There's a a real
quality benefit. Um and there's some
benefits [clears throat] that I always
describe as the previously unthinkable.
Which is really the magic of AI, right?
It's It's not just that you do things
faster, it's that you do things you just
couldn't do before.
So um
let me give you a couple pieces of color
around that. One of our clients
um really succinctly put it the other
day. She said, "Look, we fired all of
our writers.
We put it all in the hands of um LLMs.
And now my team and I that are left
spend 80% of our time fixing content
that comes out of LLMs.
Um so LLMs have turned people from
writers into editors.
>> Yeah.
>> Um so using our platform, we really
streamline that process. We can fix a
tremendous amount of content. Our agents
using deterministic rule sets. Um we
know when to put uh the human in the
loop uh if there's something that
requires their inspection as opposed to
just fixing.
So all that's around quality and
productivity. Um and the kind of thing
you can do with us that you you couldn't
really do before. Uh so what I call the
previously unimaginable.
Is you can use our API to check a
repository of content of
>> [clears throat]
>> limitless size. Um so um I'll give you a
couple of examples. Um
one of uh one of our clients told us the
other day, "Oh, we just did this big
acquisition
and the brand of the company we acquired
is all is all off. It's not our brand.
Um can you know, can we use you to fix
the brand?"
The answer is yes. We can scan 5 million
pages
um of support documentation of marketing
for that brand um and flag everything
that doesn't conform or needs to conform
or fix it automatically.
>> Amazing. And may I ask, do you do this
in the cloud or do you do this on your
own uh servers?
>> Um
we I mean we're we're we are native
cloud-based application for sure. So we
we run in AWS instance um and um and
that that's where everything is is
located, but obviously the um
uh we do draw on the LLMs and we do most
of that through AWS Bedrock.
>> Okay. Yeah, I guess uh
my one of the things I've been toying
around recently is like with
uh open-source models and things like
that and I I don't know where you stand
on that, but uh you sound like you're
you might be using some frontier model.
>> We are, yeah. Yeah, we actually use
different models um
uh we um
uh you know, we have lots of different
agents and different cases and um one of
the um sort of value props we have to
clients is um that we make sure that
we're using the right model, the most
efficient model and that anytime we
switch models,
um we are doing all the exhaustive eval
work to make sure that the the output is
consistent for the customer. So we have
a lot of things running on Gemini, we
have things running on Anthropic, um we
have things running on on some of the
open-source models as well.
>> What kind of evidence
do you gather uh
to say like you're helping your customer
with
uh
guarding their content, for example?
Like how how do you prove that?
>> Well, it's fairly um easy with our uh
analytics and reporting module uh
because everything that we do for a
client's content, what we're doing is
we're checking their content against a
particular standard.
>> Mhm.
>> Um so, the reporting and analytics just
comes back to how many things did we
catch and fix against against a given
standard. So, um I'll give you some
examples. So, for Brand, which is one of
our swim lanes, um the uh standards
could be a company's terminology
dictionary or glossary of preferred
terms, or it could be their brand and
style guide. And some corporations have
brand and style guides that are hundreds
and hundreds of pages long.
>> Yeah.
>> Even smaller ones have brand and style
guides that are 20-30 pages long.
So, anytime we do a pass at a document
or a webpage and correct it, we can say,
"Oh, we found 82 errors. We fixed them."
Um same thing if we're doing compliance
checking
um
for a particular law that the client
cares about based on its jurisdiction or
its vertical,
how many things did we flag for human in
the loop?
Um similarly for AEO and GEO, sort of
that AI search visibility, how many
things did we find, flag, and fix that
are going to improve um AI search
visibility. And then the same thing for
accuracy, uh when we do accuracy work,
how many things did we find and flag
against the deterministic source that
needed to be corrected.
>> Right.
Well, I thought that
>> And our system our system rates
everything low, medium, high. Um so,
there are a lot of things we find that
like, all right, great, we put another
comma in.
Okay, you want your content to be
consistent, but no one's going to get
fired because the comma's missing. Um
that's a little different than a
pharmaceutical company putting out
marketing that doesn't actually speak
the truth about the drug,
where someone could get fired or someone
could die. So, uh you know, that's a uh
an extreme example
on either side.
>> What do you think about the I talked
about this on a on a taping yesterday,
but like the agent-to-agent economy and
people are talking about
you're going to be talking and your
brand is going to be represented by
another
uh
is going to be assessed by a agent um in
at some point in the future.
So, it may not be a human reading the
webpage anymore.
>> Yeah, I mean it is
it's an interesting world. Like they
talk about the metaverse, I guess.
The
a lot of people are starting to talk
about this sort of two-track internet,
the human-to-human and
machine-to-machine and and the crossover
between those two.
You know, the
reality is you can do some things to
optimize your content for machine
readability, but most machines are
trained to read human content and
actually look for signals of human
content.
>> Right.
>> Um so, we have agents like the AI search
and AI visibility agents that know the
rules for AEO and GEO and will will make
the text conform to those rules, which
sort of gets to machine readability. But
if you really look underneath the hood
with those rules, a lot of those rules
are about the content being authentic,
about being fresh,
about
being accurate, and all those things are
are human rules. So, I'm not sure at the
end of the day that this two-track
internet is exactly going to unfold the
way it sounds,
but to the extent that it does, that
just means that people are going to need
to version their content A and B.
>> Right.
>> that's what our agents are designed to
do.
>> You mentioned the word metaverse. Did
you go through that that whole cycle?
>> I don't mean the metaverse.
But it is it is uh let's call it a a
multiverse.
>> Right. Right. Uh did you did you go
through that sort of cycle with NFTs and
metaverse just randomly at
>> Personally, I didn't engage that much in
it. I mean, I know what all that is, but
um uh I my my businesses have always
been a little more boring than that.
>> [laughter]
>> Yeah, so
uh speaking of which, um Matt, what do
you do for for fun as a as a father and
as a CEO?
>> Um I have lots of fun in lots of
different ways. I've got three great
kids. They're late teens and uh I love
having fun with them. Uh it's great to
have everyone home for the summer from
the different uh schools that they're at
and uh um one of them likes to golf and
so do I, so we do a lot of golf. Um
a couple of them like to watch movies
and uh we do a lot of that. Um and um
love hiking. Uh love spending time with
my wife. Um
and uh I would say sort of the
intellectual interests for me are have
always been around uh American history
and politics. Uh so I exercise that one
in lots of different ways. I'm I'm doing
a lot of vibe coding at the moment. Um
so
like uh like to keep busy.
>> The thing about history is like I never
watch historical movies because I know
the the the movies are written by the
winners and it's like I don't want to be
lied to, right? So, how do you tell in
history what's real and what's not?
>> [snorts]
>> Um you know, I I think with all content
um
and and increasingly so with with AI,
all content um
>> [clears throat]
>> people need to bring check with healthy
skepticism to it. Yeah. Um and really
understand how to look for
um
you know, look for uh signs of
credibility. Um
it's one of the things I wish schools
taught kids a little bit more.
Cuz I think the internet has kind of
done a lot to to break that um
in in lots of ways. So, I you know, I
feel like I have pretty finely tuned
radar at this point, but I worry
sometimes that that
teenagers don't. Although, quite
frankly, teenagers are pretty good at
spotting video fakes
in ways that
you might not catch as as as an adult.
>> Yeah, teenagers are good. My my my
5-year-old isn't as good. He just
watches these cat videos that the cats
are doing all of these weird different
things and you can you know it's AI, but
he doesn't care. So.
>> Yeah.
>> It is it's it's a weird world.
Back on track to to to
to mark up.
Um you guys lean on the Gartners
Gartners
sort of certification. Talk Talk about
that and and and what that means for the
future of content.
>> Yeah, absolutely.
You know, we So, Gartner sort of coined
this term guardian agents a while back
and it was it was as we were really
building out our solution. We spent a
lot of time with with Gartner. We're a
client. We do a lot of briefings. We do
a lot of inquiries there as well. And
those guys are super smart about
software world and you know, their their
point
and sort of the origin of the term
guardian agent is that the only thing
powerful enough to check AI is AI.
>> Right.
>> And which is I I always say like the
only thing strong enough to cut a
diamond is another diamond.
>> Yep.
>> And
that's the the the the term guardian
agent. So, AI to check the AI.
And you know, the reality is our agents
will check human content as well, not
just AI content, but
but the power comes in when you're
checking
you know, kind of hundreds or or
thousands of things or millions of
things all at once that you really need
AI to do.
>> And there's like a there's a concept of
a deterministic trust score when you
have AI
track AI or or check on AI. Explain
that.
>> Yeah, I mean all of our agents have um
algorithms that score. Um we uh most
often, unless a client really wants to
get granular and see a zero to 100
score, um we will bucket things into
low, medium, and high risk. Um and that
that tends to do the job for most
clients. The high risk has to be human
in the loop. Medium and low risk just
fix. Um but uh but you know, any any
determinism can come with an algorithm
that produces a score.
Uh and uh you know, again, back to my
earlier example, if a comma is missing,
it's not going to be that big of a deal.
Um if you are saying something that's
out of compliance with a claim
substantiation law, uh that's going to
be a real problem.
>> And is there like some way to check what
you guys have done? Like is there like a
a false negative or check or anything
like that for you guys?
>> have agents that check our own agents.
Um
uh yeah, so there is there is an extra
loop on that.
>> Amazing. Uh
definitely you're you're you're
marketing and selling safety and you're
checking yourselves. Uh
so I think that's amazing. What what are
some of your future
>> we're selling safety
um and confidence. Um but we're also um
you know, I think selling productivity.
Um and in the case [clears throat] of of
search AI search visibility, um you
know, we're selling a revenue driver. Um
if companies you know, if your your
content can't get found, you can't get
found.
>> I absolutely believe in that. The the
the sponsor of this show is is Huckabuy
and they are in the search visibility
phase. Let maybe let's talk about that a
little bit. Um
where do you think this space is going?
Obviously, the old uh world of Google
search is no longer there with with AI
results coming above the fold um and and
most people using AI to
discover brands these days. What is your
uh take on that?
>> I mean that's that's here to stay.
You know, it's interesting because you
look at
you know, you look at the different AI
services and they really the quality
varies pretty widely
you know, when they default you to a an
old model or if you decide you're going
to use an old model because it's
cheaper.
You're going to find stuff that's out of
date.
People who use things like perplexity
which are like up to the minute rag
optimized are finding things that are
really current.
Freshness is a real test that you want
to use with that. But you know, I think
whether it's Google layering in Gemini's
output or people going straight to
perplexity or something else. People are
just going to increasingly be
you know, turning to AI to look for
things and you know, I mean the results
the difference in the results is
incredible.
You you ask perplexity a question you
get back a table comparing five
different products against the three
things they know you care about. That's
a pretty big difference than than
getting a page of links which is sort of
the old old school work. So Google's
obviously figured this out too. It's
sort of you know, a 10 up top.
But I'm not sure that's exactly the best
engine for that output at least today.
Google's got plenty of resources. They
can make that better and better and
better.
>> And you know, the old way is paid
search.
How does that get translate into this
world? Do you see a path ahead for
neutrality there?
>> Yeah, I mean that's that's interesting
when you think about it. You know, I
would say the current regime is that
paid search is getting a little less
impactful.
I expect that will change over time
because economics dictate that it will.
But I you know, I could be wrong. Look
if everybody starts doing you know, $20
a month subscriptions to these things
you know, to use their preferred one and
to use it in a memory focused mode.
Maybe not. I mean the reason that paid
search evolved is that search is free
and chewed up a lot of compute and a lot
of everything at Google and Yahoo and
Microsoft.
And
you know, SEM was a really good way of
of recouping the cost of that.
You know, if the world moves to
subscription model, maybe that doesn't
need to be there. My guess is even if it
moves to subscription model, you'll
start seeing that in
search results and you know, hopefully
that will evolve the same way the SEO
versus SEM world did where things are
flagged and at least you know what's
sponsored versus what's organic.
>> I like that
insight very much. I think like maybe
everybody will have a $20 a month
subscription just as they have car
insurance and uh
>> And
and my guess is more than one.
>> [snorts]
>> Um you know, they'll have probably $20
ones and then they'll have the $100 one
for the max work.
>> Right. Right. It it it certainly
I do. I have couple and I have $20 ones
too. So you're right.
Talk about the world of I guess search
in a year's time or two years' time.
Where do you think it's going to go?
I'm interested in this question as well.
>> Yeah, I am you know, I'm not really an
expert in search. So I don't know that
I'm the best person to ask. I mean, I
would say um
uh
the data would suggest the public data
would suggest that Google's not losing
share.
Hmm. [snorts] I find that a little hard
to believe.
Um
and I don't I can't reconcile that
though. And the only reason I find it
hard to believe is that there are a lot
of people I know that are using the the
different models not Gemini for search.
Um and I know maybe I know a really
small segment of the population, but um
and Google certainly built a reflex over
the last you know, 25 years
that that included a verb Google. So
um
Uh so, I you know, a little unclear to
me, but there there has to be some some
fragmentation coming.
Um but, you know, you never know with
big tech. Um
you know, Perplexity could start eating
share, and all of a sudden someone buys
them.
Uh and that could be Google, you know,
doubling down if they're allowed to uh
with antitrust. Uh or it could be
someone else that decides to um you
know, to really to pick up that user
base, pick up that technology, and and
um
it's I think it's I think it's
impossible to tell.
I think quite frankly, it's impossible
to tell where anything is going beyond a
few months out
uh because the pace of change and the
pace of development is like nothing I
have seen in my career in technology.
>> Well, and the one thing,
you know, markup is it is is policing is
is the it sounds to me like the
avalanche of AI slop that that's that's
coming out there, and and we all see it.
It's there there's a bunch of stuff uh
on your LinkedIn feeds, on your
everywhere. And what is your, I guess,
take on that? Like, how do you feel
this AI slop problem
uh will be
I guess, dealt with?
>> Um well, hopefully we deal with it. Uh
and the world turns to us to deal with
it. And uh you know, we built a business
that's really easy to embed in lots of
other solutions. We are not a monolithic
stand-alone thing outside of workflows.
Um but, um
you know, uh but realistically, not
everyone in the world is going to use
us, and I don't know. I mean, it you
know, AI automates bad behavior. Um and
the reality is the internet automates
bad behavior, too. Um and I'm not sure
everything has been solved around that.
And uh I don't think everything's going
to be solved around AI slop, either. Um
maybe the uh maybe the
machine-to-machine reading will will
either mean that it's not a problem
because they can cut through slop, um or
uh surfaces the problem more efficiently
to solve.
>> What do you think about AI influencers
and user-generated content?
>> Um, there are a couple of them that I
follow,
who have really smart things to say, and
who definitely influence influence us
here that are I would say they're you
know sort of more
power enterprise, you know, B2B
influencers.
I don't focus a lot on B2C AI
influencers, and I don't know if there
if there are any. There probably are
some. Um, but you know, the thing with
AI is
again coming back to the previously
unimaginable, it's really about power
users exploring and pushing the
boundaries and then recording what they
did and what worked and what didn't
work. So a couple of people
[clears throat] that I pay attention to
are like Camille Bach or Bank, B A N C.
Um, Nate Jones. They both have really
good substacks,
um, where they just go into like either
what they did something they did that
worked, something they did that didn't
work, or something a client of theirs
tried.
And those those end up being really
really helpful.
>> Matt, what's the next
6 months to a year look like for Mark
up, and what would you consider
this 2026 being a great year capping
off? What would happen there?
>> Well, we launched our platform last
week. So the rest of the year is all
about adoption.
And for us that's
moving our legacy clients over as well
as selling new clients. We're off to a
great start on both.
So it's early days and and therefore
adoption matters and and obviously
client impact and results.
Um, and you know, our road map is is
fairly straightforward. More surfaces,
more agents and functionality, deeper
memory,
so that every client who uses us and
adds another agent, another surface, or
another employee to the team, uh
capabilities are just better and better
and better.
>> Well, where can we keep up with you
guys?
What is your most active channel? And we
definitely will have my audience follow
you guys.
>> Yeah, so Markup AI is the name of the
company. My email is matt@markup.ai.
LinkedIn is probably our most impactful
channel, but we do have a blog that you
can get off of the website markup.ai.
And yeah, lots of lots of new product
coming out every week.
>> Thanks, Matt. It was a It was a pleasure
having you on and I learned a lot from
this interview.
Please hang on after and we can have a
little chat.
>> Sounds good. Thanks for having me on,
Johan.