Music.
Dot io your podcast and youtube
blog covering the german startup scene with news
interviews and live events hello
and welcome everybody as you hear him laughing in the background today i'll
bring you another startup interview today with caston carsten is an entrepreneur
um co-founder of Casablanca.ai. We'll talk about it soon.
He has been an entrepreneur since age 16 and also is the business angel of the year 2024.
So-called the golden nose because you can sniff pretty good investments.
But we'll get to this afterwards because this is part one of a two-part recording
because usually we get through something like 20, 25 questions.
And I was preparing for this interview, I was getting to almost 50 questions
and I was like, that may be a little bit long.
Let's cut this into two recordings. So, Karsten, welcome.
Yes. Hello. Now from Zanzibar. I'm currently on holiday, but I'm very happy
to do this interview with you.
Oh, very nice. You're doing a sundowner at the Africa house?
No, not the Africa. I'm somewhere on the south coast of Zanzibar.
And I want to go diving tomorrow. So I'm going to do the sundowner.
If we finish in time, I'm going to do the sundowner on the jetty here, which is also very nice.
And tomorrow morning, I'm going to do some diving and hopefully also see some dolphins there.
For everybody who's not been there, Sanzibar is strongly recommended.
I spent a part of my honeymoon there with my wife. Wow.
Yes. We also may tell that this interview is in association with the Business
Angel event back in 2024 with the German Business Angel Association Band.
Let's dive right into the interview. You built your first company with 16.
What did that early experience teach you about entrepreneurship that still applies today? Okay.
I think the most important lesson for entrepreneurs is let's do it.
So don't get blocked by whatever rules, obstacles, something that you might
not have and it would be better if you had it.
Of course, it's always better if you have more, but if you don't start, you don't start.
And so the most important thing is once you have a really good idea, you just do it.
Not quoting an international apparel client here.
Now, some people, because we do know, we're usually pretty popular,
8.35 and up, some people will get nostalgic because you sold a company to Atari
back in the days, very popular.
And a lot of people will get, oh, yeah, I remember those games with the joystick and all that stuff.
Oh, yes. Can you tell us a little bit the story of selling Omicron Basics to Atari?
Because it was a major milestone in your life, right?
Yes, it was, yes. So the key thing was we invented or I invented new architecture
for programming languages.
And so principally new structure, how to build a programming language interpreter,
and built this together with two friends.
They wrote most of the code and we were 70 times faster than what atari had at the time,
for their atari st computer series so that was a new processor from motorola
with a 68 000 processor very fast processor that was also used by unit packet
and some other um high-end manufacturers,
and atari and also the apple mac and atari launched a computer for about 1500
at the time that was like one-tenth of the price of the unit packet and one-fifth of the Mac price.
And we launched a new programming language which made it faster than all the
other machines with the 6,000 to 8,000 processor.
And we first sold it separately and then Atari offered to buy it from us and
we had hard discussions and they negotiated very well.
And in the end, they bought it from
us and they bundled it with all their machines at the time. Thank you.
And the processing capacity one computer had there at the time you now have
on a smartwatch, I assume.
No, smartphones are far beyond. So when you take a look at… No, smartwatches.
Smartwatches, yes. So probably, yes. So my comparison actually is when you take
a look at the computer that brought the Apollo 11 to the moon and you compare it.
So many people have an iPhone. Now, don't compare it with the iPhone.
Compare it with the charger of the iPhone.
And the processor built into the charger that controls the voltage is about
the compute power of the Apollo 11 computer.
Okay, I see, I see. Getting to the next milestone in your life,
FactFinder, scale to 2,000 plus online shops.
What was the single smartest strategic move you made that led to this success?
And can you tell us a little bit about what FactFinder is or was?
Okay, so you mean an additional strategic move just outside,
just building by far the best search technology at the time.
Because that was also very important, I think, because else it's difficult to
sell something if you're a small company and nobody knows you.
So what did we do? We built a search technology in the year 2000.
I actually built the prototype with an intern.
So the intern coded I did the algorithms in six
weeks and the prototype showed
that we can solve this the question of
how to find things that are misspelled better than
anybody else it was the prototype was very
slow and we had to make a lot of additional inventions which
were made mostly by my best programmer armed at
the time to have it fast enough but
I could show that we have an
understanding if that was also ai it was just not machine learning and understanding
how humans perceive similarity and how we can represent this in the computer
so that was the new thing in fact finally in the year 2000 two years before
google launched its did you mean and did you mean from google.
Had a totally different approach they just asked millions and millions of users,
did you mean this and then if they said yes they uh
they they saved the synonym so they saved
like this is in in fact that and this is in fact
the other thing and they were very often wrong in the
beginning but then they improved with all the users
and that was a totally different approach and we solved it
from the ground up we didn't have the resources we
didn't have the millions of and billions of users um so
we had to do it with ai and we did in the
year 2000 and we solved the similarity problem with
for misspelling things so um what was
the most uh important strategic decision besides the
very very good product um i think
the most important thing was that i started uh not offering
it for sale only but also for rent because we
were a small company with seven people at the start i had
some other products before but then i started fact finder and we put a lot of
resources in that was almost killed us um and um and then people did not trust
a small company so um if we said it costs up to 60 000 deutsche mark to buy this so that 30 000.
Um many were still reluctant at the time because e-commerce
was not as big as now and things were not so important as now and not so expensive
as now and um so people were reluctant i said okay i can offer this for rent
you can you can rent it instead of buy it and you pay only one and a half percent
of this amount per month and um.
So, of course, so four and a half percent per month, four and a half percent per month.
So after 22 months, this pays off the full purchase price. So you should switch after a time.
And we offer until half a year, we offer you to deduct 75% of the rent you have
paid from the purchase price.
And so people said, OK, I can decide this. I can risk that and we will test
it. and we just throw it out and cancel it immediately if it doesn't run in
practice, if it doesn't run well in practice.
And so that reduced their threshold a lot and made us also trust us because
they said, okay, if they are offering it for rent and not for purchase,
that means that they believe that we will keep it.
So it was in both directions. It was good for trust. And because it was so good, everybody kept it.
And some purchased immediately after a month and some actually
tended to not buy it because they
were CEOs who did not own the company and so they said it's better for my bonus
if this year I don't have the full purchase price on my expenses and just the
rent and that's how I kind of invented ZAS but we didn't call it ZAS,
we called it software rent at the time,
that was quite new Because software as a service was not usual at the time.
That was very, very uncommon.
I see.
You obviously do a lot with Omicron Basic and FactFinder.
You had two huge successes early on. And you also do have 25 patents pending.
I would be curious. Some pending, some still granted, yes. Ah, okay, okay.
How do you get to all of them? And if you could just pick one that would change
an entire industry, which one would it be?
So actually, I have lots of ideas which just keep coming when I'm under the
shower, going through the park, when I'm sleeping.
I suddenly wake up at night, have to write something down, then fall asleep again.
And sometimes I make a pattern out of it. not all of the ideas are worth a patent
because some are just rubbish commercially,
some are also not good ideas technically, and some have already,
many have already been invented by other people and just not put into practice by them.
So I have patents, for example, a granted patent for a new, for a new online,
sorry, on-screen keyboard, which will make significantly,
less miscorrections. So very often you type something, you mistype and you get
a correction and the correction is actually worse than what you mistyped.
And I have a granted patent to significantly improve this by some additional
measurements which I do because I get more of the intent the user has rather
than just the characters he types, he or she types.
So that's a granted patent where I have not actually started developing yet
because I don't have the time to build up a new company right now for that.
I have other patents also for understanding if a picture is reality or if it
has been manipulated, which also applies for pictures which are in printed magazines.
So you can use this on printed pictures as well.
And there are several other things where I have not built a company yet,
but they also might do a lot of good for the world.
So which is the one pattern that can change entire industries?
I think most of my patterns don't go for one industry.
So like when you look at Casablanca, it has the potential to disrupt video communication throughout the world.
So in all industries, but of course, video communication is just a small part
of the work, mostly of the work for internal meetings, sales, recruiting.
But it's not for, for example, for production, not for fabrication.
It's not for programming. It's not for all these things that produce the things.
It's just for the communication. But of course, communication is also an important part of our lives.
So Casablanca can disrupt video communication, but it will not be limited to one industry.
Same goes for things like this better on-screen keyboard.
It's also not for one industry, it's for many industries.
I see. Given that you have so many ideas, built so many successful companies, when?
When do you decide, now it's the time to implement one idea or step away from
something and sell it or give it to another leadership team?
That depends. So in some cases, I have an idea and suddenly I find somebody
who would be the right person to implement that idea.
And if I can get hold of her or him, then I start a new company with them.
So that can be one point when I start.
With Casablanca it was different, so I decided I sell FactFinder in order to start Casablanca.
I wrote the patent, I registered the patent, I still had not sold a FactFinder yet.
But I knew I needed to shift my attention to that project because it's a huge project.
It's a huge work also to get it done. And I underestimated it,
even though I thought it was a lot of work.
I thought it would be like one year for five people. And it took us four years
with five researchers plus me, so six people in total maybe.
But the researchers are doing more of the new patents than I did.
So in total, we are 20 now with Casablanca, so including people like marketing
and administration people and so on.
And besides the researchers we also have developers now because we wanted to
implement the software and not only build the technology,
so sometimes I have to dedicatedly start a new company and sometimes I can just
pick the chance and do something so I just started the biggest German AI.
What's the thing in English uh,
I just started the biggest German AI directory called alles-ki.com.
And I had this idea several months ago because I thought the ones I had seen
in Germany were all so small and so difficult to find things.
And also the American ones were not so easy to navigate and not so easy to find
the solution you actually need.
And with alles.ki with our german ai directory which is also usable in english actually,
we have built everything on an ai stack and when i had the right people i started
that was in october and i did some pre-tests before if my ideas work my ai ideas
but but then i had the right people together.
And we started with two people. Currently, there are three people in there.
Besides me, I only put very little work into it. Mostly it's the other people who do it.
So I mainly had the idea. But so sometimes it's this way. Sometimes it's the
other way. It depends on the idea.
Sorry for our audience. We have some very bad internet connections here.
And actually, I can only understand all of the stuff Carson is saying after
his file is uploaded. so not during the video.
Really sorry about that. But my next question is, many startup founders focus on scaling fast.
What's the biggest mistake they make when trying to scale quickly?
So actually, I think there are some people who do it excellently.
And I'm just a mediocre scaler, I would say.
So I'm not the worst, but also by far not the best. There are people who really know how to do this.
And so in terms of scaling, I would love to learn more.
But some mistakes that people make at the very beginning is not being dedicated enough.
Also, not starting quickly is often a mistake.
If an idea is somewhere already somewhere in the air, and then you wait until
you have more resources, more something, more something, then somebody else will just do it.
So you can save the most time
in the very beginning of an idea when you're when
you're the first one to do it of course you will get people
who copy you and that's there's
you have to prepare for that and maybe the idea is
just not working and somebody else does it much better but
generally it's rather like start fast I
think that's the that's a big mistake that people wait
too long and until they start and then
of course you have to be able to make mistakes and you have to
understand that everything you do when you build when
you scale a startup everything is an experiment and that
means many many things will go wrong not just.
Some things and it's not so error
tolerant work in in german companies normally
is seen as yes i accept that sometimes people also
make mistakes this is not what we're talking about I'm
talking about people do experiments every day
and many of those experiments don't work so
they don't just sometimes make mistakes they consequently make mistakes and
you have to accept that many things go wrong so in marketing especially but
also in lots of other things you just have to accept this what you don't have
to accept and you shouldn't accept is mistakes out of negligence.
Mistakes out of laziness and so on.
But mistakes out of you think this is right, but you were wrong and thinking it's right.
That's mistakes you have to learn to accept when scaling company,
else you cannot scale it. So bottom line is do mistakes, but learn from them.
Yes. But be prepared that many, many things go wrong when you start something.
Aside from Casablanca if you
were to launch a startup today what market or problem would you go after?
So if I would,
launch something just because I want to launch something, not because I have
a specific idea, because if I have a specific idea, then I would do that.
So, but generally I would build something on the basis of AI technology that
is here and is going to be available easily for the next year. So like LLMs.
And the problem is of course that everybody does this.
So what you need to do, and I wrote this in an article also.
What you need to do is you have to find some niche where you have more expertise
or more knowledge, more data or something else that other people don't have
or more market access where other people don't have this.
So when you build something new on the basis of, let's say, a large bandwidth
model or some other AI technology, it could also be like object identification or other things,
but you build it on top of an AI technology that's easy to use and there are
many AI technologies right now which are easy to use so they have APIs,
it's easy access, you can use them without much difficulty,
and then you just go for some niche where you have the better market access
than anybody else or the better knowledge or some data which nobody else has
and so on so what I yeah okay so this kind.
Of company is not a world changing company in in all industries this is going
to be something that changes a specific,
industry or a specific topic probably because that's the thing where you have
more knowledge so um if you are the best person for let's say um uh,
spices or so then you build something built on
your knowledge of spices that nobody else has and maybe
your data on spices that nobody else has and your market access to spice suppliers
and maybe spice users which nobody else has and spice could be a big market
but it could also be something very specific like the pumps for fire sprinkling,
for fire watering or something. So it could be something very specific.
But you build it fast and you build it in your area where you have better market
access, better knowledge than anybody else.
And we just talked about mistakes, doing mistakes.
And I was curious, looking back, what's the biggest bet you've made that didn't
work out, and what did you learn from it? You're talking about learning from mistakes.
Yeah, so there are probably thousands of small mistakes I made,
and there are a few big ones.
And I would say the one that cost me the most money, where I went in the wrong
direction and stopped it completely.
So not just did a turn or something is
fact finder travel so the idea in the year 2011 was that we have sold fact finder
at that time to i don't know like a thousand something e-commerce shops 53 of
the top of the top 100 in germany and um,
There were no travel sites on it.
And the point is when you search for, let's say, an iPhone charger,
you type in iPhone charger or maybe iPhone charger for iPhone at that time, 11 or something.
And when you search for holiday and you type in Christmas holiday with my little daughter on the beach.
Then what you
would get with a standard keyword search is something where Christmas appears
in the text daughter appears in the text also beach appears in the text and
Christmas so the thing is keyword search brings you the wrong results because
that also might be something like.
Clothes on Christmas and the word Christmas is still in there,
so you would not want that so what you need is you need understanding of the
text and we produced the world first semantic search for the tourism industry
which really worked so we could find those things so we thought okay so beach
probably means swimming, swimming means warm,
where is it warm over Christmas and we reasoned these things at the time so
that was over 10 years ago and launched the product and the industry actually
was enthusiastic about us So
we got six customers within a few months who built it into their portals.
And what happened was the end users did not use it.
98% of the end users just typed in one word, one word like Mallorca or Caribbean or something.
And they did not type in long sentence because at that time they had just been
trained by Google that the best thing you can do for searching is type just one word.
And so they didn't understand what it was about and none of our travel portals,
really trained the users to change their behavior.
So we were only participating in success, so things that were booked at a higher rate than normally.
So if it was just as good as normal, we would not get anything.
And in the tests, we made tests in the usability studio. People were much happier
about our search, but after we explained it.
And so in Effect Final Travel, the end users didn't use it.
We got a number of prizes for the software. So we won like the innovation prize
of Deutsche Börse for the most promising startup,
which is going to be an IPO soon and so on.
So we got a number of prizes for it, for the innovation we made,
because it was really disruptive innovation again.
But we made €50,000 revenue and we invested about €1 million within three years
and didn't get the market running.
So we tried with some press releases and the press people just published the
funny stories but never published like, this is a game changer for you.
And we didn't have the money to really do TV advertising or so else we might have changed it.
So that was hard. and I stopped it after spending roughly $1 million in three years.
Okay. Talked about stopping that funding, talked about big decision management decisions.
What is your go-to decision-making?
Is it gut instinct? Is it data? Or do you have a certain rigid framework where
you make your decisions?
Yeah, all of them. So I do have two kinds of frameworks and one sentence to remember.
So if you do a big decision and you have thought about it for a while,
then the one sentence is never without your brains, never against your gut.
Yep. So that sounds reasonable. if you
cannot find a plausible reason so like when you calculate
it so that you should do it you shouldn't do
it so you have to have some reasoning why it
should be done and if it still feels bad even though you have the reason then
don't do it because your the gut feeling takes and takes in a lot more um factors
and you take the factors uh which you you can't you cannot reason over 20 factors,
but you can actually take your gut feeling for 20 or 50 factors because it will
take all this into account.
We'll be back after a short ad break and then we'll talk about Casablanca AI
technology, AI differentiation and your future vision.
Okay, guys, thanks for sticking around. Welcome back. Now we are talking with
the Business Angel of the Year 2024,
Carsten Krauss, currently in the first of two interviews about his most exciting
startup right now that he does himself.
It's called Casablanca.ai and it claims to be 20 times more efficient than Microsoft or Nvidia.
What does it do and what's the secret?
Okay so what does it do is simple so when
you do a video call normally don't look at each other you
normally look somewhere down on the side and so
on because you look at the other person on screen
you want to see their reactions but the camera is
somewhere else it's not behind their eyes their eyes where it should be so what
we do is we put a virtual camera behind the eyes no hardware it's just software
we put a virtual camera behind the eyes of the person you're talking to and
our software produces the picture in a way as if the camera would look from that perspective.
And what's interesting for me, it also enables you to do some eye tracking,
which you can also do with other competitors always to what's the camera.
So for recording, it's pretty interesting, but we have to admit it's made it
a little bit more for saving.
Bandwidth so therefore it's not for a
high for for high resolution recordings
like we're doing now it's not made for that yet okay yes so generally it's the
the Casablanca model is a we need to keep the model small in order to make it
fast enough that you can use it without an extra GPU on a normal current computer.
So an Apple M1 or a Pentium starting from end of 2022, beginning of 2023 is enough.
Or an AMD from that time also. So that's why we need to make it small.
And that means the resolution is not good enough for a high-quality video.
But in video calls, you always have bad resolution anyway.
Way so you don't see the difference so when
when you do a normal video call Casablanca is good
enough and it's fast enough to run on a normal computer so
why why are we so fast it's not only because
we have we we save time on resolution so it's also because we built a very very
efficient model and we could do that because and we build a much smaller model
than others do and we could build a smaller model because our model understands the faces better.
And when you have more understanding, you can compress better.
So if you have no knowledge of a language,
then you have just to listen and you have to record the audio and you have to
remember the audio by heart if you want to repeat it.
That's very hard. If you understand the language,
you can compress the audio to words and that's much less information bits you
have to put and you can just put much longer texts into the same kind of sequence.
And our model understands faces better than any other model.
And that's mainly because we have built a self-supervised approach and we have
built a new way how to build face models.
And thus we can make a very small model and this very small model also allows us to make it very fast.
And we will also launch higher resolution models, which will also be faster
than all other high resolution models.
But they will probably require a GPU if you want to use them on your personal computer.
Your AI technology also enables a realistic 3D phase reconstruction using minimal
data. How does this work?
So that's part of our small phase model. So it's a number of new inventions.
So we also made a new GAN, which doesn't need perceptual loss,
which makes it faster and at the same time better in quality, actually.
And we made a lot of inventions and registered a number of patents.
The first one has been granted. The others are still pending.
However, so to sum this up, what we do is we can compress a video picture of
a person. So all their expressions, everything they do in a vector of less than 300,000.
Data points so 300 dimensions of the vector and so if we have 25 of these vectors per second.
That would be seven and a half thousand data points and that's
fast enough for making a video call with this
compressed data over an
edge communication so there's a 2g communication that
will be it will be fast enough for that if both
sides have casablanca and it would be a direct
communication so it's currently not integrated into
this kind of communication into zoom or teams or anyone
but if they would integrate it they could enable video
calls also in areas like where I am now where the internet connection is not
so good or Germany where the internet connection is also not very good outside
the big cities so very often you only have edge connection and you always say
oh I can't do anything on the internet but now with So Casablanca,
if both sides had this technology and it would be built into video communication,
you could do video calls even with only this batch connection.
Every major tech company and non-tech company is investing in AI,
especially talking about AI-driven video communications.
What makes Casablanca stand out there?
Well, the thing we are solving, we solve best in the world. So making authentic
communication with a full face turning and eyes turning.
So all the competitors currently can only correct the eyes, but Casablanca corrects
the full face so that you have an authentic communication as if the camera would
be behind the eyes of the person you're talking to on screen.
So we're the only ones who can do this at the moment. That's what we do better.
But then how do we do it better by a lot of inventions again some have been
made by me but most have been done by my by my team of researchers and that's
actually one of my talents,
so i start with an idea and then i find
people who understand the details even better
than me and i can understand if they
do or they can't because mostly the ceo
does not understand enough technology to to realize if the person who claims
to be an ai expert is just okay with ai or really good and i'm one of the few
ceos who can do that and i've done this all my life so all i've,
mostly i have made some part of the invention myself,
uh where you needed a lot of things to come in together but for um that that
does not complete the product so also in fact finder as i told you the um we
started out with this very slow,
um implementation which already showed that the idea of how to how to represent
similarity in search is really understood well but in order to get the speed
somebody else had to do it and there had to be a lot of additional inventions.
And I find those people who make the details, who it's not a small detail,
it's an important detail. Speed is essential.
And I find those people and I can decide if they are really so good or not.
And I bring them together and I make them work together and I make them work
with me also, but also work together very well.
So I think that's my secret sauce here.
I've done this all my life in all my companies.
Apple's FaceTime now offers an eye-powered gaze correction. Why is Casablanca a better solution here?
As far as I know, Apple only corrects the eyes again.
So that means it works well for a small angle, if you have a very small angle.
So you're like on a smartphone, normally you're like this far away,
and you talk, and then the angle between the eyes and the,
And the camera is very small. And if you correct only by a small angle, just the eyes.
So I'm trying to simulate this now.
So if you do a small angle, it looks good. If you do a big angle,
it looks crazy if you just correct the eyes.
And so it looks like this is a different emotion you're showing. Yes, yeah.
Yeah, so yeah, maybe that. But even if they don't appear on your head,
if they're just correct, But just looking at somebody from the side is like,
oh, he's giving me a side-eye view, so what does he want to say? Is something wrong?
Is he not believing me? That's also a mimical expression when you look from
the side. And you don't want this.
You want the true mimical expression. That's the essence of communication.
We humans are so fine in reading all the small movements of the mouth, of the eyes.
If you move the lower eyelid half a millimeter down, people say, oh, now he's skeptical.
Or he's ironic when you move it further down. So there are some things which
are very small mimic changes, making an expression.
And you want to avoid this. And Casablanca changes or corrects the full face
so that you don't have this involuntary eye expressions.
And it works well when you just correct the eyes if the angle is really small
and it does not work well when the angle is bigger, like when you have an additional
screen or even just a big notebook screen.
I was wondering, seeing that you put so much thought, so much energy and so
much future potential in this company. What is your ultimate vision for Casablanca AI?
Is it an IPO, an acquisition, or a long-term standalone company?
So the first vision is like in five years, nobody will remember how video calls
were before when you had no eye contact.
So I want to improve the world here. So, I mean, people will probably remember,
but they say, oh, yes, long ago it wasn't like this.
And so that's my first vision. And then I think I will go with what is a good
offer. So at a certain size of the company, I think other people can run it better than me.
And so right now I'm open to everything, but we are currently in a seed phase.
So we're taking up angel investors.
So far, I invested about two and a half million euros myself.
And now we're currently gathering one million for the seed phase,
but we also want very good angels in there. so people who can also advise us
and also open us some doors and so on.
And then probably like around the end of the year or so, we will go into a VC phase.
And then probably it's more the VC who decides where we are going because they
know better how to make the most money-wise out of it. It could be all of them.
Anybody who's now interested about working with Keterblanke.ai or investing
into it, they can reach out to you on your LinkedIn profile,
which we link down here in the show notes?
Yes, please do. So we already have some people we're discussing with now,
so it will not be endless the time we will have.
But we are also very interested to have international people because internationalization
is one of the topics I personally would love to have somebody who advises us
on this much better than I know myself.
I see. Awesome. Closing words to our audience.
What questions do you think we missed? Let us know in the comments down here.
Karsen, thank you very much for the first interview. For everybody,
it will be one of the next interviews published.
Your interview number two. And we only take like five minutes break.
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