Building EVERYTHING in-house and raising. By Sharmin Ali

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They're releasing to fundraising
video a podcast about

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fundraising for early-stage
startups, the major rule that we

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follow here is no bullshit on
this podcast.

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No music to relax.
You know, advertisements of our

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sponsors.
We only talk about fundraising

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here and nothing else.
So let's jump into the episode.

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And today's guest speaker, we
have Charmin only founder and

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CEO of in storage who just close
their series a of 10 million.

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Dollars and in this episode
we'll talk about that series a

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and rounds predator and more.
Specifically, why did Charmin

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choose to raise in the United
States while being out a company

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entirely out of India and
focused on the Indian market?

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And of course, we're going to
touch on to the hardships of

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such a fundraising when it makes
sense to actually visit the u.s.

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to close some deals, when you
can just Outsource it and how to

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build a company remotely and how
to expand to the United States,

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which is going to come at the
end of this episode.

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Sewed.
So Charmin, let's kick it off by

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you, giving us some background
on yourself on and on in store

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it.
Sure, first of all, thank you so

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much for having me on your show
Constantine.

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It's, it's my delight to be
here.

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So I am an engineer by
profession.

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Not do any people know that, but
I did my electronics and

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communication engineering from
one of the Premier institution

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and in the southern part of
India.

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And then I moved to the u.s. to,
you know, pursue my first job

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which was in the analytic space
which was based out of Chicago.

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Oh, and I was overwhelmed by the
weather.

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Either because I never really
seen such a winter in part of

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India that I come from after
working there for, you know,

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five years.
Plus I realized that, you know,

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I was just helping the rich get
richer wasn't adding too much

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value to my own life.
So I decided to quit that

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company came back to India to
start my own, you know company.

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The first company was in the
media.

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Space is the plan was to build
India's, very own it.

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Legs because the whole Netflix
revolution had already began in

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the u.s. so you know, the plan
was to replicate the same thing

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but you know, more focused
towards the Indian audiences

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because, you know, the Indian
vernacular languages are a

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little different.
So we ran that company for

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almost three and a half years.
But then we soon understood that

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we were a little ahead of our
time because Indian audiences

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were still very much prone to
consuming content.

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It on their television sets, as
opposed to, you know, their

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mobile devices or on their
laptops, which I was that, by

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the way.
So this is up to, you know,

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until 2018 I mean from from 2015
to you know 2018 only 28.

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So we understood that we were a
little ahead of our time in so

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we ended up selling the
copyrights of all the scripts

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that we had written to a Bombay
seduction house.

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I took the money and then I
exited post this, you know I

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ended up writing two books, one
officials announced a

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best-seller back Any 19 and you
know, it was my little shot to

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fame.
So then I you know, understood

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that content is is something
which is here to stay good.

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Quality content is King as we
all know that.

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And in order to connect with
your customers, you have to

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always create, amazing content.
And that's where the idea of in

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storied actually came to me
that, you know, most of the

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content writers and content
marketers out there, most of

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their content generation.
Assess is very intuition driven,

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you know, it's very manual.
There is acknowledge we that can

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actually assist them when it
comes to their content

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generation.
So that's where we thought.

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What if we, you know, we were
able to build a smart tool using

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which a Content marketer would
be able to, first of all gauge,

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what is their emotional
engagement quotient and also get

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smart recommendations on that?
And on top of it, you know, if

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you were to just feed in a few
keywords and the tool were to

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automatically generate that
content for you.

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Wouldn't that be awesome?
So that is exactly what you

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know, we have done it in storied
in the last three years now.

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And yeah we you know we have
over half a million plus users

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and I must say one thing that,
you know, we do, we initially

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started out from India but our
main Market is the US and you

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know, so now the money that we
raised we are looking at

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expanding in the u.s. completely
and yeah.

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Yeah, we want to disrupt the
American entrepreneurial

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ecosystem.
Interesting, interesting.

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And yeah, maybe at the end of
the episode or closer to the end

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of the episode, we're going to
touch into a little bit more of

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the tech and specifically, why
the, why the team decided to

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build everything in-house,
rather than trying to, you know,

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take a few pieces here and there
and just assemble them into the

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final product.
But first question is actually

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going to be about how did you
build the MVP?

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How did you make sure that this
is a real Market that you are no

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longer?
You know, ahead of your time as

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As happen with your previous
company.

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So it seems like incest or in
storage sort of.

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Keep mispronounced.
It, it, it seems like it store.

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It is quite Tech heavy product.
So how did you make sure that,

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you know, you're going to build
it out?

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Test it out and if it doesn't
work, you don't incur massive

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losses.
Right?

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So, yes, absolutely.
You know, we are a very

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tech-heavy, you know, company.
So, we decided to build

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everything in house.
Yes.

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And, you know, the product also
was was built from the scratch.

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The reason being that.
You know, my co-founder and I,

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we were always very sure of the
fact that, you know, there is no

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point in just becoming a copycat
product like everything, you

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know, like like everyone else
out there.

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We want to ensure that, you
know, we will something Give you

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know of which the data would be
completely proprietary.

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And you know, so we were very
sure from the scratch that we

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had to build this in-house.
So initially when we started,

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you know, we had done a huge
amount of market research,

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actually.
I even went to Harvard to, you

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know, meet with a few
neuroscientists and Euro

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marketers to understand what is
it that you know that that they

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feel when it comes to content
generation when it comes to

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marketing.
So what they said is that As we

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all know that it's a, it's a
very globally.

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Well-known fact, that all of the
consumer decision-making, all

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the customer buying patterns,
everything is driven by emotions

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and not by Logic.
Hence, in order for marketers to

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connect better with their
audiences, you know, the content

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has to be emotionally engaging,
you know, the, the empathy

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quotient has to be in place in
order to resonate with your

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customers, the emotions that
your content exudes it.

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Should have, you know, all of
the right set of emotions in

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place.
So what they said is that there

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are, you know, three three tones
or opinions is the say, which

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any marketer looks at first is
positive negative neutral.

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And then if you dig down a
little bit, there are five main

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emotions that we as human
beings, connect the most to it,

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starting with uniform or, or
fear of missing out is the same.

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When, you know, there is Joy,
there is anger, there is

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sadness, and there is surprise
So these five emotions so

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marketers around the globe are
also looking for, you know,

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these five emotions and three
tones to, you know, ensure that

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the content has, you know, has
the has the right tone and the

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right emotion in place before
they go out there and publish

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it, right?
So what we get is that, you

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know, we collected about 30
million data points from

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multiple sources and we got them
tagged to the right set of tones

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and emotions and then we built
the whole MVP in house.

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It actually took us almost 18
months to, you know, will the

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technology?
Because we did everything from

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this crash and we did everything
in house.

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And the the first version was
like, and okey okey, I want to

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show you know, because it was an
MVP.

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But now what we have, it's so
highly evolved, it has anything

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and everything under the sky it
has a plagiarism Checker which

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would help you tell if your
content is real or or, you know,

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has it been plagiarized.
It has a panel testing.

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Which, you know, through which
you can get it tested by a panel

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of people as the name suggests
and, you know, you can get their

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opinion on what they feel about
your content.

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So basically, an AI enabled
engine and also, you know,

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real-time human engine, which
will tell you that, okay?

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This is how good my content is
looking like.

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And on top of this, a very smart
recommendation engine, which

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will suggest words to, you know,
either increase or decrease the

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empathy quotient of your
content.

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So it's like an end to end You
know, content content platform.

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Now, we all have a Content
generation piece, you just feed

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in a few keywords and the tool
would, you know, create the

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content for you.
So, yeah, I think by far in the

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market, we are the most evolved
when it comes to, you know,

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having built something in house.
And the tool is above anything

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and everything that is available
out there.

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All right, that does sound
pretty freaking cool.

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So actually since you've
mentioned fear of missing out

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and you know, multiple of those
emotions that have to be present

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in the social media post and any
other content that is thrown out

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there for the users to consume.
Let's, let's talk about the use

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of those emotions while you were
fundraising.

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So, you know, you're the expert
in the field obviously, which of

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those motions.
Do you think works the best You

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talk to investors.
How do you make sure that

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investors invest in you as soon
as possible and you know, with

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as little negotiation as
possible, using those emotions,

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have you actually tried doing
that or did you just, you know,

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go with the standard flow.
So formal always works.

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Absolutely for more works
everywhere in any and every

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failure we are.
We are human beings after all

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but then I didn't really have to
use it much because, you know,

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more than words, I think.
As this a actions speak louder

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than words.
So, you know, the tool that we

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built it was so beautiful and
you know, I mean we we already

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had a good amount of traction
and you know, we had we had

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already raised some money before
that when we were building the

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to and and and of course you
know the first round as they

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call it the precede and then the
seed round that is all about,

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you know, the team and the story
of the team, right?

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So you know, I think me and my
co-founder we had, you know, to

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Amazing Story.
To tell.

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So it was more of a team gamble
initially.

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So I think former really work
people were like if you don't

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invest in them then who so you
know, that battery work for us.

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Yes, awesome.
And congrats, worry.

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Having worked speaking of it
work and you reason you're

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serious, a you have actually
mentioned on our pre-interview

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called that's by far series.
A was the toughest round fruit

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to raise honestly based on my
standard knowledge of the

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industry and base.
Tan, hundreds of other people

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who have participated here on
fundraising radio and shared

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their fundraising Stories.
The majority of them say that

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the further you go the easier,
it is to raise your rounds.

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Why do you think in your case
series?

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8 was harder than, let's say
precede stage?

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Because you're cool with
company.

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Yeah, yes.
Grow you know as you grow

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raising rounds, you know,
becomes easier because you've

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been there for a while and you
know the process and you know,

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you know, the whole drill.
Yes.

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So that that absolutely makes
sense but the thing is it's you

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know, when you're covid company
and you know things are not that

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great globally and you know,
there are millions who are

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dying.
In between all of that, you

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know, raising money does become
a little painful.

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So I think it was, it was both a
pro and a con for us covid.

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You know, because a pro as in,
you know, because I think the

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timing was perfect.
We were able to identify a huge

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opportunity in this adversity,
but most of the brick-and-mortar

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stores were shutting down.
The only option that people had

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was to be, you know, able to
move online and you know, sell

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better by Ting more engaging
content, and that's exactly what

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we do.
So, you know, getting customers

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was was very, very easy for us.
But then yeah, the funding was a

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little painful, you know,
because things in India weren't

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all that great when it came to,
you know, the whole covid

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scenario.
So it was the pain, raising

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money in India.
Yes, that is when we decided to

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move to the US to raise money
and I'm happy to share that in

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the first call that we had,
which was, you know, with krita

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00:13:28,600 --> 00:13:32,800
Iseman Partners from Washington
d.c. within a week.

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We have the term sheet, you
know.

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So yes in the u.s. it was like
one call and that's it which

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really helped and you know then
I think after the due diligence

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and everything was done and then
he a things were fine so in the

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u.s.
I just spoke with one investor

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and we were able to close it it
was painful in India.

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Yeah all right and yeah that
happens to a lot.

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A lot of Founders, I've honestly
seen so many people who are to

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literally change their entire
companies, just because they

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realize that they cannot raise
money in their own country.

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I've seen that so many times and
yeah, it's quite painful as

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you've mentioned.
But yeah, let's let's, let's

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talk about that.
Let's talk about Founders who

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are basically forced to raise
money outside of the United

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00:14:22,100 --> 00:14:25,000
States even though they're
building a company in a

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completely different country,
not for American Market at all,

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In your case.
What do you think was the major

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00:14:31,000 --> 00:14:33,500
struggle there to explain to
American investors, you know

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00:14:33,500 --> 00:14:36,400
what you're doing?
Or was it the cultural barrier

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or was it just you know, the
fact that he just didn't

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00:14:38,900 --> 00:14:42,300
understand Americans too well?
Or what do you think was the

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00:14:42,300 --> 00:14:45,500
major barrier for you to raise
money from American investors?

254
00:14:47,900 --> 00:14:51,900
So you know I mean from the US
market, Frankie I didn't have

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00:14:51,900 --> 00:14:56,000
too much of a barrier because,
you know, I have worked in the

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00:14:56,000 --> 00:14:58,600
u.s. lived and worked in the US
for almost 5 years.

257
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So I really understand how the
market is, you know, but but

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initially, we were thinking that
we will raise some money in

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India and then most of the US.
But then I think all's well that

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ends.
Well, we were not able to raise

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00:15:12,500 --> 00:15:15,800
much money in India and so we
had to move to the US but then,

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Eventually we knew that, you
know, u.s. is the main market

263
00:15:18,300 --> 00:15:20,100
for us.
So in the US, the good thing

264
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that happened is that, you know,
all the things that they needed,

265
00:15:23,900 --> 00:15:26,500
they were all tick marks for for
us, you know, all the boxes were

266
00:15:26,500 --> 00:15:28,900
checked.
We had a great team.

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We had a great product, we had
traction and, you know, as in

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00:15:34,000 --> 00:15:37,400
early traction, of course.
And, you know, we had a clear

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00:15:37,400 --> 00:15:40,700
roadmap in place about how we
wanted to expand in the u.s.

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00:15:41,200 --> 00:15:46,400
So I think the stars were
aligned and, you know, It was it

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00:15:46,400 --> 00:15:49,600
was sweet.
It was easy in the u.s. there

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00:15:49,600 --> 00:15:51,500
are not too many barriers
accept.

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The fact that you know I mean
because because it was foreign

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00:15:55,500 --> 00:15:58,700
direct investment for us.
You know at that point in time

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we were not a u.s. entity so
other than the legal trouble,

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00:16:02,800 --> 00:16:04,700
you know.
Other than that we didn't really

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00:16:04,700 --> 00:16:06,900
have too many challenges search.
Yeah.

278
00:16:08,600 --> 00:16:10,600
All right.
And actually, you mentioned

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00:16:10,600 --> 00:16:13,800
something that would like to go
back to, which is the fact that

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00:16:13,800 --> 00:16:15,600
you did raise some money in
India.

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00:16:16,400 --> 00:16:18,500
How did you deal with the money
that you've already reason

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00:16:18,500 --> 00:16:20,500
India?
And then you had to open another

283
00:16:20,500 --> 00:16:23,500
entity in the US.
Did you just transfer money and

284
00:16:23,500 --> 00:16:25,600
issues?
Some shares from the new company

285
00:16:25,600 --> 00:16:29,000
to investors or how do you
transfer that legalized?

286
00:16:29,000 --> 00:16:31,700
Yeah.
Yes exactly.

287
00:16:31,700 --> 00:16:35,700
That is odd.
So you know I mean one one thing

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00:16:35,700 --> 00:16:39,200
that I've learned in this entire
processes that you need to have

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00:16:39,200 --> 00:16:42,000
a great lawyer and a great
chartered accountant in order

290
00:16:42,000 --> 00:16:46,700
for your company to grow, you
know, no matter what, what

291
00:16:46,700 --> 00:16:50,000
business Acumen you carry, but
unless and until you don't have

292
00:16:50,000 --> 00:16:52,900
a good legal attorney and you
know, a good Financial

293
00:16:52,900 --> 00:16:56,600
Consultant in place, your
company will not grow globally.

294
00:16:56,800 --> 00:17:01,300
So thankfully in our case, you
know, we were able to And do

295
00:17:01,300 --> 00:17:04,700
amazing people, you know, one
from the finance side and one

296
00:17:04,700 --> 00:17:09,099
from the legal side who were
able to help us and yes like

297
00:17:09,099 --> 00:17:12,500
your right heel, you know, like
you rightfully said, we were

298
00:17:12,500 --> 00:17:15,599
able to open the u.s. entity and
then transfer shares in you.

299
00:17:15,900 --> 00:17:17,900
Yes, all of that process
happened.

300
00:17:18,700 --> 00:17:21,500
I wouldn't say that it was very
smooth because we had to figure

301
00:17:21,500 --> 00:17:24,300
a few things out.
So we had to transfer money and

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00:17:24,300 --> 00:17:26,800
you know, then all of those
things followed wherein, you

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00:17:26,800 --> 00:17:30,800
know, because out of India, the,
the challenges that That you

304
00:17:30,800 --> 00:17:34,700
know, the whole taxation system
and the laws, they are little

305
00:17:34,700 --> 00:17:37,900
more tedious, you know.
So we had to do a number of

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00:17:37,900 --> 00:17:41,000
filings, we had to get a number
of papers in place.

307
00:17:41,600 --> 00:17:44,800
But thankfully, everything was
was, you know, Dunning time and

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00:17:44,800 --> 00:17:46,600
we were able to incorporate in
the u.s.

309
00:17:46,600 --> 00:17:51,400
Yeah.
Gotcha, and congratulations.

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00:17:51,400 --> 00:17:53,900
I know that this process is kind
of complicated, especially if

311
00:17:53,900 --> 00:17:57,000
you've never done it before, or
you don't have the theoretical

312
00:17:57,000 --> 00:18:00,400
background into that, but you've
handled, it's okay.

313
00:18:00,500 --> 00:18:04,600
Congratulations, good stuff.
So now let's talk a little bit

314
00:18:04,600 --> 00:18:08,000
more about the tech side of it
and then we're going to wrap it

315
00:18:08,000 --> 00:18:11,600
up briefly.
So one thing that stood out to

316
00:18:11,600 --> 00:18:13,800
me while we were talking about
the technical stuff on the

317
00:18:13,800 --> 00:18:17,300
prince recall is the fact that
you had an exclusive or you have

318
00:18:17,300 --> 00:18:20,000
actually currently an exclusive
partnership with Oxford

319
00:18:20,000 --> 00:18:22,400
University.
So how did you make that happen?

320
00:18:22,400 --> 00:18:24,400
How does this partnership look
like?

321
00:18:27,200 --> 00:18:30,900
So basically, you know, Oxford
University, as we know, they are

322
00:18:30,900 --> 00:18:33,700
pretty much the owners of the
Oxford dictionary, right?

323
00:18:33,800 --> 00:18:36,300
Those guys are the, you know,
Big Daddy's of the English

324
00:18:36,300 --> 00:18:39,100
language and you know, because
we are we have a product that is

325
00:18:39,100 --> 00:18:43,500
built.
So you know, it definitely makes

326
00:18:43,500 --> 00:18:46,800
sense to partner with the Oxford
University press.

327
00:18:47,700 --> 00:18:51,800
So we did that.
And you know, we've got paid

328
00:18:51,800 --> 00:18:56,400
Partnership, of course, and we
were able to get some amazing

329
00:18:56,400 --> 00:18:58,100
data.
Dictionary from them.

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00:18:58,300 --> 00:19:02,600
And, you know, they, they really
helped us, you know, align, the

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00:19:02,600 --> 00:19:04,600
data points that we were looking
at.

332
00:19:04,600 --> 00:19:09,200
And this was actually great, you
know, because it because because

333
00:19:09,200 --> 00:19:11,700
they already had it in place,
they didn't really have to work

334
00:19:11,700 --> 00:19:16,300
very hard, you know, on this.
So, and, and, you know, we, we

335
00:19:16,300 --> 00:19:18,700
already had like a huge amount
of data base.

336
00:19:18,700 --> 00:19:21,700
But then on top of that, when
you, you know, superimpose that

337
00:19:21,700 --> 00:19:25,600
you'd something amazing as the
Oxford guys gave us it just, you

338
00:19:25,608 --> 00:19:28,600
know, enabled.
Our recommendation engine to,

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00:19:28,600 --> 00:19:31,400
you know, get get these amazing
record indications.

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00:19:31,400 --> 00:19:35,600
You know, our data was super
refined and we were able to get,

341
00:19:36,200 --> 00:19:38,800
you know, the kind of results
that we were looking at.

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00:19:38,800 --> 00:19:42,200
So all of the quality checks
that any tech company would be

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00:19:42,200 --> 00:19:45,400
looking at in order to upgrade
their data and you don't get the

344
00:19:45,400 --> 00:19:48,900
whole process, much more
efficient, more productive, all

345
00:19:48,900 --> 00:19:52,500
of that was enable.
So I think it was a big win for

346
00:19:52,500 --> 00:19:55,500
us.
Right?

347
00:19:55,500 --> 00:19:59,200
And I mean, nicely partnering
with Oxford is pretty fun.

348
00:19:59,900 --> 00:20:03,000
Did that help you find race at
all having?

349
00:20:03,000 --> 00:20:06,800
You know this big daddy of
English language on your team

350
00:20:06,800 --> 00:20:11,100
basically?
So I think the help that they

351
00:20:11,100 --> 00:20:14,100
have Print is that, you know,
the product was greatly

352
00:20:14,100 --> 00:20:16,300
improved, right?
So, whatever, the product is

353
00:20:16,300 --> 00:20:19,200
great, more customers with our,
you know, our are interested in

354
00:20:19,200 --> 00:20:23,400
your tool so indirectly.
Yes, you know, indirectly, it

355
00:20:23,400 --> 00:20:25,800
did help us.
Yes, increasing, I would

356
00:20:25,800 --> 00:20:29,600
imagine, you're going to flex
that much harder, but fair

357
00:20:29,600 --> 00:20:32,300
enough, fair enough.
So, let's, let's talk about last

358
00:20:32,300 --> 00:20:35,000
thing before, rip it up, which
is the fact that you chose to

359
00:20:35,000 --> 00:20:38,800
build everything in house, you
know, sounds like something

360
00:20:38,900 --> 00:20:42,100
Facebook will do where they just
refuse to take a and Technology.

361
00:20:42,200 --> 00:20:45,200
From anyone else and they just
built every single thing that

362
00:20:45,200 --> 00:20:48,700
they use in house.
Why did you choose to go clean

363
00:20:48,700 --> 00:20:56,400
up the Facebook routes?
I think Mark Zuckerberg and I

364
00:20:56,400 --> 00:21:03,500
think alike, you know, so yeah,
the reason was was actually very

365
00:21:03,500 --> 00:21:07,000
simple.
You know, we didn't want to have

366
00:21:07,000 --> 00:21:10,400
the same set of results that all
the other people, you know, just

367
00:21:10,400 --> 00:21:15,300
built to prom, you know, apis.
We wanted a very exclusive, a

368
00:21:15,300 --> 00:21:19,200
very refined product which would
be state-of-the-art built

369
00:21:19,200 --> 00:21:22,300
in-house and you know, it would
give the best responses when it

370
00:21:22,300 --> 00:21:23,600
comes to content.
Aunt.

371
00:21:23,600 --> 00:21:25,700
As we know, AI is no magic,
right?

372
00:21:25,800 --> 00:21:29,000
It is basically all about the
data that you feed in, and then,

373
00:21:29,000 --> 00:21:31,400
you know, you trained your
system using that data.

374
00:21:31,700 --> 00:21:34,600
And that is how you get those
amazing incredible responses,

375
00:21:34,600 --> 00:21:36,800
right?
So basically, it is all about,

376
00:21:37,400 --> 00:21:41,500
you know, the the food, which is
the, you know, the the basic

377
00:21:41,500 --> 00:21:45,400
fuel for that AI engine to run.
So that food for us, who is was

378
00:21:45,400 --> 00:21:48,200
amazing data.
So, we were like, very sure that

379
00:21:48,200 --> 00:21:52,400
we have to build 30 million data
points at least in house, in

380
00:21:52,400 --> 00:21:56,100
order to get that Using, you
know, responses when it comes to

381
00:21:56,100 --> 00:21:59,500
the tool and yes, it did.
Take us a lot of time almost 18

382
00:21:59,500 --> 00:22:02,600
to 20 months to get that in
place that I think all those

383
00:22:02,600 --> 00:22:05,500
efforts were worth it.
Because, you know, our data set

384
00:22:05,500 --> 00:22:07,100
is completely proprietary,
right?

385
00:22:07,100 --> 00:22:12,000
That is our, you know, that that
is that is our, our IP, right?

386
00:22:12,000 --> 00:22:16,000
So it was, it was an amazing
thing and we were very sure that

387
00:22:16,000 --> 00:22:20,100
we want to stand apart.
So our biggest barrier to entry,

388
00:22:20,100 --> 00:22:23,300
you know, for for anyone to copy
us, the biggest barrier to To

389
00:22:23,300 --> 00:22:26,600
entry for them would be the data
set because our data set is

390
00:22:26,600 --> 00:22:30,600
completely proprietary, right?
Yes that's why we're not going

391
00:22:30,600 --> 00:22:35,700
to go into any further details
of explain how the data set with

392
00:22:35,700 --> 00:22:37,900
collected even though I'm a
little bit curious actually

393
00:22:37,900 --> 00:22:40,100
never mind.
Fine fine let's let me ask that

394
00:22:40,100 --> 00:22:41,900
question.
How did you acquire the data

395
00:22:41,900 --> 00:22:43,100
set?
Where did you get it from?

396
00:22:43,100 --> 00:22:47,700
Did you scrape the internet?
Did you just purchase that day

397
00:22:47,700 --> 00:22:52,400
sets somewhere?
These we have scraped the

398
00:22:52,400 --> 00:22:56,000
internet of course from you
know, multiple platform from

399
00:22:56,000 --> 00:22:59,900
from WordPress from Hotspot,
from Twitter, Facebook,

400
00:22:59,900 --> 00:23:04,600
LinkedIn, Instagram, anything
and everything is both manual.

401
00:23:04,600 --> 00:23:09,700
Both manual and machine based
data, scraping everything, we've

402
00:23:09,700 --> 00:23:12,700
done, yes, yikes.
And when you're scraping the

403
00:23:12,700 --> 00:23:15,600
internet, how do you know that
you're feeding the machine?

404
00:23:15,800 --> 00:23:17,900
Some like a good piece of
content.

405
00:23:19,200 --> 00:23:23,000
Because we have hired linguists
in house, who, you know, help us

406
00:23:23,000 --> 00:23:25,500
do this.
These are guys who have like the

407
00:23:25,500 --> 00:23:29,800
Masters in literature, they are,
you know, gods and goddesses of

408
00:23:29,800 --> 00:23:33,400
contact.
So we are always very short to

409
00:23:33,400 --> 00:23:36,200
have a stellar team in place,
who would, you know, help us

410
00:23:36,200 --> 00:23:38,500
build this.
So, when we say that, we are a

411
00:23:38,500 --> 00:23:42,700
tech heavy company, yes, 70% of
the team are techies.

412
00:23:42,700 --> 00:23:47,100
But then, you know, almost 15%
of the team is, you know,

413
00:23:47,100 --> 00:23:50,300
linguists and And, you know,
these are guys who really

414
00:23:50,300 --> 00:23:53,800
understand content in, you know,
English language really well.

415
00:23:54,100 --> 00:23:57,300
So with their help and wonderful
support, we were able to build

416
00:23:57,300 --> 00:24:01,500
what we have built, right?
And it does look very good.

417
00:24:01,500 --> 00:24:04,000
Honestly, I'll definitely get a
free trial.

418
00:24:04,000 --> 00:24:07,200
See how much you use it is.
And based on this conversation,

419
00:24:07,200 --> 00:24:10,100
I'm pretty confident going to
get an annual plan because first

420
00:24:10,100 --> 00:24:13,100
of all, it's pretty cheap.
Secondly, I feel like sometimes

421
00:24:13,100 --> 00:24:14,900
I'm just repeating myself there
a little bit.

422
00:24:14,900 --> 00:24:20,700
So, we now have a joke that when
words Huh.

423
00:24:20,700 --> 00:24:24,400
Just just log into a dotting
story.com and starting it very,

424
00:24:24,400 --> 00:24:27,900
very easy to use, and it's
already nearly create my account

425
00:24:27,900 --> 00:24:29,200
while we're having this
interview.

426
00:24:29,300 --> 00:24:32,800
So, yeah, is that easy?
And on this note, let's move on

427
00:24:32,800 --> 00:24:35,300
to the very last question.
If today's episode, which is the

428
00:24:35,600 --> 00:24:38,000
call to action.
So drumming, would you want to

429
00:24:38,000 --> 00:24:40,600
listen to do?
As soon as this episode is over?

430
00:24:42,000 --> 00:24:45,000
Oh well of course the founder
and me would say that log into

431
00:24:45,000 --> 00:24:49,500
AB dot in story.com and start
using the tool ASAP and you

432
00:24:49,508 --> 00:24:53,900
know, suggest more people.
But I feel on top of that, what

433
00:24:53,900 --> 00:24:57,800
we would also, you know, love is
that, they are now coming up

434
00:24:57,800 --> 00:25:00,600
with some incredible other
things so far.

435
00:25:00,600 --> 00:25:03,900
We were only a web app, but now,
we are coming up with a Chrome

436
00:25:03,900 --> 00:25:06,500
extension WordPress.
Plug-in.

437
00:25:06,700 --> 00:25:09,600
And, you know, we and and most
importantly, we're going to have

438
00:25:09,600 --> 00:25:11,600
this beautiful beautiful
content.

439
00:25:11,700 --> 00:25:15,200
Generation system, you know.
So we need a lot of people to

440
00:25:15,200 --> 00:25:17,500
try that out.
Give us the kind of feedback,

441
00:25:17,500 --> 00:25:20,500
you know, honest feedback,
constructive feedback what they

442
00:25:20,500 --> 00:25:23,600
think about it.
So you know I mean in order for

443
00:25:23,600 --> 00:25:28,100
you to get that catchy caption
for your Instagram post or your

444
00:25:28,100 --> 00:25:31,300
Facebook post, just feed in a
few keywords and the tool will

445
00:25:31,300 --> 00:25:34,800
come up with that texture and
the whole idea behind doing this

446
00:25:34,800 --> 00:25:38,700
is to, you know, help you create
better content which is much

447
00:25:38,700 --> 00:25:43,800
more productive, very easy to
use and No, bitch would see with

448
00:25:43,800 --> 00:25:47,000
the right set of emotions, we
are the world's only platform

449
00:25:47,000 --> 00:25:51,000
which will have both a Content
generation and a Content

450
00:25:51,000 --> 00:25:56,600
evaluation system on just one
platform or and that too.

451
00:25:56,600 --> 00:25:59,700
At a very, very cheap price.
Yeah.

452
00:25:59,900 --> 00:26:03,300
So yes, Phoebe more people to
use this.

453
00:26:03,300 --> 00:26:06,200
Give us their constructive
feedback and help us spread the

454
00:26:06,200 --> 00:26:08,500
word.
Yes, them's the facts.

455
00:26:08,500 --> 00:26:11,500
I'll make sure to leave the link
to in store it in.

456
00:26:11,600 --> 00:26:15,400
The description fits episode for
people who really are really bad

457
00:26:15,400 --> 00:26:18,500
with spelling things out.
It is going to be down there.

458
00:26:18,500 --> 00:26:22,500
So if you think that's sometimes
you need to replace some words

459
00:26:22,500 --> 00:26:25,900
with better words because you
just keep repeating yourself or

460
00:26:25,900 --> 00:26:29,800
you just put out dry text, which
happens to the best of us.

461
00:26:29,800 --> 00:26:33,600
Honestly, it takes practice to
not do that, check it out.

462
00:26:33,700 --> 00:26:36,600
It does seem like a super
helpful tool, probably later on,

463
00:26:36,600 --> 00:26:39,600
in other episodes.
I'm gonna once I try, I'm

464
00:26:39,600 --> 00:26:42,100
actually going to do some actual
feedback or I'm just going to

465
00:26:42,100 --> 00:26:45,200
include it down there in the
description of this episode.

466
00:26:45,500 --> 00:26:48,400
So that's gonna be my call to
action is always super simple.

467
00:26:48,700 --> 00:26:50,200
Go check out the description of
this episode.

468
00:26:50,200 --> 00:26:54,500
I'm going to include in storage
sharman's LinkedIn and of course

469
00:26:54,500 --> 00:26:56,600
there's going to be Shameless
plug in of our course.

470
00:26:56,900 --> 00:27:01,900
Because why not?
And as always, go have a good

471
00:27:01,900 --> 00:27:02,300
day.