October 29, 2025 • 10 mins
John Imah is Co-Founder and CEO at SpreeAI, an AI-driven company transforming the future of fashion and e-commerce with our photorealistic try-on technology.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
And so when you are looking at the metrics, so like,
how how does this work? How does like what are
the things we're measuring to see that? Okay, we're making progress,
you know, the team is doing we're they're supposed to
be doing. How do you measure that?
Speaker 2 (00:15):
Yeah, I think there's two folds of the metrics.
Speaker 3 (00:17):
So before we started building this product, I spent a
lot of time in Europe. I had worked in tech
my whole life, and so I had a lot of contacts,
and so I met with a lot of these luxury
houses and I noticed the commonality and all of the
answers they had. They needed a product that was personalized
and needed something that was going to reduced returns. And
then also on top of that, which is more important
(00:37):
because they're a business, they need something that's going to
increase sales, right, And so we wanted to make sure
that those KPIs were built in to our products. On
the team side is we need to align with our
customer goals and so there's a lot of things that
we need to build, and so it's very important that
we set milestones because our products, sorry our partners.
Speaker 2 (00:57):
Dictate when they launched.
Speaker 3 (00:58):
Because we're a white level service, right, and so we
need to make sure that we have the right packages
for each partner to gear them up to launch as well.
Speaker 1 (01:08):
You said something a moment ago about ninety nine percent accuracy.
Can you restate that, so I will make sure. My
next question IS's own point.
Speaker 3 (01:16):
Yes, so it's nine nine percent accuracy. And so how
it works is there's a lot of math and science
that's involved into this, and so we've partnered with institutions
like Carnegie Mellon and MT to help us co develop
our product, and we also.
Speaker 2 (01:28):
Hire students from there and internships and.
Speaker 3 (01:31):
So basically from a consumer perspective, the way that to
use our product is it starts with your phone and
so essentially you take a picture is a full body
picture of yourself. Right, there's an onboarding process that's saved
into the.
Speaker 2 (01:43):
Cloud one time. Right.
Speaker 3 (01:45):
What you don't know is when we're taking that picture
of you, we're actually measuring the depth of field and
there's all these order sort of contingencies or are that
are basically applied for us to formulate that. That's the
first part on the back end of things any of
AI company.
Speaker 2 (02:02):
One of the things that's probably the most valuable.
Speaker 3 (02:04):
To an AI company is the data. And so the
question is, well, how do you get that. We have
vendors all across the world that are basically capturing data
points of all shapes, all sizes of people, because we
need to know what to look for, right because as
you know, there's all saxeu and sizes, all shades, et cetera.
And then sort of the third component is our partners
as well, and so we're capturing data on their garments, models,
(02:28):
et cetera. And so we're able to merge that all together,
and that's what powers our product now for our sizing product.
The one sort of additional detail is in the fashion
world they call it tech packs, and tech packs are
basically the dimensions of the garments, right, and so we
have that piece of data as well. So if you
merge all that together, we're able to with a nine
percent accuracy, not only tell you your size of the product,
(02:51):
but also tell you what it would look like and
how it would feel if you wanted something like a
tight fit or a loose fit and so forth.
Speaker 1 (02:58):
So it can tell you know, if I'm our size
eleven and sheet right, so soon I got on our eleven,
but if I buy some a six, it's not to
be eleven and a half. So it can tell the
difference between that.
Speaker 2 (03:09):
Yeah.
Speaker 3 (03:10):
One of the pain points we discovered from talking to
brands and also through a lot of our case studies
with consumers is every brand has their own unique size,
right Bucci where the media medium, Nike wear a large,
et cetera. And so the critical component to that is
the tech packs. The tech packs aren't necessarily about the size.
It's actually the measurements of the garment and it basically
(03:31):
converts that into data. And so that's how we're able
to know. We wanted to basically create the world's first
what we call a universal sizing metric, meaning that from
a consumer perspective, you.
Speaker 2 (03:42):
Never have to worry about your size again.
Speaker 3 (03:44):
Right, We're telling you every single time, yo, will, this
is your size in this brand, this is your size
in that brand, et cetera.
Speaker 1 (03:50):
So yeah, I like that. So I think about you know,
people who are launching AI companies and most of the
world just got aware of what was going in in
AI like eighteen months ago, twenty four months ago, and
with chat chipbt, you know, because of things like chatchibt,
how fast like, when did you start building this, When
(04:13):
did you got to have the idea? And how fast
to market did this happen?
Speaker 3 (04:18):
Yeah, so I started working on this approximately three years ago.
It's definitely been a grind. I always loved fashion, so
I grew up a nerd.
Speaker 2 (04:29):
I grew up an entrepreneur.
Speaker 3 (04:30):
I had two companies that I sold before I was sixteen,
and then went to work in corporate America and it
worked at places in like Snapchat, Meta, et cetera. But
during my time, through this evolution of growth, if you will,
I was always looking for a way to merge techic fashion.
There were tools and products out there, the challenge it
wasn't necessarily up to the par or standard that I
(04:51):
was looking for. And so before the world started talking.
Speaker 2 (04:55):
About AI and chat and GBT, I was.
Speaker 3 (04:57):
Already sort of in the mix of exploring AI and
machine learning, etc.
Speaker 2 (05:02):
When Chat GPDBT launched.
Speaker 3 (05:04):
In many ways we benefited from that because it educated
the world on what this AI thing is and we
became a part of that conversation because the name of
the company Spree AI, and so when people are searching,
we come up until we get a lot of that
SEO and so in many ways, it was very meaningful
to us.
Speaker 1 (05:22):
So when you went to start raising money, was there
like already an MVP in place, or was the convergence
of the idea just situated such that investors are like, yeah,
he's billy AI, that's throw money at it.
Speaker 3 (05:35):
Yeah, it was the convergence of the idea. I think,
you know, entrepreneurs, one of the challenging things is raising money,
amongst many things. I think specifically for me, I was
very fortunate, bless that I had a reputation because I
already had startups before that I sold, and I already
had worked in tech until in many ways, the investors were,
for lack of better words, investing in me. It wasn't
(05:55):
necessarily about the product. And I know that's not usually
the case for entrepreneurs, and so I wouldn't say it
was easy for me to raise money, but it wasn't
as difficult as maybe someone that's starting from scratch to
you know, raise money and then you know, start their journey.
Speaker 1 (06:12):
Yeah. So how do you then, because you've exited twice,
you know, kudos to you for that, how do you
personally define generational wealth?
Speaker 3 (06:23):
Yeah, it's it's so funny that you mentioned that for me,
I've never in my entire life been basically motivated by opportunity.
It's sorry, buy money, not opportunity. Yeah, yeah, sorry, I've
never been motivated by money. It's been mostly about opportunity
and obviously money falls with that. And so, you know,
(06:43):
I'm first generation Nigerian. My parents grew up poor. I
didn't come for money, and so you know, my parents
had to sacrifice a lot to come to this country
and basically create a means for us to you know,
live and be where we are to today. And so,
as I said, to begin through this journey, it became
very apparent to me that you know, oftentimes when we
(07:04):
think of success, especially in our community, sometimes it's comparable
to things that we see in our eyes all the time,
like sports and things of that nature, right, and so,
but we don't necessarily translate that to tech at least yet.
I know it's getting texts becoming more mainstream. And what
I mean by that is when you think about someone
(07:25):
like Lebron James or Michael or Michael Jordan, one of
the things that comes to mind is this person is
a unicorn. They're kind of a one of a kind
and they're basically about to put on for their family
and friends and so forth. And so I started to
carry that same mindset with me, and I realized how
fortunate I was because a lot of the technology that
I learned was all self taught.
Speaker 2 (07:46):
Right, If you think about the complexities.
Speaker 3 (07:47):
Of technology, it's not an easy thing to get into,
just like arguably it's not easy to get into the NBA.
And so in many ways, this is like a once
in a lifetime opportunity. And so generational wealth means to me,
it's not about me, it's about everyone else around me,
plus people that aren't here yet, So my kids, my
kids kids, setting up a foundation that they don't have
(08:10):
to work as hard as I did, and being able
to have a stable company to where you know, maybe
you have a son one day and you're like, yo,
he needs an internship. I'm like, I got you right,
Being able to like form those connections and help elevate
other people that are around.
Speaker 2 (08:25):
Me as well.
Speaker 1 (08:27):
Yeah, something you just said there is like I'm going
to do my best to formulate the question out of this,
but I'm hoping you just kind of get what I'm
trying to say. So you just said something that. I
also heard another recent interview Todday or youreende frough Campus
just said also in that you're not necessarily thinking about
the money opportunity when you're going to build something because
(08:48):
the money that's part that part is a given when
you've achieved the mission. And I think, like so often
we get money focused by because we're taught to. You know,
when you when you talk about you know total you
know market opportunity, you know TAM, you know the total
addressable market, the you know all those sorts of things.
You're thinking about dollar signs. And what I hear you
(09:10):
say is like I'm thinking about, is the opportunity big enough?
Speaker 2 (09:14):
It?
Speaker 1 (09:15):
Can I make a big enough dit in the world
to where if I do that, then the money is
like a given? Does it make sense what I'm trying
to say, Like we're trying to get like some money focused.
We talk to be money focused in one way, but
you're saying, let's just focus on the concept and be
big enough.
Speaker 3 (09:30):
Yeah, exactly, I get exactly to say. I think though,
to play Devil's advocate. Where it becomes challenging is when
you don't come from money and you're trying to survive
until money becomes a priority because you're like, yo, I
gotta eat right, and so I think that becomes challenging.
But I think naturally for me, the way that I
was raised is, you know, we weren't rich or anything
(09:51):
like that. Like I said, we you know, my parents
got good jobs later on in their careers. When we
were growing up, you know, we used to share the
same room things of that nature. There's you know, there's
four of us between our brothers and sisters. And I
just realized what was really important was for me to
leave my impact on the world and create something that's
so meaningful that it would last forever.
Speaker 2 (10:13):
Right.
Speaker 3 (10:14):
And then if you think about it from that notion,
anything that is meaningful in the world, the money does
come from that. It is associated with that, right. And
so I just felt like, you know, I'm a religious person.
I know not everybody is.
Speaker 2 (10:25):
That I had this.
Speaker 3 (10:26):
God given talent and it was my duty to get
back to the world these skill sets and if it
brings money, which it has, that's great, Right, then I
can use that to provide for my family and friends
and the people that aren't here yet that I haven't created.
Speaker 2 (10:41):
So
And so when you are looking at the metrics, so like,
how how does this work? How does like what are
the things we're measuring to see that? Okay, we're making progress,
you know, the team is doing we're they're supposed to
be doing. How do you measure that?
Speaker 2 (00:15):
Yeah, I think there's two folds of the metrics.
Speaker 3 (00:17):
So before we started building this product, I spent a
lot of time in Europe. I had worked in tech
my whole life, and so I had a lot of contacts,
and so I met with a lot of these luxury
houses and I noticed the commonality and all of the
answers they had. They needed a product that was personalized
and needed something that was going to reduced returns. And
then also on top of that, which is more important
(00:37):
because they're a business, they need something that's going to
increase sales, right, And so we wanted to make sure
that those KPIs were built in to our products. On
the team side is we need to align with our
customer goals and so there's a lot of things that
we need to build, and so it's very important that
we set milestones because our products, sorry our partners.
Speaker 2 (00:57):
Dictate when they launched.
Speaker 3 (00:58):
Because we're a white level service, right, and so we
need to make sure that we have the right packages
for each partner to gear them up to launch as well.
Speaker 1 (01:08):
You said something a moment ago about ninety nine percent accuracy.
Can you restate that, so I will make sure. My
next question IS's own point.
Speaker 3 (01:16):
Yes, so it's nine nine percent accuracy. And so how
it works is there's a lot of math and science
that's involved into this, and so we've partnered with institutions
like Carnegie Mellon and MT to help us co develop
our product, and we also.
Speaker 2 (01:28):
Hire students from there and internships and.
Speaker 3 (01:31):
So basically from a consumer perspective, the way that to
use our product is it starts with your phone and
so essentially you take a picture is a full body
picture of yourself. Right, there's an onboarding process that's saved
into the.
Speaker 2 (01:43):
Cloud one time. Right.
Speaker 3 (01:45):
What you don't know is when we're taking that picture
of you, we're actually measuring the depth of field and
there's all these order sort of contingencies or are that
are basically applied for us to formulate that. That's the
first part on the back end of things any of
AI company.
Speaker 2 (02:02):
One of the things that's probably the most valuable.
Speaker 3 (02:04):
To an AI company is the data. And so the
question is, well, how do you get that. We have
vendors all across the world that are basically capturing data
points of all shapes, all sizes of people, because we
need to know what to look for, right because as
you know, there's all saxeu and sizes, all shades, et cetera.
And then sort of the third component is our partners
as well, and so we're capturing data on their garments, models,
(02:28):
et cetera. And so we're able to merge that all together,
and that's what powers our product now for our sizing product.
The one sort of additional detail is in the fashion
world they call it tech packs, and tech packs are
basically the dimensions of the garments, right, and so we
have that piece of data as well. So if you
merge all that together, we're able to with a nine
percent accuracy, not only tell you your size of the product,
(02:51):
but also tell you what it would look like and
how it would feel if you wanted something like a
tight fit or a loose fit and so forth.
Speaker 1 (02:58):
So it can tell you know, if I'm our size
eleven and sheet right, so soon I got on our eleven,
but if I buy some a six, it's not to
be eleven and a half. So it can tell the
difference between that.
Speaker 2 (03:09):
Yeah.
Speaker 3 (03:10):
One of the pain points we discovered from talking to
brands and also through a lot of our case studies
with consumers is every brand has their own unique size,
right Bucci where the media medium, Nike wear a large,
et cetera. And so the critical component to that is
the tech packs. The tech packs aren't necessarily about the size.
It's actually the measurements of the garment and it basically
(03:31):
converts that into data. And so that's how we're able
to know. We wanted to basically create the world's first
what we call a universal sizing metric, meaning that from
a consumer perspective, you.
Speaker 2 (03:42):
Never have to worry about your size again.
Speaker 3 (03:44):
Right, We're telling you every single time, yo, will, this
is your size in this brand, this is your size
in that brand, et cetera.
Speaker 1 (03:50):
So yeah, I like that. So I think about you know,
people who are launching AI companies and most of the
world just got aware of what was going in in
AI like eighteen months ago, twenty four months ago, and
with chat chipbt, you know, because of things like chatchibt,
how fast like, when did you start building this, When
(04:13):
did you got to have the idea? And how fast
to market did this happen?
Speaker 3 (04:18):
Yeah, so I started working on this approximately three years ago.
It's definitely been a grind. I always loved fashion, so
I grew up a nerd.
Speaker 2 (04:29):
I grew up an entrepreneur.
Speaker 3 (04:30):
I had two companies that I sold before I was sixteen,
and then went to work in corporate America and it
worked at places in like Snapchat, Meta, et cetera. But
during my time, through this evolution of growth, if you will,
I was always looking for a way to merge techic fashion.
There were tools and products out there, the challenge it
wasn't necessarily up to the par or standard that I
(04:51):
was looking for. And so before the world started talking.
Speaker 2 (04:55):
About AI and chat and GBT, I was.
Speaker 3 (04:57):
Already sort of in the mix of exploring AI and
machine learning, etc.
Speaker 2 (05:02):
When Chat GPDBT launched.
Speaker 3 (05:04):
In many ways we benefited from that because it educated
the world on what this AI thing is and we
became a part of that conversation because the name of
the company Spree AI, and so when people are searching,
we come up until we get a lot of that
SEO and so in many ways, it was very meaningful
to us.
Speaker 1 (05:22):
So when you went to start raising money, was there
like already an MVP in place, or was the convergence
of the idea just situated such that investors are like, yeah,
he's billy AI, that's throw money at it.
Speaker 3 (05:35):
Yeah, it was the convergence of the idea. I think,
you know, entrepreneurs, one of the challenging things is raising money,
amongst many things. I think specifically for me, I was
very fortunate, bless that I had a reputation because I
already had startups before that I sold, and I already
had worked in tech until in many ways, the investors were,
for lack of better words, investing in me. It wasn't
(05:55):
necessarily about the product. And I know that's not usually
the case for entrepreneurs, and so I wouldn't say it
was easy for me to raise money, but it wasn't
as difficult as maybe someone that's starting from scratch to
you know, raise money and then you know, start their journey.
Speaker 1 (06:12):
Yeah. So how do you then, because you've exited twice,
you know, kudos to you for that, how do you
personally define generational wealth?
Speaker 3 (06:23):
Yeah, it's it's so funny that you mentioned that for me,
I've never in my entire life been basically motivated by opportunity.
It's sorry, buy money, not opportunity. Yeah, yeah, sorry, I've
never been motivated by money. It's been mostly about opportunity
and obviously money falls with that. And so, you know,
(06:43):
I'm first generation Nigerian. My parents grew up poor. I
didn't come for money, and so you know, my parents
had to sacrifice a lot to come to this country
and basically create a means for us to you know,
live and be where we are to today. And so,
as I said, to begin through this journey, it became
very apparent to me that you know, oftentimes when we
(07:04):
think of success, especially in our community, sometimes it's comparable
to things that we see in our eyes all the time,
like sports and things of that nature, right, and so,
but we don't necessarily translate that to tech at least yet.
I know it's getting texts becoming more mainstream. And what
I mean by that is when you think about someone
(07:25):
like Lebron James or Michael or Michael Jordan, one of
the things that comes to mind is this person is
a unicorn. They're kind of a one of a kind
and they're basically about to put on for their family
and friends and so forth. And so I started to
carry that same mindset with me, and I realized how
fortunate I was because a lot of the technology that
I learned was all self taught.
Speaker 2 (07:46):
Right, If you think about the complexities.
Speaker 3 (07:47):
Of technology, it's not an easy thing to get into,
just like arguably it's not easy to get into the NBA.
And so in many ways, this is like a once
in a lifetime opportunity. And so generational wealth means to me,
it's not about me, it's about everyone else around me,
plus people that aren't here yet, So my kids, my
kids kids, setting up a foundation that they don't have
(08:10):
to work as hard as I did, and being able
to have a stable company to where you know, maybe
you have a son one day and you're like, yo,
he needs an internship. I'm like, I got you right,
Being able to like form those connections and help elevate
other people that are around.
Speaker 2 (08:25):
Me as well.
Speaker 1 (08:27):
Yeah, something you just said there is like I'm going
to do my best to formulate the question out of this,
but I'm hoping you just kind of get what I'm
trying to say. So you just said something that. I
also heard another recent interview Todday or youreende frough Campus
just said also in that you're not necessarily thinking about
the money opportunity when you're going to build something because
(08:48):
the money that's part that part is a given when
you've achieved the mission. And I think, like so often
we get money focused by because we're taught to. You know,
when you when you talk about you know total you
know market opportunity, you know TAM, you know the total
addressable market, the you know all those sorts of things.
You're thinking about dollar signs. And what I hear you
(09:10):
say is like I'm thinking about, is the opportunity big enough?
Speaker 2 (09:14):
It?
Speaker 1 (09:15):
Can I make a big enough dit in the world
to where if I do that, then the money is
like a given? Does it make sense what I'm trying
to say, Like we're trying to get like some money focused.
We talk to be money focused in one way, but
you're saying, let's just focus on the concept and be
big enough.
Speaker 3 (09:30):
Yeah, exactly, I get exactly to say. I think though,
to play Devil's advocate. Where it becomes challenging is when
you don't come from money and you're trying to survive
until money becomes a priority because you're like, yo, I
gotta eat right, and so I think that becomes challenging.
But I think naturally for me, the way that I
was raised is, you know, we weren't rich or anything
(09:51):
like that. Like I said, we you know, my parents
got good jobs later on in their careers. When we
were growing up, you know, we used to share the
same room things of that nature. There's you know, there's
four of us between our brothers and sisters. And I
just realized what was really important was for me to
leave my impact on the world and create something that's
so meaningful that it would last forever.
Speaker 2 (10:13):
Right.
Speaker 3 (10:14):
And then if you think about it from that notion,
anything that is meaningful in the world, the money does
come from that. It is associated with that, right. And
so I just felt like, you know, I'm a religious person.
I know not everybody is.
Speaker 2 (10:25):
That I had this.
Speaker 3 (10:26):
God given talent and it was my duty to get
back to the world these skill sets and if it
brings money, which it has, that's great, Right, then I
can use that to provide for my family and friends
and the people that aren't here yet that I haven't created.
Speaker 2 (10:41):
So
Host
Will Lucas
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