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Syed Alam Transforms Healthcare Through AI: Early Cancer Detection Five Years in Advance · The Inspired Stories Podcast

0:04
Welcome to another edition of the Inspired Stories podcast
0:08
where leaders share their experiences so we can learn from
0:11
their successes and be inspired by how they overcome adversity.
0:15
My name is Anthony Kotaspodi and today's guest is Syed Alam.
0:18
He is the founder and CEO of Xen Edge.
0:20
It's an IT services and consulting firm that provides
0:23
solutions in cybersecurity, digital transformation,
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artificial intelligence, and cloud computing.
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They also serve healthcare, financial services, retail, and
0:33
government. They help these sectors adopt
0:36
secure, scalable solutions, and their mission is to drive
0:39
positive change by leveraging advanced technologies for early
0:43
cancer detection and democratic engagement.
0:46
Syed has more than 30 years of proven leadership in technology
0:50
and business. He founded Accentage to focus on
0:53
healthcare innovation and empower communities worldwide.
0:56
He led strategic initiatives as managing director at Allen
0:59
Company and served as Global head of Digital Transformation
1:03
at AB V. Under his guidance, Accentage
1:06
has contributed to global transformations, which we'll
1:08
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1:11
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1:48
All right, back to our guest today, the founder and CEO of
1:51
Exenage Syed alum. I appreciate you making the time
1:54
to Share your story today. Good morning, Anthony.
1:57
Thank you so much for giving me the opportunity.
1:59
Really looking forward to a good conversation.
2:02
Let's get into it then. So Syed, your journey started in
2:06
Pakistan decades ago. What was it like growing up
2:09
there and what opened the door to the USA for you?
2:14
So yeah, I grew up in Pakistan and it was great.
2:19
I mean, I actually grew up in a military base there.
2:22
My father worked for the government and he he was an
2:27
engineer and I grew up in a in a area where, you know, we had
2:33
access to good education, good facilities for healthcare as
2:38
well as education. And growing up, one of the
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things that I always looked up to was the United States.
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And I always looked, you know, through the TV, through books
2:51
that I read about, you know, that, that this American system,
2:56
this American way of living. And I, I really admired her.
3:01
So it was always my goal to come to America to learn about what,
3:07
what drives this. And so after my secondary
3:11
education, I arrived at, you know, University of Wisconsin,
3:15
Milwaukee in the fall of 1984 to begin that journey.
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And so tell us about those early days coming to the States.
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Did you already speak English? Was the culture a big shock to
3:29
you? Yeah, I I did speak English.
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As I said, I grew up in an area where we had access to good
3:36
education. So English obviously I had, and
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I still have a little bit of that accent, but I did
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understand and others understood me.
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So I had, I had that skill already, but when I landed in
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Milwaukee, WI and went to my dorms, that's when I started
3:58
interacting with my, you know, you know, my other students in
4:02
the dorms and we started becoming friends.
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And immediately what I realized was that I was in a place where
4:11
people were extremely welcoming. They're extremely generous and
4:17
they're extremely excited to learn about me, you know, asking
4:21
simple questions like do you have pizza in Pakistan?
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Do you have ice cream in Pakistan?
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And some place, people may think that it was inappropriate in
4:30
today's politically correct world world, but I didn't feel
4:35
that way. I felt it was they were just
4:37
trying to be friendly and they had legitimate questions that
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they wanted to ask me and they would invite me to the Trivial
4:46
Pursuit games and would be ping pong.
4:49
The things that I was good at, they will, I will share with
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them and the things they were good at they they would share
4:57
with me. So I think it was just like
5:00
really I, I, I couldn't believe how seamless it was to, to make
5:07
friends, to share I, you know, ideas and moments immediately.
5:13
It was such an open society that I, I, I was really, really not
5:19
worried. And it just happened over time
5:21
that I, I became more adept at the American culture.
5:28
So it was not a shock. I think it was more like
5:31
assimilation of me. Lots of curiosity on your.
5:37
Yeah, explore. And understand what this this
5:39
whole country was about. Right.
5:40
And, and the same way I think it felt that, you know, my people,
5:45
my, you know, people on my dorms that were in my, you know, in my
5:49
house, on my floor, they were genuinely interested in me as I
5:55
was in, in the, in them. So I think it it really was
6:00
amazing. And I still have those friends.
6:02
I still have those memories of those early days.
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How did your interest in both business and technology begin to
6:11
develop? So I came here for those two
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reasons. Number one, to learn about
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technology, you know, because obviously United States is the,
6:22
the technology technological power without any, you know,
6:27
peer and also the business. So I wanted to learn those
6:32
things and I wanted to take those things back to Pakistan,
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which which was a recently in the 84, it was only like, I
6:40
don't know, 30-40 years old from 1947, an economy that was that
6:46
was just trying to get a footing.
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So I want to take all those things back.
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I was, you know, I was interested in technology from
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the early age. I remember one time our father
7:02
went to Germany on an official trip and he brought better, you
7:06
know, those they, we used to have those pool tape recorders.
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I don't know if anybody else remember.
7:11
I do real and I would, I would, I just open it up and, you know,
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I want to see what's inside it. So I've always been interested
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in technology all my life, so you know, so obviously to come
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here and look at what's the cutting edge was a draw for me.
7:32
And So what was coming out of college?
7:34
What was the first job that you had?
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So I, you know, it's interesting.
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So I, I started work. So first, first year I didn't
7:44
work, you know, and then the first summer that I was, I, I
7:50
work, I started working on campus as a foreign student who
7:54
was in a visa. I only was allowed to work on
7:56
campus up to 20 hours a week. So I had to look for jobs on
8:01
campus. So in the summer I work, work in
8:07
our dorms. And then, then I, you know, in
8:12
the fall, when the new Jobs came out, there was a position for an
8:17
assistant at the university's power plant to run their Apple
8:20
computer, to run reports. And I, I, I got that job.
8:26
So I started working right away. And that's what I loved about it
8:31
that I was looking every time I would go to the UNI.
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And those days we used to have card box, you know, the index
8:38
cards on, on boards and you just look at what jobs are available.
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So every time I pass, you know, look at a job, the job board, I
8:45
found that I applied it, but then I got it.
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So I started working right starting the second year that I
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was. While you were in school.
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While in school and then then the final year I you're allowed
9:01
to do practical training in business.
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The law allows you to go and work at a company and and
9:09
outside so you can have that practical training in a
9:13
business. So in, in the last year, last
9:17
semester, I then went to work for a, a major Wisconsin bank
9:25
data center doing MIS work, which was my degree in MIS and
9:30
finance. So I became a programmer there.
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So again, that, that that is something that I didn't know was
9:39
possible because in Pakistan at that time that didn't happen.
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But here I got engaged, you know, whatever you're.
9:46
Getting really great work experience while you were still
9:49
finishing up your first degree. Right, so, and then three months
9:53
into my internship, my boss came up to me and said, Hey, we would
10:00
like to hire you full time. If if you, if you when you
10:04
graduate. So then one, you know, whatever
10:09
day it was, I graduated the next day I was, I was working.
10:13
And so I had I, I actually, I didn't, I interviewed for my
10:17
internship at that that organization.
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But after that, I didn't interview with anybody for five
10:24
years 'cause I. What was you think they saw on
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you, Sayan? I think the most important thing
10:32
that I've learned is the relationship that you have with
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people. I think people like to work with
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people that add value and that are that they can count on.
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So I think that's what they saw that I would.
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I mean, even, you know, I don't know where you live.
10:55
Maybe you're, you know, in your area you have blizzards.
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We do. Wisconsin, there's a lot of
11:02
blizzards and they saw on me that even if there was a
11:05
Blizzard, I found a way to get to work.
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They saw that, you know, I took my work seriously and I put in
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an honest 8 hours of work. I think that really is what my
11:23
personal experience has been, that people are not necessarily
11:27
looking for geniuses, they're looking for people that they can
11:31
count on. Just being dependable was a huge
11:35
part of your. Just being, just being
11:38
dependable and being part of a team where you look at, you
11:45
know, what the team is trying to accomplish.
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So I think that they enjoyed working with me and so they
11:52
wanted to keep me around. I think that's probably the
11:55
simplest way to put it. Makes a lot of sense.
11:58
I want to spend quite a bit of our time talking about, you
12:00
know, what you're doing today with Extent Edge.
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But before that, maybe hand pick one of your career stops outside
12:08
of Extent Edge and why it was so formative for you in the way
12:14
that you approach your work and Business Today.
12:18
Yeah. So what, what really as I, as I
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was evolving myself by going through these experiences, you
12:28
know, of working at corporations.
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At one point I realized that working without in a large
12:39
corporation was limited for me. I think I wanted to, I wanted to
12:46
do more things and I wanted to do things where I had more
12:53
control over what I worked on and how it I wanted to see how I
12:58
impacted the world. So I had a great job at, you
13:04
know, at a major consulting company at that time, one of the
13:08
top technology consulting companies at the time.
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And I was doing great, but I got an opportunity to do some
13:17
groundbreaking work. So I just drop quit that job and
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I went and I started my own business.
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So I think it was that defining moment and and my core of what,
13:34
what really I want to do is to first of all work on things that
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I like to work on and I want to see those things making an
13:43
impact. And I think it allowed.
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Having a business allows me to do that.
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Say more about this opportunity that came about to I think your
13:52
words were do ground breaking work.
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So, so this is Milwaukee. I think it's it's like 1992.
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I'm finishing up my MBA at Marcotte and I I was paired with
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with a person to do a project for a major manufacturing
14:13
company in Milwaukee where one of the problems that the the
14:20
manufacturers has is how much to produce for the next quarter.
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Because if they produce too much, they have more costs of
14:30
inventory and if they produce less, they have, they miss out
14:36
on sales, lost sales. So we did, so this is from a
14:41
statistics class. And what we did with our project
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was we took that company as an example for our project and we
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did a time series statistical model where they could predict
14:52
what their sales would be based on their, you know, and there's
14:57
a whole science that goes behind that in terms of, you know, how
15:00
you, how do you apply that science to it?
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So we that did that model and we presented that at the senior
15:08
management at that company. And the senior management tell
15:14
my partner who was, who was the manager there.
15:16
So who is this guy? If he wants to do this in, in,
15:21
in a real, as a real project, we'll give him a project.
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So they gave me a $50,000 project.
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They said, I said, sure. So for $50,000 project with one
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company, I quit my job and I started on that because I
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thought that was something that was more meaningful for me to go
15:40
in an area where where we could we could.
15:47
I could see that this is an area that's unexplored because even a
15:51
major corporation was used to stuck struggle with that.
15:55
Did you feel ready for this project?
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Were you at all kind of intimidated or like I'm just
16:00
wrapping up my MB AI? Don't know if I've got what it
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takes to pull this off. So, so I I don't know if if
16:10
intimidated is the right word. I think and, and my and my days,
16:19
I think I look, I'm more like driven by learning and, and
16:25
exploring and just going for it. So I think it was very exciting
16:33
to me and I was learning a lot about that.
16:35
And I think the exposure that it was giving me to actually talk
16:40
to real business people and, you know, have them give me
16:45
feedback. I think that was just too
16:48
tempting to for me to when I compared with where I working
16:55
for major Brewing Company as as part of this consulting team
16:59
where I had a very limited impact on, on, on what.
17:06
This was a chance for you to learn to get feedback on your
17:08
ideas and your processes and be able to throw your line in the
17:12
water. Right.
17:13
And I think I have kind of a blind spot for for fear like,
17:21
you know, I think because I think people said, hey, 99% of
17:24
the people at the time that said 99% of the people would not, you
17:30
know, drop your job or quit your job and go on their own on just
17:36
one project. So.
17:38
And you say a blind spot for fear, meaning you don't feel
17:41
fear. I, I think what I, I think, I
17:47
overlook that more so I've, I've learned and my experience, I've
17:52
learned and my experience that I overlook fear and my decision
17:56
making process more so than I think so.
18:01
It's not that you don't feel it or experience it.
18:03
It's you like, oh, there's the fear over here.
18:07
I'm going to look in this direction instead.
18:10
Right. Or this is the way to overcome
18:11
that. You know, I would say, OK, if I
18:14
did this, like it, it would be fine in the end, because if I
18:20
keep doing it, it would be fine. And so, and I think I was very
18:24
young at the time, I wasn't married.
18:26
I, you know, I could start over rather easily.
18:31
So I I valued those things more that my, my, my youth, my skills
18:39
and the fact that I had the ability to relatively easy start
18:44
all over again it over, you know, it, it bade more than the
18:50
security of the job that I already had and the next
18:55
promotion and all that. So that wasn't that exciting.
18:58
Was that first $50,000 job successful?
19:01
Did it lead to more work with that client or referrals for
19:04
other companies? Right.
19:06
So it it yeah. So it's was successful, but it
19:12
didn't immediately leave lead to more work because again, there,
19:19
there had to be processes to follow through on that.
19:23
And so then I had to learn how to get more work right.
19:30
So, so I did, I, I thought that so we, I didn't get to meet at
19:36
work. So we finished the project.
19:37
It was great and they loved it. But you know.
19:42
Now you got to go into business development mode.
19:44
You're. Right, probably didn't have
19:45
experience with a lot of a lot of people.
19:48
And I think that's true. In my experience, a lot of
19:50
people think that if you do a good job, the the follow on work
19:55
is automatic. It it is not.
19:58
I mean the business that you're working for, even though they're
20:00
doing a great job. It doesn't mean that they will
20:03
immediately shower you with more work because they have their own
20:06
budgets, they have their own priorities.
20:09
They may bring you back maybe after three months, maybe I was
20:13
six months, maybe after a year. But for a legitimate business,
20:17
it has to have the capacity to generate more business.
20:21
You can't just say that, oh, I'm going to skip.
20:24
So it didn't happen. So then I had to figure out how
20:29
to get more work and that led me to the area of marketing, that
20:35
led me to the area of sales, making cold calls, dialing for
20:38
numbers, doing, doing collateral myself.
20:45
So yeah, so and then it look took me to other areas.
20:49
So I did find work. That's what I'm saying.
20:51
I did find work and. Who taught you about business
20:56
development and marketing? So I relied a lot on what I had
21:03
learned in in Business School and a lot of people say that
21:07
Business School is not that useful, but I think it is.
21:10
It gives you the framework. I think so and those things kind
21:14
of worked, but I think that what you have to do is to complement
21:19
with your network. So the people that I worked at
21:22
the bank, the people that I worked at the consulting company
21:26
and the people that I work at my first client, they all know
21:31
other people. So, so it so you do that.
21:37
You first define who you are, what, what you add as value, but
21:41
then you leverage your network and then you leverage your
21:45
collateral. And then you have to overcome
21:48
the fear of calling strangers. So you have to do everything
21:53
right. So you know your education, your
21:58
experiences, your network and your skills.
22:03
There's no one thing you have to kind of come up with your
22:06
formula at how you're going to balance all of that, that
22:12
results and and and work. It, it strikes me that to go
22:19
through sort of these different phases of growth that you have
22:22
to be sort of at your core, curious, willing to put yourself
22:27
in uncomfortable situations and open to a variety of different
22:32
possibilities because you, you, you're, you're pushing yourself
22:35
in directions that you hadn't gone before.
22:39
Right. You know it is, it is.
22:42
And I think that that is that is, that is the, to me, that has
22:46
been the most exciting part because in America you can go
22:53
and you will make it work. It will work because there's a
22:56
there's a system that that does structures and transparent.
23:01
And I think I found that having that opportunity to make things
23:06
work where you, there's a predictable system in terms of a
23:11
structure, in terms of, you know, the capital markets, in
23:16
terms of the legal system, all those things are transparent in
23:21
structures. So you can depend on those
23:23
things you know and. You think this is a
23:26
differentiator for the USAI? Do think that because I, I do
23:32
business with, I mean today I do business in many countries
23:35
outside the US, many, many countries and we know that we,
23:42
we know that why or I know personally, I mean, I, I do
23:46
business in Pakistan. I do a lot of business in
23:48
Pakistan and I can tell why it is that, that it, it, it doesn't
23:58
become, it is not able to tap into that talent of 250 million
24:04
people. These inefficiencies and these
24:08
not having a transport, a transparent structure system,
24:12
how that chips away for that. So it, it actually makes me
24:19
value the United States systems more because you can see that.
24:25
You can see there's an incredible idea, there's an
24:28
incredible person, but there's no capital markets because
24:32
there's no transparency, there's no liquidity.
24:35
You people are extremely smart, but they can't get the.
24:40
They don't have access to the funds to.
24:42
They don't have their. Ideas.
24:43
On the action. They don't have access to the
24:45
firm they don't have access to I mean as simple as mailing system
24:52
US mail. I'm in a lot of places on this
24:56
world and it doesn't matter. I mean, still matters, but it
24:59
before it didn't having a predictable, you know, mail
25:04
system like 6 Sigma plus accuracy for mail system is
25:08
important because you know that at least what you're mailing
25:10
10,000 pieces, almost all of them are going to hit at at
25:17
almost a predictable time frame. So you can plan against that.
25:22
So I can see that that how those things you know, 'cause issues
25:30
with certain certain locations. So the transparency, the capital
25:35
markets, the legal structure, that's all made the USAA great
25:39
place for you to start XN Edge and grow it from.
25:44
You're now doing business in multiple countries around the
25:47
world. Let's Fast forward a bit and
25:51
talk about the state of the company today.
25:53
What are the services that you actually, let me, let me rewind
25:57
for a second because I understand that there was a bit
26:00
of a transition that took place through the COVID years.
26:03
So why don't you kind of Fast forward us to maybe 2018-2019,
26:08
what the state of the company was and and then let's
26:11
transition into that sort of COVID story.
26:14
Right, So right before I the next sentence, I, I was with
26:21
ABV, which is I think it's like an hour $60 billion
26:28
pharmaceutical company and I was leading the digital
26:31
transformation efforts at that time.
26:34
It was just starting. It was 2014, fifteen, 1617.
26:38
I was there and I just thought that again, I had I had that
26:48
feeling, that limiting feeling of, you know what, what am I
26:55
doing? Yeah, I'm delivering projects,
26:57
I'm saving the company money and I'm, you know, helping the
27:00
company succeed. But what does that really mean
27:04
from for me because I was so removed to the actual impact.
27:08
So I started this savage and to really focus on digital
27:17
transformation of large corporations, what I had learned
27:21
at FV and other large companies that I've worked before.
27:25
And again, I just laughed and I relied on my network.
27:33
I had friends and colleagues that I'd worked with at major
27:38
airlines, major financial institutions, major chemical
27:42
companies. Chicago is a large economy.
27:44
So if you're working in Chicago, you can actually develop a good
27:48
network. So we started working with them
27:51
and we're extremely profitable. This is like mid 2018.
27:55
And come I was, I was at my health club, a gym in morning in
28:03
May a bit right before the March Madness.
28:08
It was March and I was watching TV and they said The Who has
28:13
declared COVID a global pandemic and everything shut down.
28:18
And we were really having a good time.
28:20
We're doing a lot of AI work. We're doing a lot of deal
28:24
transformation work. And our airline client said,
28:27
look, it's not you we're shut down.
28:30
You know, we're not flying planes.
28:32
We don't want projects. You want to survive.
28:35
Our bank's client said we are not looking to give out more
28:38
loans. We're trying to hurt the cattle
28:40
to see if we're going to survive this because everything is shut
28:44
down. And I had all this stuff, you
28:47
know, of really, really smart people that were doing great
28:51
job, you know, and they were enjoying it and they had
28:54
meaningful work. And so again, I saw.
28:59
So I had to pivot or we had to pivot.
29:01
And we said, well, who is spending money right now?
29:05
And there were two areas where there was a lot of spending,
29:08
healthcare and government. So we said, OK, in all
29:13
commercial enterprises are not spending.
29:16
So it's going to be a very tough sell.
29:17
Let's go sell to the government and let's sell to healthcare.
29:22
So we redeployed our AI experts that are working on on
29:29
commercial projects for commercial clients on AI and we
29:34
put them on healthcare for, for and then we went after the
29:40
government. And then what we ended up doing
29:42
was we immediately became a leader in early cancer addiction
29:51
to our people that had experience in that in the
29:54
healthcare sector. And then we ended up getting
29:58
contract. One of them was with the
30:00
government, one of them was with the United States Senate.
30:03
Because what happened was senators have to be with their
30:09
constituents and with the COVID, they couldn't be.
30:14
And because they they couldn't do town halls, they couldn't go
30:17
not shake hands. So how do you do that?
30:20
So we then came to the US States Senate and we put in a service
30:26
where we could allow them to do everything virtually.
30:30
When we put up an office at the village centre in downtown
30:34
Washington, DC where they could record, you know, you know,
30:38
videos, they could, it's an, it's, it's, it's, it's a mile
30:42
from from the US Capitol. So they could switch and record
30:45
something real quick. They could do town halls, they
30:48
could do all those things to really Democrat to engage with
30:53
their with their, with the constituents.
30:55
And that just grew into one of the major business areas that we
31:00
focus on as democratic engagement.
31:04
So that, but when we powered that, that engagement through
31:08
technology, we also saw opportunity to do it better than
31:12
in person, right, Because so we so it's better engagement and
31:17
how to fight misinformation. What are some of the tactics
31:21
where so that went into that our early cancer detection algorithm
31:27
that we had developed, we actually went to Tokyo and we
31:31
competed with over 1200 companies on early cancer
31:35
detection algorithms and we actually won that in Tokyo for
31:40
this major Asian competition that they have.
31:45
So and then so going into the pandemic, we had one business
31:51
and coming out of the pandemic we had three businesses.
31:54
OK, so again, I want, I want to peel back the layers of the
31:56
onion here a bit because you know, we're talking about it and
32:00
we sort of condense the story into just a couple of minutes.
32:03
But what you're talking about is a pretty drastic change in the
32:09
direction of the business. You guys going into COVID, you
32:12
had a lot of good work with banks and airlines, right?
32:15
And then airlines aren't flying. They're like, we're in survival
32:19
mode. Banks are like we're in survival
32:21
mode. So the spending stops there and
32:24
the whole world is panicking, right?
32:26
I mean, there's some industries where spending his way up there,
32:28
other industries where the the spending just stopped.
32:32
And I think maybe this is a bit of where like you just kind of
32:35
overlook the fear part because a lot of people just they, they
32:38
sort of like were shaking on their boots.
32:40
They're stuck. They don't know what to do.
32:42
You guys made, you know, not one, but you know, multiple big
32:47
pivots in the industries that you weren't really working in
32:50
before. How did that actually transpire?
32:54
How did you actually get contracts with the government?
32:57
How did you actually get into cancer detection when that's not
33:01
something you were doing previously?
33:03
So, so, OK, so let's take one at a time and if I'm going too
33:09
long, please stop me. So the scenario is that so you
33:16
know, there's a global pandemic and within overnight we lose 80%
33:21
of our business other than what we have long term contracts, all
33:24
the project were was stopped. So we lost 80% of our business.
33:32
So when you say, OK, let's, I will go and do the government
33:35
route first. So we say how do, how do you do
33:38
that? So one of the things without
33:41
about government is if the government is spending more than
33:45
$25,000, they have to let you know.
33:49
So commercial, they don't have to tell you if they'll work or
33:51
not, but the government does. And there's a website called
33:55
samsam.gov that lists every single opportunity, every day
34:01
that the government is, you know, purchasing for.
34:05
So we just went to the sam.gov, created an account, registered
34:09
and you have to register with that and you have, they have to
34:11
vet you and you have to with government.
34:14
There's a lot of paperwork, but you know, we did that, you know,
34:18
I mean, again, this doesn't happen without work.
34:21
There's a lot of work, There's a lot of 1618 hour days doing in
34:26
front of a computer, making sure you know, and creating like the
34:29
government contracts. There's a lot of paperwork.
34:32
So we, but it's, it's a, but it's there, you know, there's
34:36
work. So you we it's a search engine.
34:39
So you go and you search what products you can do, what talent
34:43
you have, and then you bid. And the thing with the
34:46
government is, you know, again, it's, it's transparent.
34:49
So, so, so that's how we went there.
34:52
So, so you say I'm going to go for government.
34:55
So you'll find out how you get to work with the government,
34:58
then you go So the on the healthcare, so healthcare, I did
35:03
have experience. We did have experience because
35:05
we, I did work with pharmaceutical companies and
35:09
there was Cancer Research there and I was responsible for
35:14
providing the technology that was needed for those particular
35:18
skills. So what we do is then again, we
35:22
leverage our network and we say, hey, we have, and then we have
35:27
people who had experience in that.
35:29
So we, we then just completely focused on that redeploy the
35:38
people who are working on their sectors to the pharmaceutical
35:43
sector. But we honestly worked, we were
35:45
already working there. So the people who were already
35:47
experts in that mentored the new people who were there.
35:52
So, and that's what I said before when we first started
35:57
that one of the things that we make sure in our company is that
36:01
we hire people who want to work and who want to work with other
36:06
people. So then those people mentored
36:09
them and obviously everybody was worried that what's going to
36:12
happen if they didn't, you know, retain this job.
36:15
So everybody kind of pull together and we and then we
36:20
leverage the network at major universities.
36:22
And after we won the award, there's incubators in Chicago,
36:28
there's one called Matter, which is actually one of the most
36:32
recognized healthcare incubator in the world.
36:35
And we connected with them. We set up an office there so we
36:39
can then leverage healthcare related ecosystem.
36:45
So again, it it's not in a vacuum.
36:50
So we would find how to enter that market and go after that
36:56
and then learn and show up. So you're somebody said that you
37:03
want to work, you're adaptable, you want people to work for you
37:09
that also want to work and they're adaptable.
37:11
When you're going through sort of that hiring and that
37:13
screening process, how do you filter for that?
37:18
How do you how do you figure out that person is going to fit in
37:21
our culture here? I think a lot of that you can
37:25
tell by how they answer questions, the words they use,
37:33
their temperament. I mean, it's all, I mean, we are
37:36
all human. So if you are even on on on a
37:38
screen, you can tell what what is, what is this person's
37:44
assets, right? I mean, are they friendly?
37:46
Are they, I mean, are they, you know, you know, tough or you
37:52
know what, what is, what is it that they like to do and what
37:55
kind of person they are? So I mean, we look for people
38:02
who who would be open to working with others and working, you
38:11
know, in a positive way as a team member.
38:13
And, you know, typically you can ask those questions to people
38:18
and the way they answer it, you can typically.
38:20
What's the question that you would ask?
38:23
You know, one of the questions that I, I, I like to ask is
38:29
explain to me how you, you work with your team.
38:34
You know what, what is your role?
38:36
Let's say you are a team member. How, how would you contribute to
38:40
that team success? Where you get your information
38:44
and how do you make sure that that you're going to be a good
38:49
member of the team? Just ask them play it.
38:52
You know, how do you do that? Put that question to them and
38:57
the way they would answer that would give you cues to to what
39:02
you know how they view the team. How do you working within the
39:05
team? I want to go back to a couple of
39:09
the things you talked about as you came out of the pandemic
39:13
with three businesses. You went in with one, you came
39:15
out with three. And two things that really
39:17
caught my attention is, you know, you figured out how to do
39:20
some of the things within government better through the
39:23
technology. And one in particular was how to
39:26
fight misinformation because it seems like this is something
39:29
that is still a giant problem, maybe even bigger than it was
39:32
going into COVID. What what are some things that
39:35
you guys have figured out? What?
39:37
What kind of tools have you built to help with this?
39:39
So we actually built a tool and where we can tell what what is a
39:48
particulars legislators, you know, how far their voice is
39:53
going, you know, what is their rating?
39:55
We rate them. There's how effective they are
39:57
because all all the legislators at the at the federal and state
40:03
level, they all have twitters, Facebook, Instagram, all those
40:08
accounts and they are pushing information through that.
40:12
And a lot of that is coming back to the website.
40:15
People are getting that information and we.
40:17
But what people don't realize is on any particular topic, they're
40:22
public interest groups that are also intercepting that
40:26
information and they're also pushing that and from their
40:29
particular information out and they're spending a lot of money.
40:33
There's a lot of money that's spent on keywords that related
40:37
to the the topics that are in front of the government.
40:42
These public interest groups as well as commercial interest
40:45
groups kind of are also doing the same thing.
40:49
And what we do is we look at at the positions of a legislator
40:53
and what they're speaking about and then compare that with all
40:56
the other information that is that's being pushed from
41:01
interest groups. And we kind of have a way, we
41:04
have developed a way to determine how we can tell and
41:09
advise them that their voices are being drowned, drowned out
41:15
or they're, you know, breaking through.
41:17
And if they're if they're being drowned out, we give them
41:20
strategies to breakthrough that so their position gets out.
41:24
And again, we have a two party system.
41:27
So you would not only look at the pub, you know, and the
41:29
interest groups of, but you also look at the, the two spectrums
41:35
of our political system and see which one.
41:38
Now we're neutral. So we don't, you know, we, we,
41:41
we are, we, you know, support our clients.
41:44
So we really don't have an interest on which, which
41:47
particular position it is from either party.
41:50
But we can tell them we have these, we developed these
41:53
systems to do that. We also help them with how to do
42:03
to their websites better to how to kind of, you know, feed, feed
42:09
the traffic to them. And so so that is providing.
42:15
Them you're providing them with a wide array of services.
42:17
Right. And that they couldn't do that
42:21
in person. You can't do that.
42:23
So because everything on, on, on, if you're online, everything
42:29
is being traced and matched and you know, processed to very,
42:34
very large scale systems. So let's go to the other new
42:38
business that you created coming out of the pandemic in
42:41
healthcare and cancer detection, not a person alive whose life
42:45
hasn't been touched either directly or indirectly by
42:48
cancer. Can you give us?
42:50
So I think this is going to capture a lot of people's
42:51
attention. Can you give us one specific
42:54
example of something that your technology has been able to help
42:58
with in earlier detection of cancer?
43:01
So are we. So what we developed initial
43:09
that one thing that that won the award in Tokyo in 2021 was
43:16
what's called digital biomarkers.
43:18
So your body has biomarkers that you can detect from like
43:27
imaging, like X-rays, MRICD scans, all that your body will
43:32
tell and it will tell because if you have 100 years of 50 years
43:40
of images and you know that they have longitudinal information on
43:45
those. These people had this type of,
43:47
you know, signature on, on, on their X-ray and they ended up
43:51
developing fatal cancer. And if the signature was there,
43:55
it was not fatal, it was benign. So this, this AI that we have
44:01
started with doing the digital imaging and we would have like
44:05
40-50 years. So we work with major
44:07
universities in the most of them where we have access to that
44:12
information as well as the medical centers and that are
44:16
associated with those these universities.
44:19
So we entered partnerships with them, let's say if you'll give
44:23
us, because we just won this award.
44:24
So now we could go and we can pitch, hey, we have this
44:28
algorithm, we can help you. So we establish those
44:30
partnerships. And So what you needed from your
44:32
partners was that data, the imaging data, so that you could
44:35
feed it into the AI, teach and train the AI so that it gets
44:39
better at detecting. Right and anonymized and also
44:44
not only anonymized, but also diverse because a Caucasian
44:52
person, African American person, an Asian American person, an
44:58
African person, a South Asian person, they all react
45:03
differently their bodies are not the same.
45:05
So if you just do 11 race or one dominant group, it'll be bias.
45:14
So in AI, one of the big challenges having unbiased,
45:18
taking the bias out because some segments of the society have had
45:23
better healthcare. So they have better data
45:26
historically compared to others. So how do you deflate that that
45:31
advantage that they have? So yeah, so we so, but hospitals
45:35
have those, right? Or there's there's lately, you
45:39
know, there's been synthetic data also that that's synthetic
45:44
data. Yeah.
45:45
It can be generated. So the latest AI can look at
45:50
like 50 years of data and then it can generate based on what it
45:55
learns. It can actually generate
45:56
synthetic data. And it does that for the purpose
46:00
of training itself even more. Yes, yes, yes.
46:04
But it's so. That's so unusual.
46:06
It's it's evaluating the this data that it just created.
46:11
Right. Well, it will feed into an
46:14
algorithm. Yeah, So, but but The thing is
46:18
that there is this synthetic data that can be generated.
46:21
Well, just like there's synthetic organs that that can
46:26
be generated. It's the same thing.
46:29
So we started with the imaging, but then we integrated with
46:33
what's called multiomics, your biology of your body because
46:39
even before you have symptoms, cancer actually starts shedding
46:46
signatures into your bloodstream and into your biology.
46:50
So we kind of so now we have a model that does both radiomics,
46:54
which is images and multiomics and integrates that and then up
47:00
to five years in advance we can. For what kinds of cancer?
47:05
We have about 50 that we can actually work on.
47:10
We have, we have trained them and we can predict from them.
47:13
So let's say I'm somebody, my family history, there's a
47:17
history of breast cancer, pancreatic cancer, prostate
47:20
cancer, bladder, whatever it is. And I'm like, hey, I feel good
47:23
right now. But maybe I'm at that age where,
47:27
you know, things traditionally in my family history have
47:29
started to unravel for some folks.
47:31
Is there a clinic somewhere in the world I can go and have a
47:34
blood draw or a scan and it says, oh, you've got the those
47:38
early shedding markers for XY and Z?
47:42
So the best place is to go to your doctor.
47:46
So that's where you capture it. So I think that we so but but.
47:50
Hang on, Saya, because a lot of doctors, how do I want to say
47:55
this, not everybody is at the forefront of the technology that
47:59
you guys are trailblazing with, right?
48:02
So there's doctors in, you know, big town, small towns that maybe
48:06
you've never heard of the kinds of scans that are available.
48:09
Am I? Am I right or wrong on that?
48:10
No. So that that is that is the
48:13
beauty of it, because it our algorithm integrates with the
48:17
existing systems. The doctor has AEMR electronic
48:21
medical records, they have our algorithms integrates with the
48:26
the systems that already exist. So what it happens is let's say
48:31
they do a blood draw, it just calls our system and our systems
48:36
respond. You don't have to buy $1,000,000
48:38
product. So.
48:41
This. I want to see if I, if my body
48:44
is shedding, it's creating those early markers for pancreatic
48:47
cancer, which is something that, you know, traditionally when it
48:50
shows up, it's too late, right when the symptoms are there, you
48:53
know, your, your time is, is limited.
48:56
So I can go to my doctor today, say hey, draw my blood and what
49:03
happened? How is that getting scanned for
49:05
those markers? So they would use, they would
49:09
actually send it to a lab or something.
49:11
And if the lab we would have interface to our system in the
49:16
lab. So as part of that they would
49:18
just perform one more task that 'cause our system, it's over the
49:24
it's called what's application programming interface or API, it
49:28
will just call that it will feed what it found on your blood and
49:34
it will shoot back the result. So what's the request I'm giving
49:38
to my doctor? I want to be scanned for
49:40
pancreatic cancer. Let's make it pancreatic cancer.
49:44
I think the ideal way would be to just say without specifying
49:48
what you're looking for, because it will, you would know that
49:51
pancreas. So we, we test for pancreatic
49:53
cancer. So it would be like this is this
49:55
is the slate of cancers that it will detect because every test
49:59
detects a certain, you know, for anything, not just for cancer.
50:04
You know, there's screening systems that are for certain.
50:09
But there's there's a name of the product or a name of the
50:12
screening or the scanning or the service that it has to go
50:15
through so that it gets access to your algorithms.
50:19
So our product, our product is the actual algorithm is called
50:26
accentage biomarker, cancer deduction, ABCD.
50:31
And then we actually the latest product that we have is is
50:36
called Doctori. What that is, that is actually
50:41
based on generative AI. So you can actually have a
50:44
conversation. So we'll take the latest
50:46
iteration of that is where you can actually have a conversation
50:51
with that. So that generative AI so that we
50:54
did that pivot because the world just changed after ChatGPT came
50:59
out. So generative AI.
51:03
So we are putting on top of our science and technology this
51:08
large language model for generative AI where you can have
51:12
a conversation with that at this point.
51:14
I mean, it's coming. It's not there yet, but that's
51:16
our latest, yeah. It's fascinating.
51:19
Wow, really mind blowing cutting edge stuff.
51:23
Let's take a little bit of a detour though, Syed, and I'd be
51:26
sure because we're your company is very successful.
51:29
Obviously we talked about the hardships you guys went through,
51:31
you know, in COVID actually let's let's come back to that
51:35
because it, it strikes me as that real, that giant hardship.
51:38
There was actually a chance for you guys to reinvent yourselves.
51:41
And as painful as that transition was, is there a part
51:46
of you that has some gratitude? Looking back on that is like,
51:49
wow, that, you know, look, look at the company we became because
51:52
of that that we might not have otherwise.
51:55
Yeah, I don't have the gratitude of for the COVID because I lot
51:58
of people died for it. So I mean, obviously that was
52:01
that was heartbreaking, but we lost, but I think where it took
52:08
us as a business and this is where we are today.
52:13
So one of the epiphanies that that I, it also improved our
52:19
profit margins because one of the epiphanies that I had was
52:25
that if you solve the biggest needs of the humanity, actually
52:30
it's the biggest opportunity to make money.
52:32
People don't realize that because by definition, you know,
52:37
if like cancer, who, who would want a discount on cancer
52:41
treatment, right? If you have a loved one and
52:46
you're going to pay what they asked for because you're trying
52:48
to save somebody from cancer who would ask for a discount for
52:54
protecting their hospital from cybersecurity attacks, who would
52:57
do that? Who would?
52:59
So if you saw humanity's the toughest challenges, that that
53:04
is also the biggest opportunity to make a lot of money.
53:07
So we realized that coming out of that.
53:10
So I have gratitude for that, that it, it actually changed my
53:16
mindset where a lot of people are saying, you know, niche
53:22
things or small things. And if I can find this and I can
53:26
cut cost to a certain bare bones and I can do this, I can make, I
53:29
can increase my. But how about thinking big?
53:32
How about thinking about? So that's why we focused on and
53:35
now we focus on solving big problems because not because,
53:43
well, they're problems that need to be solved, but also there is
53:46
a lot of money to be made from those.
53:48
If you focus on that, if you solve that problems.
53:51
And that's one of the other areas that we're looking at
53:53
right now is, is climate change. That is a big problem.
53:59
That's an existential threat. So if we can come up with
54:02
solutions for addressing that, I think that also is, is, is an
54:08
opportunity to make to be a successful business.
54:11
And so this is an area that you're in the process of growing
54:15
into. Right.
54:16
And one of the things that I like to do is this kind of funny
54:19
story. One of the things that I like to
54:20
do is to actually experience this myself, you know, like see
54:26
what it is like. So I recently took a trip from
54:30
Chicago to Yellowstone National Park in an EV which is 1400
54:34
miles one way. And I say, OK, what is the
54:39
experience of an EV? Can I actually, because biggest
54:43
fear that people have that I'm going to run out of batteries,
54:46
right? So no SO.
54:50
What is shocking to me is that there's so much EV
54:54
infrastructure already in place and then the cars have the
54:58
technology will they will route you to the exact same station
55:04
and you can actually charge an EV now and within 45 minutes,
55:10
which is not too bad. If you are next to like Wall
55:13
Drug in South Dakota. I don't know if you know that
55:15
there's like, 'cause they had, they put like Wall Drug, they
55:19
put like EV is actually that. So you can go and you can, you
55:23
know, charge a car and go and get the nickel coffee 'cause
55:26
they still have a place where they still have, they still have
55:30
that. So it was my first time there.
55:32
So you, you go there, you walk there, you go there.
55:35
They put them next to Walmart's Targets and I was at yellow.
55:41
All the, all the national parks have free charging.
55:44
So you actually don't even have to pay.
55:48
Mount Rushmore doesn't have has free charging.
55:51
So, but the issue is cost because if you have high speed
55:56
charging you, you have to pay a lot more.
56:03
So it is actually more expensive than than gasoline almost twice
56:08
as expensive. But but so I think but those
56:12
costs are going to come down. But I think, but that's an
56:17
existential threat. We believe and we believe that
56:20
that's an area how can you help? So I think we need to have
56:25
solutions for that. We need to find ways to reduce,
56:33
reduce emissions and we need to also find ways to generate
56:37
electricity or power for that matter, that that doesn't, that
56:45
doesn't, that is, you know, free neutral, carbon neutral.
56:51
I mean, there's so many ways you, we can build buildings that
56:53
don't waste energy. We can do so many things and
56:57
applying that technologies like IoT or other technologies to
57:01
see, you know how we can kind of bring all that down.
57:06
So we're just beginning to look that, but that's another area
57:09
that we are looking at right now as a big challenge that we want
57:13
to get involved in. So I think I want to wrap up our
57:16
interview with what tends to be my favorite question.
57:19
But before I do that, I want to give you a chance to tell people
57:23
how to either get in touch with you directly or accent edge or
57:28
to follow your story or for that of the companies, what's the
57:30
best way? So the best way, I mean, I think
57:33
would be to just send me an invite on LinkedIn.
57:38
I say it Alam, I'm founder and CEO Accentage.
57:43
They can also visit our website, accentage.com, which has our
57:49
phone number on it and they can definitely call and ask for me.
57:52
I'll be more than happy to. I'll personally talk to any and
57:56
all as long as you know I'm available.
58:01
It's generous offer. We'll include links to to all
58:04
that in our show notes here. But last question for you, Syed.
58:08
What's a serious challenge that you've had to overcome, personal
58:11
or professional? How'd you get through it?
58:13
What did you learn? The personal challenge I think
58:20
was for me was to be alone when I, as I came from a family, I
58:25
came from a culture that, you know, that was surrounded by
58:28
friends and family and I came alone.
58:30
And I think I had to overcome that.
58:34
I had to see how to survive and how to succeed when you don't
58:40
have a support system around you.
58:43
And I feel lucky that I ended up in Milwaukee, WI in America,
58:50
where it is an open society. But that was the challenge to
58:54
rebuild my whole life from a ground up.
59:03
I think in that what I learned from that, whether it's all
59:08
about people, you just have to introduce yourself, say, hey, my
59:13
name is Syed. You know, 99% of the people will
59:18
be open to talking to you. So just show up.
59:22
I think just ask, just do. It's very simple thing that you
59:27
know, you probably your mother told you.
59:29
So don't forget those lessons that you were told as a child.
59:34
And I think everything takes care of itself after that.
59:39
I love that message. You know, safe human connection,
59:42
I think is some of the best medicine that we have, Yep, in
59:45
the world. It's all about people.
59:48
Yeah. And you coming here, you're, you
59:51
know, young adult at the time hadn't lived on your own before.
59:55
You came from an environment where, you know, friends and
59:57
family were close. And now you.
1:00:00
But now you had to meet a whole bunch of new people.
1:00:02
You know, you weren't coming here with that support system.
1:00:04
You you had to stand on your own, and you had to.
1:00:07
Kind of breakthrough that barrier, that fear of and I got
1:00:10
to go and introduce myself and, and I and I've got to find a new
1:00:14
group to interact with. And it sounds like, man, you
1:00:16
couldn't have landed in a better place.
1:00:18
You know the folks that you found there in Milwaukee, they
1:00:21
accepted you arms wide open, right?
1:00:23
Yeah, America. That's America for you.
1:00:28
I love it. Syed Alam from XN Edge, I want
1:00:31
to be the first to thank you for sharing both your time and your
1:00:33
story with us today. I really appreciate it.
1:00:36
And thank you for having me. I appreciate it as well.
1:00:39
Folks, that's a wrap on another episode of the Inspired Stories
1:00:42
podcast. Thanks for learning with us
1:00:43
today.