Latest / AI for Founders with Ryan Estes / AI Is Rewiring Pregnancy Care: Babyscripts CEO on RPM, Risk, and Real Outcomes

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AI Is Rewiring Pregnancy Care: Babyscripts CEO on RPM, Risk, and Real Outcomes · AI for Founders with Ryan Estes

0:00
Welcome back to AI for Founders. I'm Ryan Estes.
0:02
You ever notice how giving birth in America, one of the richest
0:05
countries in the world, is somehow getting more dangerous?
0:08
Maternal deaths are rising, access to care is falling and
0:11
the system meant to protect new mothers is still running on fax
0:15
machines. That's the problem Aneesh
0:17
Sebastian, CEO and Co founder of Baby Scripts set out to fix.
0:22
His company has raised over 37 million, helped manage hundreds
0:25
of thousands of pregnancies, and is using AI remote monitoring in
0:29
data science to reimagine what care looks like when your doctor
0:33
is as close as your phone. In this episode, we get into the
0:36
friction between innovation and regulation, the cultural tug of
0:39
war between doctors sworn to do no harm in patients desperate
0:44
for faster, smarter care. And you'll learn how Aneesh is
0:47
using technology to bridge that gap, why AI might soon assist in
0:51
every pregnancy, and what the future of healthcare looks like
0:54
when access isn't tied to a waiting room.
0:57
This conversation is for Founders building in Healthcare,
1:00
ministers chasing high impact innovation, and anyone who's
1:03
ever wondered why the most advanced nation on earth can't
1:06
seem to modernize maternity care.
1:08
If you like stories where AI meets ambition and babies meet
1:11
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1:14
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1:17
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1:28
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3:31
Anish, how are you, Sir? Welcome to the show.
3:35
Ryan, I'm excited to be here. Thank you for the opportunity
3:38
and having that. Absolutely.
3:39
My pleasure. Now, to give us some context for
3:41
this conversation, give us a quick introduction to your
3:44
company baby scripts. Yeah, I'm one of the founders
3:48
and CEO baby scripts. We are in the mom baby space.
3:51
It our mission is to make the world a better place to have
3:54
babies. And who can't get behind that,
3:56
right. But specifically, I think the
3:59
things that we like to highlight is, you know, maternal morbidity
4:03
is, is increasing in the United States.
4:04
We're actually the only country in the, in the advanced economy
4:08
or that's happening. That's not something we're, you
4:11
know, we're super proud of. And I think one of the things
4:14
that we believe is, is a big kind of barrier is, is for
4:18
access to care or the heart of baby scripts is a platform to
4:22
help providers think about doctors, OBGYN's, nurse
4:25
midwives, improve access to care by using smartphones, you know,
4:30
data science, really remote monitoring technologies.
4:35
We think that can make a big impact to care, ultimately
4:37
really better quality and lowering the cost, right?
4:39
So that that's what we're all about.
4:41
You know, it's, it's I love it, man, and thank you for doing
4:44
that. It's you.
4:44
You could obviously do a lot of different things and you're out
4:46
here helping the babies. You're right.
4:49
Like what else? What better can you get behind
4:52
besides that? Now it's interesting to me in
4:54
medicine that it's called care and I, I happen to be a person
4:59
who, and probably some other people can relate to this, that
5:02
there seems to be a tension. It's like you have, you have
5:05
patients that are in need of care and you have doctors that
5:09
are willing to provide care. And yet our medical system is
5:12
such that like it's just an absolute quagmire of bureaucracy
5:18
and, and issues. And of course, all of these are
5:20
probably front page kind of news items, you know, but really the
5:23
promise of technology is to to facilitate that care, you know,
5:29
So you know, when I'm doing research on your company, it
5:32
sounds like you guys found it in 2013 with the vision of Internet
5:36
enabled devices and big data transforming pregnancy care.
5:40
Now we're at this moment where we have AI integrating into all
5:45
of our technology. Nobody really knows exactly how
5:48
we can utilize some of these tools.
5:50
There's a lot of different creative ways.
5:52
So if you look back to when you are founding the company to
5:57
where, where the company and where technology is now what
6:00
what's new and different and maybe exciting to to the
6:03
projects you're working on. Yeah, that's a really good
6:07
question. To your point, right, Like we,
6:09
we did found the company over a decade ago.
6:11
And I sometimes like to joke, I, I didn't have Gray hair when I,
6:14
when I started the company, you know, and I look closely, but
6:17
you might catch a couple, you know, but really we've gone
6:20
through, I'll say, multiple waves of technology adoption.
6:25
So, and when we started, like a telemedicine appointment was a
6:30
very novel concept. Right?
6:31
Now today, you can, you know, dial A doctor or call a doctor,
6:35
get on a call and get a, you know, mobile prescription,
6:38
right? So it was all very new and, and,
6:40
and certainly remote care or remote patient monitoring was
6:44
certainly very new, right? So the first few years for us
6:46
was just really clinical validation.
6:49
We did some studies, we partnered up with some, you
6:51
know, doctors and academic medical centers and, and really
6:54
published on the clinical efficacy of it.
6:56
And then as you imagine, COVID was this big, big, big
7:00
accelerant, right? You know, people couldn't leave
7:03
their homes, right? It was every, you know, there
7:05
was, there was national shutdowns, but how do you
7:07
deliver care when you can't leave the home, right?
7:10
So you got to do it remotely, asynchronously.
7:13
So much like a lot of other areas of healthcare, we saw this
7:17
traumatic adoption of since then, the pendulum sort of swung
7:22
back a little bit and people are trying to figure out what the,
7:24
what the white balances of in person care and virtual care and
7:28
digital health and all that kind of stuff, right?
7:30
So what's the first wave of technology that we saw?
7:34
And certainly kind of we, we were big benefits of
7:36
beneficiaries of it. The second wave is, is happening
7:40
right now, which is I'd say even bigger, right, which is the
7:43
impact of AI and AI related technologies and healthcare.
7:48
And there is so much to do and unpack there.
7:52
Ultimately a delivery of care we believe over the course of
7:56
several years will be delivered by AI in, in some way, shape or
8:01
form, right? But I always say in healthcare,
8:03
it's going to take a little longer for us to get there,
8:05
right? We're going to be probably one
8:07
of the last industries to truly fully kind of adopt healthcare,
8:12
as you can imagine, because of all kinds of risks, right?
8:14
Regulatory compliance, business model incentives, patient risk,
8:18
right? So I think, you know, in, in, in
8:20
the time that I've been, you know, with the company, you've
8:23
seen sort of two major sort of ways, right, that there's a
8:26
mobile digital teller and then now the AI, right?
8:29
And and on both instances we've we've really taken advantage of
8:33
it, right? So, yeah, you know, there's a
8:36
major regulatory compliance with medical for good reason, but
8:39
there's also kind of cultural barriers as well.
8:42
You know, the old guard. And, you know, doctors probably
8:45
get a a reputation for being stodgy and maybe a little
8:48
arrogant for good reason. You know, we, we want, we want
8:51
people in charge of our medical decisions to have a certain
8:54
swagger about them. How does that kind of impact the
8:57
the integration of technology into that kind of medicine?
9:01
Yeah, for sure. I think medical professionals,
9:03
doctors, their nature tend to be fairly conservative.
9:07
And they're thinking, I'll say right now, they certainly are,
9:12
you know, open to innovation, but for a lot of the reasons
9:15
they they want to make sure it isn't going to harm patients.
9:18
I mean, that's a really important thing.
9:20
They took that Hippocratic Oath, right?
9:23
And as a result of that, you know, what we see is
9:26
dissemination of any new technology, you know, takes
9:29
sometimes over a decade, right? Think about the new drug or
9:33
therapeutic or medical device post FDA clearance will take a
9:37
lot of time to get, you know, market acceptance, right?
9:41
And even then I think there, there tends to be skepticism
9:43
around new studies, right? We just saw the whole thing that
9:46
that came up with Tylenol, right?
9:47
And then pregnancy, right? So, yeah, I think, you know, for
9:51
a lot of good reasons, this has to be and medical professions
9:55
tend to be fairly cautious. I will say, I think, you know,
9:59
the, the, the other big kind of barrier in this is, you know,
10:03
the, the, the, the structure of payment and incentives in
10:07
healthcare, you know, like forces you to just go down one
10:11
very narrow pathway. It's people serve self-care.
10:14
So it's something is not being paid for.
10:16
Why would a doctor do it? Right?
10:18
So I'll just give you an example.
10:20
The the other day I was talking to someone, I was collecting all
10:24
this data from their oral ring, right?
10:27
I don't know if you're familiar with like the oral ring, right?
10:29
So, and he was telling me it's like, hey, like, you know what,
10:32
why doesn't my, why doesn't my doctor want to know, you know,
10:35
all the matter? And so if I sleep and overall
10:38
health and Wellness and you know, maybe he could find some
10:41
insights and, and give me some recommendations on it.
10:43
I think there's number one, right, Just, you know, is that
10:46
data valuable and meaningful, right?
10:48
And there's some open questions there, but more than anything,
10:51
it's and why would a doctor take 2030 minutes of this time?
10:55
And you know, do you or just review when you know, no payers
10:58
incentivizing him to do that, right?
11:01
So I think there's just like this mismatch and and payment
11:04
and business model. It's a massive tension and you
11:07
can see it play out on NFL Sundays, you know what I mean?
11:10
So you have kind of like a a conservative, slow moving
11:14
regulatory body and culture and medicine.
11:17
But if you're watching football, there's going to be
11:19
advertisement where someone's like, hey man, do you want to
11:22
lose a bunch of weight? Get super sexy with the full
11:25
head of hair in a massive erection?
11:27
No problem, we got you covered right here.
11:29
Just go to the app and download a couple of things and boom,
11:31
we're sending you pills. You know, So like, the, the, the
11:34
market's demanding, like speed and innovation and like, we
11:38
don't want these barriers. I don't want to have to deal
11:40
with, like, driving 20 miles to go see my doctor for 30 minutes
11:44
where, you know, he taps me on the knee with a hammer and he's
11:47
like, yeah, yeah, you're good. And you ask him about your diet,
11:50
and they're like, eat what tastes good.
11:52
You know, you ask about your sleep.
11:53
You like sleep when you're tired.
11:54
You know, I think the, the demand is really asking for a
11:58
lot more. And technology is delivering a
12:01
lot of these answers. Now.
12:02
You've been doing this for 10 years plus, so you have a good
12:06
kind of finger on the pulse of like, you know, not only
12:08
regulatory but also culturally, like what people are ready to
12:12
take because oftentimes, if you're giving too many ideas at
12:15
once, you're going to overwhelm people.
12:17
So when you're thinking about baby scripts, what are the kind
12:20
of successful features of the tool now that kind of resonate
12:23
both with, you know, patients, Mamas and doctors?
12:28
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14:34
Yeah, Yeah, it's a really good question.
14:37
You know, look, I'd say one thing I'll start by mentioning
14:39
is that the users and the patients we serve are typically
14:42
young, right between the ages of 18 and 35.
14:46
It's So what does that mean? That means they are not even
14:49
millennial anymore. They're Gen.
14:51
Z, right? So they are on the tip of the
14:54
spear. You know, they, they like to
14:55
TikTok, right? They, they love adopting and
14:59
examining new technologies, right?
15:01
So I mean, one thing we've seen is as a result of that, they
15:04
just demand better tools and better products and better
15:07
services from there. That's point number one.
15:10
Point #2 is in pregnancy specifically, it's a defined
15:16
episode. Like they have 123 and and you
15:20
know, we think about the fourth trimester after the delivery as
15:22
also 4th trimester, right? That's what we're dealing with.
15:25
And they're folks want to be really connected with their care
15:29
team. And what I mean by that is they
15:32
don't want to just go to, you know, online or or some consumer
15:36
store and just buy a widget, you know?
15:39
Yeah, that's cool, right? And there's some value in that,
15:41
OK. What they want is to collect
15:43
this data, interact with these devices, but then share that
15:47
with their care team in a way that is super thoughtful without
15:50
creating more work for them. And then that's what we focus in
15:53
on, right? So when someone gets pregnant
15:55
and gets on baby scripts, we ship them a kit goes through the
15:58
home, There's usually a blood pressure cuff in there, the
16:02
connected blood pressure cuff cellular live.
16:04
You know, it's a Bluetooth, right?
16:06
Not only are we with the companion app and a bunch of
16:09
other tooling within the app, are we collecting all that
16:12
information if something requires immediate attention,
16:15
we're notifying the patient, but also their doctorate.
16:18
The whole loop is complete, right.
16:19
So we think that modern way of delivering pregnancy care is is
16:25
through this virtual sort of asynchronous modality as opposed
16:29
to, you know, need a knee, right?
16:30
Like those days around right. So we're adopting that and and
16:34
really amplifying that across the country.
16:36
Amazing. So blood pressure is one data
16:38
point that people can get right in their their their homes.
16:42
What are some of the other data points?
16:45
Yeah. So we look at weight, weight,
16:47
gestational weight gain, and then the other things we start
16:50
to weight, we started to look at is diabetes, right?
16:52
So if you're pregnant and, and, and become diabetic or already
16:55
diabetic, become pregnant, right, Gestational diabetes,
16:58
right? That's this blood sugar that we
16:59
collect from and then, you know, through the app itself, we
17:02
collect a whole bunch of information around symptoms.
17:06
How are you feeling? What's your mood like now?
17:08
We collect specific symptoms from preeclampsia, which are
17:12
which is a very dangerous addition in pregnancy.
17:14
We also look at overall, you know, social determinants of
17:17
health. You have difficulty getting to
17:19
the practice. Do you need concentration help?
17:22
Turn on mental health studies, right?
17:24
Scanning for depression or suicidal ideation, right?
17:28
So yes, through, through the app and, and you know, kind of the,
17:31
the advice and Corey, we're able to collect a lot of data.
17:35
And then in the future we're also looking at remote
17:38
stenography field monitoring type of thing.
17:40
So I think that stuff gets a little bit more science
17:43
fictiony. But, you know, we think that's
17:44
the future, right? But it's here, it's here now,
17:47
you know, so it's, it's a mix of kind of contextual, almost like
17:51
a journal, you know, the old school baby book.
17:53
You pull that out for any one of us and our moms filled out the
17:56
1st 5 pages and then it's blanked the whole way through
18:00
largely because, you know, you didn't have it pinging you
18:02
asking for updates, which we can do now on people's phones.
18:06
You also have biometric data that that is getting inputted.
18:10
That's, you know, if it's blood pressure, I'm sure you can add a
18:12
lot of different blood works and things like that.
18:15
Now the, what I'm really interested in with kind of like
18:18
where we are right now is kind of what are kind of the ideal
18:21
data points because we're getting to a point with
18:24
wearables and things like that. I mean, you mentioned the aura
18:26
ring and we got, you know, Zuckerberg's got his classes and
18:30
we're going to have all these different ways to measure had a
18:32
wonderful conversation with the, the founder of Canary Speech
18:36
that's doing AI analysis of your voice.
18:38
And they can detect like depression, stress, anxiety,
18:41
multiple sclerosis, like these different variables from just
18:44
like the tenor of your voice. So we're getting able to,
18:48
because of the massive processing power of LLMS and,
18:51
and other AI tools to really interpret a lot of different
18:55
markers, you know, whether it's sweat or blood pressure or heart
19:01
rate, obviously, or vision or, you know, mood and, and, and
19:06
attitudes and diet and all these things.
19:09
So when you're looking into the future, short term, long term,
19:13
are you, you know, are you thinking of developing, you
19:16
know, baby scripts into a hardware company that's going to
19:18
actually get and gather some of these markers?
19:20
A software company, a medical company that's doing analysis
19:24
and serving the doctors? Where do you see kind of the
19:26
future? Maybe scripts evolving?
19:29
Yeah. I mean, I think I'll kind of put
19:31
it into two categories, right? There's things that we collect
19:34
today and I want to make a really important point on that.
19:36
And then there's kind of the future state, right?
19:38
So, you know, one thing that's interesting in in pregnancy is
19:43
that you can actually do a lot by collecting kind of very basic
19:48
information. It's so for example, you know,
19:51
just simply knowing that you know, like what type of
19:55
pregnancy it is, right? Is it a basic pregnancy or does
19:59
the amount of right like that creates 2 very different
20:03
trajectories essentially or a history of pregnancy.
20:05
What happened in last pregnancy ends up being pretty overstate,
20:08
right? The only thing also is that
20:11
being like the mom basically engaged right?
20:15
In other words. Like back in the old days, you'd
20:18
go to your local library or go to the bookstore and just buy a
20:21
buck, right? Which I say, here's everything
20:23
you should know about pregnancy. Wait, how much water can you
20:25
drink? How much coffee can you drink?
20:27
Can you take time, blah, blah, blah, right.
20:29
Super important because if you make wrong kind of move there
20:33
and that leads to, you know, potential adverse events
20:36
downstream in the actual delivery episode.
20:39
A lot of what we do is actually like not just collect
20:41
information, they're also educate and engage patients
20:44
right to the point where it's specific to their doctor.
20:47
It's OK, like who should I call if this this happened or now?
20:52
What pediatrician do you recommend as my doctor, right?
20:54
So it's a lot of that. It's a conduct care
20:56
coordination, right. But I put that all in the
20:58
current day, sort of like, you know, bucket in the future.
21:02
It's like there's this all of these like data that's been
21:05
collected lead nutrition, the use of CHG on continuous glucose
21:12
monitors is a big deal. And I think a rate limiting step
21:17
there is the clinical efficacy and validation.
21:21
And then what I mean by that is now it's, it's, it's one thing
21:24
to collect the data, it's something different to validate,
21:30
Hey, here's when you should intervene.
21:32
Here's when you should do nothing, right?
21:34
Because what doctors tell us is OK, like, I love all this data
21:37
that's happening. And I love like that your, I can
21:40
track your steps and your heart rate and all these type of
21:42
things, your temperature, right? What I, what I don't have the
21:46
time for is to weed through all of those details and know when
21:50
to intervene. And if I look at that data now,
21:54
I'm actually exposing myself to more live like one thing we
21:57
haven't touched on medical legal, right?
21:58
So I don't want to get sued if something bad happens in
22:01
pregnancy as this is very litigious, right?
22:03
So we do sample, see, right, a study showing, hey, like if
22:08
temperature rises X percent, then that's a rising risk that
22:12
needs intervention or sleep patterns are off this percent,
22:16
then that requires A deeper sleep study, right?
22:18
That type of thing. And I think that's sort of like
22:20
stitching of that value is something that we're very
22:23
interested in, but but frankly hasn't been fully done or
22:26
published, right? So now look at our North Star.
22:28
It's to remove all the friction in that process.
22:31
We think data is the the future, right?
22:34
And this is where AI can play a big, big role in that.
22:37
Percent. Did you say that like
22:39
introducing more data creates more liability for the on the
22:42
doctor side? Yeah, yeah.
22:45
So I'll give an example. So let's just say, you know,
22:50
they decide to share my sleep, sleep data with my doctor and
22:56
you know, like, let's just say something adverse happened like
23:00
to the baby at the time of delivery or to the mom then.
23:04
But that can get into some legal complications in the sense that
23:09
the doctor has, you know, actionable information
23:13
technically, right? And you know, a patient could be
23:16
a litigious on it, right? Like, I mean, these are all like
23:19
rare scenarios, right? Candidly so, but at the same
23:22
time, right, like, you know, it is one of the things that goes
23:25
into the thinking the of the provider or the doctor in making
23:30
a decision. It's OK.
23:30
You know what, I'd rather not even look at it then go down the
23:34
road of taking on risks. Right so.
23:35
What a nightmare. It's yeah, I mean, if the
23:38
incentives are totally screwed on this one.
23:40
So it's definitely a concern. It's terrible.
23:43
And this is where like even like there's at home ultrasounds you
23:47
can do like there's a little monitors and kind of
23:51
commercialized, all really interesting and valuable
23:54
technologies, but there's real rest.
23:57
I mean, to a certain extent I can, I can definitely see and
23:59
understand where the medical profession is coming from,
24:03
right? They're like, hey, like I don't
24:04
want to do this unless it's number one, it's technically
24:06
validated and #2 it's, it's actionable, right?
24:09
So, but at the same time right like this, this goes back to the
24:13
early question. It just slows down the rate of
24:16
innovation right in in healthcare.
24:18
So seems like a major problem. Like if if doctors aren't
24:22
incentivized to have as much data points as they possibly can
24:25
to inform the care, rather they're like AI don't want to
24:28
deal with the liability of knowing too much about what
24:30
you're eating. So let's not talk about that
24:32
wine at the end of the night. That's all you talk.
24:35
I don't know. So so 11 interesting piece on
24:38
this. There is like some interesting
24:41
areas of potential excitement here, right?
24:44
Like 1 is on this your model of statement called value based
24:48
care. Relatively, it's been around for
24:50
a while, but the where in in in value based care.
24:54
Let's just say, you know, Ryan, you're the patient and the
24:56
doctor, right? I get paid a 5 feet to take care
24:59
of you every year. And then doesn't matter what
25:02
kind of care I deliver, how often I see you.
25:04
If I don't see you, I just get one feet, right.
25:07
So all of a sudden I'm incentivized to make sure like
25:09
really taking care of you, right, Because I'm getting one
25:11
fee and I, I keep you, you know, safe and then not really all
25:15
that sick, then basically profit more.
25:19
It's so these alternative payment models are interesting.
25:22
It's, it looks like the wave of the future, right?
25:25
But it's it will also take some time to fully mature, right?
25:29
Yeah, it just makes me want to like interview my doctors and
25:33
make sure they're not on this train or I'll fire them
25:35
immediately. You know, it's like, I would
25:38
much rather prefer somebody who's like, look, man, I'm going
25:41
to kind of keep it loose and loose and fast here, give you
25:44
the best care I possibly can. Let's try this, let's try this,
25:47
let's try this. You know, that kind of person
25:49
brings it, you know, also just kind of philosophical spark of
25:52
improvisation and, and innovation that you know, so I
25:58
won't harp on it too much, but like kind of as I introduced it,
26:01
I do find myself in this like frustrating place often times
26:04
with the medical system and, and the kind of actual care, because
26:08
to me, you can't provide care. It's actually the antithesis of
26:11
care. If you're like you, you're
26:13
putting your head in the sand, you know?
26:16
Yeah. Yeah.
26:17
Well, I mean, I think, you know, if I'm also kind of steel
26:22
manning their case as much as possible here, right.
26:24
So it comes back to the access to care.
26:26
I mean, you know, if if I have 30 patients at sea today with 15
26:31
minute increments, but it's like, you know, at the end of
26:34
the day, I'm kind of burnt out. My wife's an OBGYN.
26:37
So, you know, I get to see this first hand to a certain extent,
26:39
right. So like, you know, you see a
26:41
whole list of patients today and then you come home and, you
26:45
know, you have dinner and then you boot up your laptop again
26:48
and you document everything, right.
26:49
Documentation is such a big deal.
26:51
There's, there's some major, major changes coming down the
26:54
Pike there, which we can talk about with AI.
26:57
But yeah, anyway, Long story short, yeah.
26:58
I mean, like this goes back to your original point.
27:01
I mean, you know, Healthcare is as you imagine, right?
27:04
Like pretty hesitant to change. It's still a major modality by
27:09
which information gets sent across machine, you know, So
27:13
that's still a real thing in healthcare, right?
27:14
So. Cool.
27:16
So who's the customer for baby scripts?
27:19
Is it doctors? Is it moms?
27:21
Who who's who's the customer? Yeah, we're, we're B to B,
27:25
right. So we, we sell to health
27:27
systems, doctors, providers. Now they in turn offer it to
27:31
their patients, right. So that's kind of the end
27:33
consumer in some ways is the B to B to C kind of model, right.
27:36
But we don't directly sell to consumers.
27:39
It requires a doctor prescription or approval for
27:42
them to get out. So, you know, Mama goes to the
27:46
doctor, they're like, hey, we're going to monitor this pregnancy
27:48
and and care with baby scripts. Talk a little bit about like the
27:52
feeling that you want to elicit from moms, Like how do they, how
27:55
do you want them to feel using the tool?
27:58
Yeah. So I mean, if that first early
28:01
conversation, it's a congratulations on your
28:03
pregnancy, you know what, we're going to just take care of you
28:07
by using baby strips. What does that mean going to be
28:10
able to monitor you when you're home, not, you know, when when
28:13
you're out and about, not, not just when you're in the office
28:16
here, right, Because a lot of stuff happens in between those
28:19
appointments. These risks are not captured.
28:21
As a result of that, we get better care and we get a more
28:26
engaged patient and ultimately a more satisfied it's so from a
28:30
patient perspective, right? The really cool thing that we've
28:32
seen is they get a little kicked that's delivered to their home
28:36
or they leave with that from the hospital, right?
28:39
And we see a huge amount of empowerment as a result of it.
28:43
It's like, oh, wow, like I get to like actually do some of this
28:46
myself, but I'm a blood pressure cop.
28:48
Take my blood pressure, answer a bunch of questions, right?
28:50
Like I'm motivated, right? Like I'm motivated in my own
28:53
care as opposed to some doctor just like telling me, yeah, very
28:58
specifically what to do, right. And I'm the one that I'll say,
29:01
hey, doc, like I took, I did XYZ and here's what I'm seeing.
29:04
Let's have that discussion, blah, blah, blah, right.
29:06
So you have a more engaged, empowered, motivated patient
29:10
that ultimately can drive just honestly a better, a better
29:13
journey for the patient and and also improved clinical that's
29:18
got a piece of letter, right. Yeah, so moms feel like they've
29:20
got agency. They're they're getting kind of
29:22
a perceived extra touch points with the doctor on a daily
29:25
basis. Hey, I'm uploading all the
29:27
information. I've seen screen grabs from baby
29:30
scripts. Haven't gotten around to play
29:32
around in there, but it's also beautiful and easy to use.
29:35
I mean, you know, I'm a little late to the doctor game because
29:39
I just, I'm more of like a rubber crystal on it kind of
29:42
guy. But you know, since you're
29:45
getting a little bit older, you got to go get things checked
29:47
out. So I got a whole fleet of
29:48
doctors and I'm telling you the technology and platforms that
29:51
they're using are terrible. You know, so you are.
29:55
You are. And I think that's that's.
29:56
Is really. But we're trying to bring it to
29:58
the 21st century. That's really what we're trying
30:00
to do, right? It's, I mean, I think, you know,
30:02
it's, it's think about like the experience that you have, you
30:06
know, if you were to drive a Tesla, right?
30:08
Or if you were to, you know, honestly, like, you know, use,
30:11
use any modern device or technology or platform, it's
30:14
like you want to try and mimic that as much as possible.
30:18
Yeah, bring, bring pregnancy to the 21st century.
30:20
And it's like a big part of what we're done.
30:22
Yeah, So Mamas are feeling good because they have agency in
30:25
their pregnancy. That's good.
30:27
Doctors are feeling good because it's aggregating all any kind of
30:29
concerns, also a lot of data before their next visit.
30:32
They're also being able to like soothe any kind of, you know,
30:37
pregnancy cares, which, you know, my wife had two kids and I
30:40
remember how that is, you know, there's definitely a lot of
30:43
anxiety there. So that's, that's helping that.
30:46
And also I'm sure it's saving, you know, the the doctors staff
30:49
resources, a lot of like answering emails and like
30:52
calling the clinics and things like that because there's a
30:54
central place where they can go. Right, avoiding unnecessary
30:59
visits, right. So that's another piece of it,
31:01
right. So and looked at me also.
31:03
So like they're identifying escalating risk, right?
31:06
So you know, one of our patients might have critically high blood
31:10
pressure it down, let's get them to leave and delivery in some
31:13
cases deliver that baby early, right.
31:15
But that having some dangerous situation happen to them on the
31:19
right. So, you know, for the doctors,
31:21
it's identifying risk that that they know is out there, but
31:25
little limited disability into it.
31:30
Seems to be like a lot of news stories about like Gen.
31:32
ZS not having kids. Are you worried about your job
31:35
security? Yeah, you know, well, I mean, I
31:41
think what's that a lot adage, right?
31:43
The the two things that will always stay is like, you know,
31:46
taxes, you know, death and and having babies, right.
31:49
So, so I mean that that's a little bit reductive, right?
31:55
I, I, I do think that, you know, we, we like there is like a
32:01
deeper sort of underlying sort of trend around not necessarily
32:06
Gen. Z not having kids, but
32:08
potentially having kids later in life.
32:11
It's so I think that's, that's, that actually ends up being, you
32:16
know, creating more risks, right?
32:17
So if you have, you know, a pregnancy after the age of 35,
32:21
it's called advanced and eternal age, right?
32:23
So, you know, that has more risks, you require fertility
32:27
services to have the kid, right. And then downstream that could
32:31
lead to a high risk pregnancy. So in some ways, right, that it
32:34
creates more usefulness for tool like ours, right.
32:38
So, so even though the numbers might kind of taper off or
32:42
stabilize, right, like more people will demand our services,
32:45
right? So that makes sense.
32:47
Well, yeah, don't answer your question.
32:49
I'm not worried about a big drop in in in pregnancies at least,
32:53
At least not. Yet first time moms when they're
32:56
40, I mean, the the anxiety and stress has really had a time to
32:59
fester and mature. So you're weren't we going to be
33:02
looking for those kind of data points and feedback For sure.
33:05
When you're 23, you still feel like you're invincibly like, oh,
33:07
we're not the baby. It's great.
33:09
You're not worried about it? Yeah, yeah.
33:11
And a lot of times, you know, if you're having a baby in 40,
33:14
right, you might not have a lot of other shots on goal.
33:17
You know, it's really important to to make sure you're really
33:20
taking care of your body and, and ultimately beat us as well.
33:24
Yeah. So as you're looking at the next
33:26
12 months, let's say, what are what are some, some goals for
33:30
the product that you're really excited about?
33:33
Yeah. So I think that a couple of
33:36
areas that were, you know, excited about, you know, one
33:40
I'll mention is, is very much sort of been the the AI realm,
33:44
right? So interestingly in in
33:47
healthcare, think the biggest value initially will be around a
33:53
nation of all of the gun, right? So every time we have an
34:00
interaction with our patient, right, that needs to be
34:03
transcribed, documented, summarized and ultimately
34:07
creates a billing event for there's a whole sort of like
34:12
this slow there, not necessarily super clinical in nature, but
34:16
highly administrative. And it just like it just creates
34:19
a lot of burden, right? So it go away as sort of the
34:24
first thing in the world of AI, right?
34:25
So any. So yeah, so using LMS to
34:29
generate, you know, clinical summaries, general clinical
34:32
notes, documenting it, it's really creating building out at
34:35
the event. So that's kind of the first
34:37
phase. And then, you know, beyond that,
34:39
looking at, you know, predictive risk algorithms and stuff to
34:42
deliver in the future is something also where get excited
34:46
about, you know, anything that's data rich, right, could be used
34:50
for used to find signals and risk predictors that, you know,
34:54
it might not be, it might be pretty difficult for just look
34:57
at the data and see right. So it can predict that that's a
35:00
big deal as well. Yeah, that could be huge time
35:03
saver, just admin administrative drain.
35:06
When you when you're building the app, how much consideration
35:09
is going into kind of stickiness for for the moms?
35:14
So is there attention to like gamification or just things to
35:18
make it more fun? You know, I could imagine doing
35:21
like a daily selfie as you can see the little bump growing
35:24
things like that. I mean, where, where does what's
35:27
the line between like creating kind of like a a fun consumer
35:30
product and having something very clinical?
35:33
Yeah. So it definitely is, you know, a
35:36
little bit more on the clinical side, right?
35:38
We, we certainly rely on core consumer kind of engagement
35:42
pieces, right? So we have, you know, in some
35:46
instances the customers can have like a reward system at that
35:49
they can use to reward patients by completing tasks and doing
35:53
things in pregnancy, right? We also generally want to make
35:56
it very visual multimodal in nature.
35:59
It's kind of this Instagram like steel within the app, right?
36:03
You know, but I will say, I think our goal isn't necessarily
36:07
like these big social media platforms to keep the mom in the
36:11
app for four, 5-6 hours a day, right?
36:13
That's just not very reasonable. But there are some very key
36:17
critical things we want them to do.
36:19
I mean, you know, learn about what's happening this week,
36:22
right? Learn about what are the things
36:23
that you do? There are a bunch of questions.
36:25
Take some biometrics and then they're done, right?
36:28
So it's it's like it's more like I kind of like to say it's like
36:31
it's like closer to Uber than it is to like, you know, Facebook
36:34
or Instagram, right, Which is I I need there's a very specific
36:38
set of things I'm going into the Apple, but we optimize for that,
36:41
right? So that's found the key thing we
36:43
we build into it. Some economics questions for the
36:47
CEO. From what I saw, you guys have
36:50
raised about 37 million. You've been around for 1213
36:54
years, fairly mature, stable business.
36:56
So what's next on tap? Are you guys looking to be
36:59
acquired? Are you going to raise and
37:01
scale? Are you thinking of acquiring
37:02
other companies? What's next for the biz?
37:06
Yeah. So I think from, you know, from
37:09
my standpoint, we don't necessarily think about an
37:13
acquisition and from a day-to-day standpoint
37:15
operationally, you see we know that there are opportunities out
37:20
there, right. So that's something we're all
37:23
sort of keeping in the back from to be honest.
37:26
Our goal is to, you know, build a broader set of products and
37:31
features on to our platform that we already have and then expand
37:35
our our user base, right? So our goals are to get to then
37:41
floor, you know, pregnancies by 2030, right?
37:44
Like that's that's sort of all the ambitious sort of goal that
37:47
we're going after. In doing that, we know we have
37:49
to build out some additional product, some additional high
37:52
risk services and at the same time sort of scaling what we
37:55
already have, right. So, but I think the future baby
37:58
stress will not just be, you know, kind of the software
38:01
piece, but a software with the blend of working with other
38:04
hardware providers and then ecosystem.
38:07
Yeah, you're, you're obviously bullish on technology and
38:10
data-driven as this gets more ubiquitous and it will you like
38:15
obviously a lot of these things will replace a lot of in person
38:20
kind of visits. Do you see like the the role of
38:24
doctors in in primary care kind of evolving to maybe more of a,
38:29
for lack of a better word, shamanistic kind of nurturing
38:32
kind of relationship? Yeah.
38:37
So I mean, I actually think what's going to happen is this
38:41
is a little bit further down the down the road, but I think the
38:46
consumers are going to have a say, like I'll say team of
38:50
expert, maybe not doctor, but team of experts that they can
38:53
pull on really on demand is sequentially.
38:56
It could be a genetic in nature, right, But it's going to be some
38:59
blend of that. It's so you'll have your primary
39:01
care physician. They as a captain of the what
39:05
these like modern technologies to enable goals to do is like,
39:07
let's just say I need a dietitian.
39:09
It's a very specific need. Not going to have to any any
39:13
longer, like find a local dietitian in my community, you
39:18
know, get an appointment, right? It's all going to be in like one
39:20
thing. It's let's just say I need
39:22
something very specific to my my sleep issued.
39:27
It's OK, well, in just threw like a turn on a switch, get a
39:30
speech sleep specialist to come in and organize me and then, you
39:34
know, kind of turn it back on. It's so you're gonna have like a
39:36
longitudinal view of a patient's health record and then on that
39:40
kind of dial it up or down as necessary.
39:43
It can and some of that's going to be AI driven, you know, all
39:46
agentic, you know, air provider, right, or a doctor, and some of
39:50
that's going to be, you know, human based right.
39:53
I think that's going to be the, you know, like the, the, the
39:56
future that I envision is, you know, they say like a doctor in
39:59
your pocket, right? Like I think that's not too far
40:02
off from where we are. Maybe I'll take another decade
40:04
or so because this is healthcare, right?
40:06
But I think, you know, kind of the ability just to scale and,
40:08
and the reason I say that is because a primary care physician
40:12
right today kind of manages about like 3000 patients.
40:15
They should be able to double, triple, quadruple that.
40:17
It would be sort of scaled and stuff, augmented and then scaled
40:20
things by way, right. So.
40:22
And you can apply that to any sub specialty and care, right?
40:24
So, so that's an exciting feature, means anyone can have
40:27
any types of care at any point at any time, right?
40:30
So, and that's also true in pregnancy, right?
40:32
So it's that's the exciting part about all those.
40:35
Yeah, you know, it, It sounds amazing having kind of like your
40:38
own doctor that's that's private to you.
40:43
You know, like you don't want like Sam Altman having all your
40:46
medical history, of course, but you can wall that off.
40:49
And now it sounds like because there's liability to data
40:52
points, then perhaps you can get better care.
40:55
And I just make the example that like, if you know, let's say
40:59
you're, you go to your primary care physician and they're like
41:02
a man, we're going to run your blood work.
41:04
Everything looks great. But you know, you also divulge
41:08
to me that you're drinking 4 cocktails a night, you know, So
41:11
when that health insurer or life insurance policy comes through,
41:14
I'm going to have to share that information with them because I
41:17
don't want the liability of this coming back to haunt me, you
41:21
know, with the life insurance company.
41:23
So now your policy went from 75 bucks to 750 bucks a month, even
41:28
though all your biomarkers show you're healthy.
41:29
But rather you divulged information that people were
41:32
afraid of liability. Now, that's a very specific
41:34
case, but if it, if it, if that trend continues, which it kind
41:39
of seems like it is. I mean, I guess I'm being
41:42
directly irritated by our healthcare system, largely just
41:48
the insurance providers and things like that.
41:49
Having an AI doctor that you can divulge without any kind of fear
41:53
of repercussion one way or the other seems like very helpful.
41:56
Now, now with the current LLMS we've got, you obviously have to
42:00
take that with a grain of salt because hallucinations are, are
42:03
real, you know, But largely, if you can get 8090% of the way
42:08
there, you're not making major medical decisions based on, you
42:12
know, yeah, perplexity or something, It seems like it
42:16
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defining together. Yeah.
43:37
And I think what's the way I kind of look at it is, is on one
43:41
hand, right, like you have this real time stream of information
43:45
coming in, like if you have an Apple Watch, it's collecting all
43:47
that data, your step count, your this, your that, your activity
43:51
circles, your rings. Like if you have like a loop
43:54
band or, or, and it's talked and all that, right?
43:56
Then in real time, you have kind of an agent, right?
43:59
Like just like screening that, looking at that, right?
44:02
Like, hang on, this is going to be totally agentic in agent,
44:04
right? And saying, Oh, you know, some,
44:06
some just a little bit off here right now.
44:08
Let me bring in like an actual, you know, doc or an actual
44:12
expert to you're human right, because I still think that's
44:15
super important and say, hey, Ryan, like, hey, I noticed XYZ
44:19
is happening. What's going on?
44:21
Oh, you just, you know, had like a big slice of pizza.
44:24
Whatever right could be, it could be nothing could also be
44:27
luck. I need you to come in.
44:28
Let's do a full blood work. This is something that that, you
44:31
know, like is speaking my interest and I need to do a
44:33
little bit more digging on this right.
44:35
So that world is, is such a like the, the detection of a risk in
44:44
the intervention and then like the same loop, right?
44:48
So that's amazing that that is the future of healthcare.
44:51
That means, you know, that the that means like you can
44:54
collectively improve out of humanity, right?
44:58
And and that's also true in pregnancy, which, you know,
45:00
think about like not having, you know, babies being burnt, you
45:03
know, born earlier than they should or just going through
45:06
full time in a more healthy manner, right?
45:08
So that gets you pretty excited, but it is also, I will say like
45:12
a ways away, right, because all the things you talked about,
45:15
regulatory governance, incentives, medical, legal,
45:18
right? So yeah, it's the vision that's
45:20
the dream. Love it.
45:23
Let's say you snap your fingers. You can never work in healthcare
45:26
again or health tech again. What?
45:28
What company would you start right now?
45:32
If I couldn't, could not work in healthcare again.
45:35
You have any other business ideas rattling around in there?
45:38
Yeah, yeah, yeah. I'll point to two.
45:41
I'm actually a big, big believer in, you know, mixed reality or
45:46
augmented reality or, you know, virtual reality.
45:48
I think there's a lot of value in it, right?
45:50
So like, you know, it's it's you know, I don't know exactly what
45:54
setting, but certainly in the enterprise setting, I can see a
45:57
lot of value for it, right. The other one is I would say
46:00
it's like, you know, robotics is the other piece, which I think
46:03
will be a truly transformative wave.
46:05
We're still a ways away from truly seeing the impact of that,
46:07
but it's on the heels of some of these LM props taken off, right?
46:10
So, you know, the optimist is an interesting one, right?
46:13
But there's a lot of others that are going on, right?
46:15
But so, yeah, I mean, I, I can't not think about healthcare.
46:20
Both of those have implications in healthcare, but but those are
46:23
two areas that I would definitely use.
46:25
Some more Optimus is going to be 20,000 bucks are you going to
46:27
get one I. Mean if it's truly $20,000 and I
46:32
don't have to fold my laundry over again.
46:35
Yeah. You know, is this what I'm going
46:36
to tell you? All right, So it would save a
46:38
lot of hassle and headache and some arguments with my wife.
46:43
Dude, they need to make it look like R2D2 though, man, some
46:46
robot with a head like that. I just have the the instinct to
46:50
want to hit it in the head with a bat.
46:52
I'm just like man, I I don't want some human looking thing in
46:56
the closet recharging and I just know it's in there.
46:58
There's something about like the build that I just.
47:01
It's a little freaky. It's a little freaky, Yeah.
47:03
Yeah. Have you seen?
47:04
I think it's like Figure 8. They they they make it super
47:07
realistic. It's a little.
47:09
With some it's a. Little some dead shark eyes
47:12
looking at you like you want a sandwich.
47:14
Be like no I do not I will make it myself.
47:16
Just go sit down and make yourself comfortable.
47:18
You give them heart palpitations.
47:20
Look at you in my kitchen. Yeah, Hang on.
47:23
Yeah, No, that's, yeah. That's definitely gonna get take
47:27
some getting used to. You know, if it was short.
47:29
Again, if it solves laundry folding for me, that's a big
47:32
deal. And dishes, those two, that's a
47:34
big deal. I might, I might have to, you
47:36
know, get OK, get, get OK with the awkwardness, you know, at
47:39
least initially, you know, So, yeah, the, what do you think?
47:43
What's, what's your, what's your hot take on future technologies?
47:47
Anything that stick out to? You, you know, I, I love all of
47:49
them. If I want to get real crazy, I
47:51
like thinking about quantum computing and just the the power
47:54
and magnitude of like what that means because it seems like it
47:57
turns into some kind of trans dimensional like wormholes
48:01
opening and stuff like that, you know, so.
48:04
It's like a, it's one of the Marvel movies, right?
48:07
Where there's like, you know, I'm lapsing and, you know,
48:11
leaping and also, yeah, I loved it.
48:13
They were on to something that. I love that you you're
48:15
interested in AR. So like let's say our glasses
48:18
right now have some kind of, we can put stuff on the screen.
48:21
What would you put on the screen?
48:25
Also, I mean, again, because of my like experience that my mind
48:28
quickly goes into care, but think about a surgeon having an
48:33
AR glass in there it and he's in there, he's dissecting something
48:39
it's doing sort of using computer vision, real time
48:42
analysis of everything that's gone on saying, Hey, hey, this
48:45
looks good. This is hold on a second.
48:47
There's something off here, right?
48:48
So and might be able to pick up things that the surgeon might
48:52
have it. So I think that's pretty,
48:55
pretty, pretty cool. And then you can also sort of,
48:58
you know, think about this in the in the paramedic emergency
49:01
response space, right? Let's just say someone needs,
49:05
you know, real time coding or resuscitation or let's just say
49:09
you have to deliver a baby, right, emergency delivery in the
49:12
back of a car at these days. It's just a total like, you
49:15
know, hope and a prayer. You put one of these arar
49:18
glasses on a dock that kind of beams in and then you know, it's
49:22
a guiding you doing this, doing that, right?
49:23
So. Yeah.
49:25
That's pretty. Powerful.
49:26
I agree. And the the the kind of
49:28
symbiosis I think is really interesting to me too, of like
49:31
robotics and humanity and, you know, human computer interface
49:36
near a link, of course, because, you know, our hardware right now
49:40
is a is hard wired for like 10 fingers, 2 arms, 2 legs.
49:44
But like, you could go Doc Ock really quick and be like, OK,
49:47
now I have 8:00 appendages. And like you can start to like
49:51
assign different tasks to different voluntary body
49:54
movements. So like, you know, you're
49:56
controlling your other two arms by blinking your eyes in some
49:59
way or by looking into a field of vision or like by secreting
50:02
some kind of like sweat gland that now you have control over,
50:06
you know? Yeah, yeah, yeah.
50:08
Well, so I think the first round there is yes, I think there's a
50:13
there's a world where you expand what you already have, but I
50:16
think the starting point there is like you replace something
50:18
you might not have. So think about a scenario where
50:20
one needs a heart. It can today you might look for
50:24
transplant it. But I I've seen these scenarios
50:26
where it's like, yeah, especially a pancreas, right,
50:29
for type 1 diabetics. There's scenarios there there
50:31
where they can, you know, replace and you know, and then
50:34
artificial pancreas eyes, right. I've seen, you know, so even
50:39
your one comes into demos. You can, you can see all of a
50:42
sudden, right, that that stuff was pretty, pretty rad.
50:46
Now, of course, the future is like, yes, having more eyes and
50:50
more ears and more sensitive ears, right?
50:52
So giving your superhuman abilities, you know, so here we
50:56
go. We're talking about, you know,
50:57
crazy stuff. Again, that's the fun stuff.
50:59
It's the fun stuff. You know, I think about it like
51:01
this. Like, would I replace my legs if
51:04
I could dunk? You know, probably not.
51:07
But would I replace my calf muscles and then I could dunk
51:10
and run really fast? Boy, I probably would, you know
51:13
it, it becomes like kind of an interesting conversation of like
51:16
what is me? Like I am in my totality, like I
51:20
want to have my toes over there. You want to replace my foot.
51:23
I don't think I'm signing up, but if it's like ligaments in a
51:26
heart and things like that, be like, yeah, I I think I I would
51:29
do that for performance enhancing even on top.
51:31
If it's a medical emergency, of course sign me up, but like.
51:35
What would I do just for? Funsies, you know.
51:38
Yeah, Yeah, yeah, yeah, yeah. No, I mean, I think, yeah, I
51:42
mean, I think the the other part of it is in in the in the realm
51:46
of like fertility, right? Like, you know, you can also,
51:51
you know, now do all these sort of like advanced screenings on
51:55
an embryo, for example, right before, you know, you put the
51:58
put the embryo back into the uterus essentially, right.
52:01
So you know, that movie of designer babies, right?
52:05
So it's that's two ways away. And obviously there's a lot of
52:09
biotics associated with it, right?
52:10
But it's it's, it's in the realm of like biological and
52:14
scientific feasibility, so. It's coming.
52:17
I know, I know. I'd be the person to do it once
52:19
CRISPR really catches up. You know, I name my kids weird
52:23
names. So I I'd be like, hey, can we
52:25
give them a tail and give them like purple eyes?
52:27
That would be cool. Yeah, yeah, yeah, yeah, yeah,
52:31
yeah. I mean.
52:32
Amazing. Yeah, I mean, that's the future
52:34
that I think we're all, you know, I don't know if it's
52:37
dystopic or utopic, you know, that's where for for society to
52:40
figure out. But look, I mean, at the end of
52:42
the day, right, technology, technological progress is
52:48
mentally a good thing. That's what I believe in.
52:50
That's why an innovator, right? That's why I think you're also
52:52
in the space, right? While there are always like, you
52:57
know, it's a double edged sword and all of these things, right?
52:59
Like we figure it out. Cool.
53:01
Couple of questions here for the lightning round.
53:04
Let's say you you sell your business for a billion dollars.
53:06
Hypothetically, you can never work again.
53:08
You actually can't work. How would you fill your days?
53:14
Would probably, yeah, I would. I think two things.
53:21
I know this is lighting around, but I think it's like, yeah, I
53:23
love learning, right? So I probably pick one or two
53:26
areas to go fully deep in and then also maybe teach, right.
53:32
So that that's one thing I feel pretty good about.
53:34
And a lifelong dream is has has also been to the farm, maybe a
53:41
little restaurant that the the from a table concept.
53:44
It's so it's more of a dream more than anything, you know,
53:48
that's all I will come to light. But yeah, you know, I'll go with
53:50
that. You know a farm and a teacher.
53:52
You know that's what. I'm doing what what would be on
53:53
the menu. It's more from a concept of just
53:59
like, you know, sustainability, right?
54:02
So it's just the basics, right? Fruits, vegetables.
54:06
Yeah, just like living off the earth type of concept, right?
54:10
The boring restaurant man. What?
54:11
What are we doing? You know what I might throw in
54:14
like some meat mushrooms in there as well, you know, so that
54:19
you know, you'd have to really come a long way to to get a hold
54:23
of right. So maybe that's all I'll do it.
54:26
I love it. Is there ACEO or a fellow
54:28
founder that is inspiring or that you follow closely?
54:34
Yeah, I mean, certainly have a lot of respect for some of the
54:39
marquee kind of generational ones.
54:41
Right? By your your, your Steve Jobs of
54:44
the world, your Larry and Sergey's of the world.
54:47
All correct. I recently read book on Uber,
54:53
Right. So Travis Kalanick, I think he's
54:56
he has his flaws, but there's a certain that, you know, certain
55:01
kind of personality that he had that indefinitely kind of
55:05
propelled Uber to into its current day, I think.
55:11
Yeah. So those are kind of the key
55:13
ones that you know that come to mind from the CE OS that inside.
55:18
Last one here, if you could live in any historical era, place and
55:21
time, where and when would it be?
55:29
I'm a sucker for childhood and that of early adolescent years,
55:36
right? So they there's a lot of
55:39
nostalgia that I have for the early 2000s, early mid 2000s
55:43
right where now like R&B, hip hop thing was just starting to
55:47
take off. You still had Rock'n'roll and
55:51
yeah, the world seemed like it was your oyster, right?
55:55
Social networking was just kind of taken off, right?
55:59
But yeah, you know, I mean, you call me a little nostalgic, but
56:01
I'll say early 2000s, you know, as as the place that I want to
56:04
go. Back to love it early 2000s.
56:06
You got your disk men and your Case Logic CD player.
56:09
What are you listening to? Definitely, you know, early
56:14
2000s I was definitely in the the Linkin Park Metallica kinda
56:20
phase, right. And then mid 2000s I shifted to
56:24
a little Jay-Z in there, you know, to some Kanye, you know,
56:29
got into like the the rap hip hop style of things.
56:32
Right now it's mostly just pop. But yeah, I mean, I was, you
56:36
know, good, good, good, good variety and blend there.
56:39
What did you think of the Linkin Park Jay-Z mashup album?
56:44
Yeah, so it's all those others is epic.
56:46
You know, it was that, like, yeah, like.
56:49
Absolute fire. Yeah, was the in the end piece
56:52
that the live concert was was amazing, you know.
56:56
So yeah, you wouldn't think it would.
56:58
It would work right off the bat, but something about that combo
57:00
just brushed. Fantastic.
57:03
Amazing. Anish, this has been so fun.
57:05
I really appreciate it. I want to give a a shout out to
57:09
a charitable organization that is near and dear to your heart,
57:13
which is the March of Dimes. Is that particularly close the
57:16
the one in New York City? There are offices in Washington,
57:20
DC, which is kind of where where I'm originally from, but they
57:23
have a national kind of presence.
57:25
But they do incredible work, research, advocacy, you know,
57:29
you know, it's, it's trying to make the world a better place to
57:31
have babies and so aligned with what we're trying to.
57:34
Do as a set and they actually have $1,000,000 babies.
57:37
March, March for babies, for March of Dimes, which is coming
57:41
up in New York City if people want to check them.
57:43
Actually participated in that Marshall waterfall.
57:45
Fantastic. You can learn more about baby
57:48
scripts at babyscripts.com. That will be in the show notes
57:52
if you want to click there and check that out.
57:54
Aneesh. What's the best place for people
57:56
to connect with you online? Yeah.
57:59
You can find me on aneesh at babyscripts.com, though I'm on
58:04
LinkedIn so you can also have me Sergeant Sebastian's.
58:07
Thanks so much for coming on the show.
58:10
It was awesome. Great conversation.
58:12
Now it was a lot of fun. Hey founders, let me ask you
58:17
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