The True Cost of Telling the Truth: Shiv Bhavnani’s Mental Health Revolution

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Getting fired was actually one
of the turning points in your

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career, and that actually LED
you to start getting the.

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I was at a ratings agency.
There's not that many out there.

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It's the one that the one that's
not S and Pi was in the office

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late one day and I found that.
Welcome to Low to Grow, the

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podcast transforming life's
toughest moments into

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opportunity for growth.
I'm Annie, a Forbes and

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Authority technology founder
who's entrepreneurship journey

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brand parallel to a mental
health awakening.

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In every episode, I sit down
with inspiring individuals and

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delve into how they managed to
turn their personal or

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professional challenges into
opportunities for growth.

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If you're facing uncertainty in
your life, feeling down, or

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simply need a kick of
inspiration to keep moving

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forward, this is your space for
the honest and uplifting

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conversations that you will want
to hear.

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Hit follow so you never miss an
episode and let's dive in.

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Today's guest is Shiv Bhavnani,
a healthcare investor, founder

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and one of the sharpest minds
shaping the future of mental

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health.
He is a partner at the venture

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capital firm Evo VC, which backs
early stage startups that are

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bridging mental Health and Human
performance.

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Now.
Shiv is also the founder and CEO

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of Gimbie, a research and
consulting firm providing

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insights into the healthcare
space that has already featured

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in places like Nature, Axios and
Business Insider as a global

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thought leader, have developed a
thesis on generative AI in

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psychiatry and is now writing a
book on AI in mental health.

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Now, Shiv is clearly someone who
really gets both the science and

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the assistance behind
innovation.

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But today he is joining a lot of
pro podcast to talk a bit about

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his own experiences as a young
professional, about big career

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pivots, finding work that
matters to him, and also what

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excites him about the future of
mental health.

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So, Shiv, welcome to the
podcast.

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Thank you so much, Annie.
That's a really incredible

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introduction.
So it's very generous.

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Thank you.
And it's awesome to be on the

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podcast today.
Yep, excited for us to be having

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this conversation.
So, Schiff, before we start, who

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do you think will benefit the
most from listening to our

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conversation today?
Honestly, I think it's just

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anybody who's trying to find
something that they want to do

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with their career that more
aligns with them.

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So basically anybody who's
looking for a change and, and

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anybody who's really thinking
about a career that resonates

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with what they deeply want to
do.

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Wonderful.
Excited to dive into it with

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you.
So you know, let's just start

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with the heart of it.
Why mental health?

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Well, yeah, so I could
definitely talk for two hours

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about that at least.
But I mean, there's so many

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reasons.
I'll first start off with the

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concept that I think when we
hear people's stories and people

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tell their stories, a lot of the
times it's a linear narrative.

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You know, this happened, this
happened, and then that drove me

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to that.
Maybe that is the truth for some

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people, but I think that for me,
life and pretty much everything

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has been way more of a spiral.
So it's circling around

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something and getting closer and
then coming back to the same

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spot, but you're closer.
And I think my whole life from

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when I was in high school,
middle school, I've been

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fascinated by the mind,
psychology, consciousness,

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spiritual practices.
That was kind of what drew me

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into the world of specifically
psychology.

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You know, when you think about
problems to solve, you know that

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there have been, you know, me
personally and people in my

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family have struggled with
mental health challenges.

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And when I look at the world and
look at, you know, what problems

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are important to solve, I'm not
saying it's objectively right,

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but I, I feel like the mind is
really the, it's the gateway to

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everything.
It's the software of humanity.

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We all operate using this tool
we call the mind, or you can

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simplify it to the brain if you
believe in just physical

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substrate.
It just seems like, wow, all of

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humanity is really through this
filter of the mind and we still

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don't understand it.
People in my life struggle with

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mental illness and I came to the
conclusion that the reason why

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we don't understand the mind
and, and, and the brain is is

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because we didn't prioritize it
as a society like putting in the

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resources and time.
That's that's kind of why mental

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health for me.
So interesting.

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And from your position as
someone who invests into really

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early stage startups without
building at the intersection of

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mental health, brain health, and
as a human performance, what are

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some of the things that really
excite you about the future?

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I mean, so many things, like
everything for from access to

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mental health care is something
that I pay attention to.

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It's like if we develop, let's
say we develop some new

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treatment, but it's, it cost
$1,000,000 and only 5 people in

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the world can get it, is that,
is that progress?

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I would not consider that
progress.

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I mean, it is one aspect of
progress in the kind of

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treatment efficacy world.
But I think we have things that

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do work.
Access is a big problem in

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mental health care.
There are some companies which

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seem, you know, maybe somewhat
boring on the cover of it.

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But what they're doing is
helping connect providers and

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people who really need care,
usually through the very

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complicated Byzantine structure
of government payers.

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So things like Medicaid.
So I would, I would say 1 area

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is expanding access.
That's that's what interests me.

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And, and I would say AI in terms
of specifically diagnosis and

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reconceptualization of like
mental health disorder

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classification, not AI
necessarily in terms of AI

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agents.
That, that that's interesting to

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me, but less, less so than using
AI to basically redefine what

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mental illnesses and identifying
different types of biomarkers

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for mental illness.
Because I think today what we

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think of as depression is
probably 16 different disorders,

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probably overlapping with our
definition of anxiety.

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Or that's just a, a random
example, but our classifications

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aren't necessarily real.
They're kind of made-up.

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That's interesting.
So what you're saying is using

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AI tools to, I guess, more
effectively segment the

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different classes of mental
disorders so about people can be

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treated more effectively based
on what subset that they have?

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Yes, exactly.
That process will involve

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rewriting the DSM.
People always ask the question,

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is that practical?
I think that ultimately it'll be

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necessary for us.
We will hit a roadblock in terms

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of how effective our treatments
can be without new

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classifications of disorders.
What does CSM stand for?

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The diagnostic manual, basically
it's a manual of mental health

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disorders, kind of like gold
standard for diagnosis.

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OK, understood.
You've talked a bit about the

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diagnostic portion.
What about using our tools in

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the treatment of certain mental
health conditions?

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Yeah.
So we, we've seen AI therapists

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as everybody knows, that's kind
of, or maybe I'm just in a

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little bubble, but I feel like
there's been talk of AI

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therapists as of the last year
or so.

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So that's like, you know, a
autonomous agent that

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potentially treats people.
You have clinical decision

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support tools for providers and
therapists and any, any type of

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other mental health professional
in the space.

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I think it's definitely
interesting and there's a huge

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need and demand for it.
If you think about how many

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people are using ChatGPT or any
kind of consumer LLM for

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emotional and mental health
support, it's already there.

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It's people are using in 10s of
millions of people are using

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those tools for mental health
support.

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Now you can argue, is that
right?

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Is that going to be effective?
That's another question, but

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people are using it, there's big
demand for it, that there's a

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very interesting case for AI to
be used directly as a treatment

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like some type of treatment
agent.

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But like I said, I think
diagnosis is actually in kind of

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redefining mental and brain
health issues and disorders.

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I think there's there's huge
potential there.

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Which organizations in your view
are leading development and also

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driving the end use of using AI
in diagnostics for mental

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health?
The diagnosis front, that's

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still largely being done by
universities and you know, there

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are definitely some companies
that have worked on identifying

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blood based, neural based or
even digital behavior based

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biomarkers for mental illness.
But it seems to me from from the

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outside, it seems like it's
tough to do that without making

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sure what you're looking for is
homogeneous.

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Like let's say, let's say
depression for example.

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There's been some very
interesting companies that have

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worked on voice based biomarkers
for depression and anxiety.

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One of those companies is
Kintsugi.

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Another company is Themia.
And I think they've actually

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been somewhat successful and
made some serious progress

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there.
But I think the more specific we

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can classify illness than, you
know, finding a biomarker for a

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very specific presentation of
something is much potentially

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easier.
It's chicken or egg obviously

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too, terms of AI agents like
chat bots for therapy.

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There have been a huge, huge
proliferation of these

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companies.
There's been dozens and dozens

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and and kind of the juries out.
We have yet to see who will

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emerge as a winner in this space
or even from a clinical

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perspective.
Understood.

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I want to take a step back.
Where did you start your career?

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Started my career in the
financial services world.

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My first job out of school was
working at Morgan Stanley on a

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sales desk, selling a kind of
complex product to banks and

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insurance companies.
Just a far cry from the world of

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mental health and healthcare
innovation when I was in

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college.
Extremely interested in the mind

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of the brain.
I started off as a neuroscience

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major actually, and through a
kind of rough year for me when I

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was 19, I failed out of almost
all of my courses in one

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semester, which were very heavy
on neuroscience.

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So my advisor was like, well,
listen, like you're going to

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have to take attention next
extra semester.

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It's probably not possible with
like the course offerings of

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different labs and things to
finish it in time.

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He was like, well, why don't you
just do it for fun and you don't

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have to major in that?
That's what I ended up doing.

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That kind of sent me in this
interesting path because I

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substituted the neuroscience
major with an econ major and

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sent me down this path in
finance.

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And I never really intended to
go down the path, but what I was

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doing was intellectually
stimulating enough.

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I was working with structured
credit, so highly financially

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engineered products, effectively
collateralized loan obligations

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specifically.
I worked in that for a few years

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across a few different firms and
I realized like this is so

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divorced from reality because
it's pretty abstract what we're

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doing.
I just felt very far from my

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personal mission.
I was about to kind of go deeper

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into space and I got an offer
from an investment fund to go

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work as a credit credit investor
and I decided to change my path

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and I started Gimme.
I started a newsletter covering

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the entire mental health startup
innovation ecosystem.

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You mentioned getting fired was
actually one of the turning

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points in your career and that
actually LED you to start Gimme.

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Could you share a bit more about
what led up to that event?

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I was at a ratings agency, which
I won't name, but there's not

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that many out there.
It's the one that the one that's

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not S&P.
At the time I was rating and

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doing research on structured
credit.

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Like I mentioned before, the
product called collateralized

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loan obligations.
At the time there were all these

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new startups coming out that
we're lending to individuals.

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So it's called marketplace
lending or P2P lending.

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So they're making these kind of
unsecured loans or it was a

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person making the unsecured
loan.

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I found that basically as as the
industry matured, a few Wall

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Street firms started to buy the
loans, package them, and then

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sell them as bonds, very similar
to a mortgage-backed security or

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collateralized loan obligation,
very similar structures.

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I was in the office late one day
and I was like, just like

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reading obsessively as I do.
And I was reading through some

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of the filings for the
securities and I found that

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there was no validation of the
information on the loans

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anywhere in this life cycle of
origining the loan, selling it

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into an SPV and then, you know,
selling bonds based on on that.

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Another way to put it, like the
nutritional facts on the bonds

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were fake.
There's like basically 0 proof

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00:14:12,000 --> 00:14:14,400
for that.
I brought it up internally and

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I'm like, wait a second.
Like, you know, I just watched

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00:14:17,040 --> 00:14:20,000
the Big Short, the, the
financial crisis when I started

237
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a career that was like very
close in the rearview mirror.

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A lot of folks had lost their
jobs during that.

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00:14:27,120 --> 00:14:30,440
And of course the whole world
went through a global financial

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crisis.
I brought it up internally and I

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00:14:32,720 --> 00:14:37,400
said, hey, like we're vetting
and rating these securities and

242
00:14:37,520 --> 00:14:40,760
we don't really bring this up as
a risk like it is an issue.

243
00:14:40,760 --> 00:14:44,680
At least I'm not saying to
totally condemn everything, but

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just say, hey, the the
originator of the loan is

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00:14:47,080 --> 00:14:49,840
basically saying all the
information on these loans could

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00:14:49,840 --> 00:14:52,720
be totally fake and we have no
liability there.

247
00:14:53,600 --> 00:14:58,960
And then the structure of the
bond was not doing any kind of

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00:14:59,000 --> 00:15:03,840
due diligence on the portfolio
of loans to, to validate any of

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this information.
So huge, huge risk if it got

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00:15:07,560 --> 00:15:10,560
bigger, if this became a
systemic problem, which it

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didn't, but if it did that, you
know, that'd be a serious issue.

252
00:15:14,160 --> 00:15:16,440
And even just for any of the
investors in these bonds.

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00:15:16,760 --> 00:15:20,680
Long story short, I, I, I wrote
a whole research paper on it

254
00:15:20,680 --> 00:15:22,880
internally.
I, I circulated it.

255
00:15:22,880 --> 00:15:27,720
However, the financial
institutions that were doing

256
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these securitizations were very
large and they had very close

257
00:15:32,320 --> 00:15:36,920
relationships with the ratings
agency goes back to the age-old

258
00:15:36,920 --> 00:15:39,960
incentive misalignment and in
the ratings world.

259
00:15:40,040 --> 00:15:43,280
But they kind of refused to
publish it.

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I'm like, what's going on here?
Like, you know, we could just

261
00:15:46,200 --> 00:15:48,520
mention this as a paragraph in a
report.

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00:15:48,520 --> 00:15:51,240
Like I don't need this to be a
whole thing.

263
00:15:51,600 --> 00:15:54,840
And there was almost like 0
receptivity to it.

264
00:15:55,280 --> 00:15:58,320
They usually do.
I like to shed light on things,

265
00:15:58,360 --> 00:16:00,960
be transparent and do what's
right.

266
00:16:01,080 --> 00:16:05,000
And I published it with a large
news outlet and then an industry

267
00:16:05,000 --> 00:16:08,200
trade publication.
I said these are my opinions.

268
00:16:08,200 --> 00:16:10,960
They don't reflect anything
having to do with the firm I

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work at or anything like that.
But very swiftly I was called

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00:16:15,240 --> 00:16:16,680
into the office and told to
leave.

271
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I'm glad I did it.
I don't have 0 regrets, you

272
00:16:19,600 --> 00:16:22,000
know, doing the right things
that you can never regret it.

273
00:16:22,000 --> 00:16:26,840
But it did make me think of
like, wait a second, maybe I

274
00:16:26,840 --> 00:16:31,680
need to actually do what I
originally kind of conceived of

275
00:16:31,680 --> 00:16:36,520
as my career working in the
world of mental and brain health

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00:16:36,520 --> 00:16:38,960
innovation.
But at this point, I have, you

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00:16:38,960 --> 00:16:42,200
know, no background in
neuroscience or mental health.

278
00:16:42,200 --> 00:16:45,280
So what do I do?
I do what I know best is and and

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00:16:45,280 --> 00:16:49,160
start publishing market research
on the space, covering all the

280
00:16:49,160 --> 00:16:51,640
investors and startups in the
space.

281
00:16:51,800 --> 00:16:55,040
Not right after that, but a
couple years after that.

282
00:16:55,040 --> 00:16:57,720
After I'd toyed with the idea, I
jumped in.

283
00:16:58,000 --> 00:16:59,960
Wow.
That's an amazing story about

284
00:16:59,960 --> 00:17:02,320
how you actually went back to
your roots of neuroscience and

285
00:17:02,320 --> 00:17:04,880
your interest in brain and
mental health while I was doing

286
00:17:04,880 --> 00:17:06,200
a detour loop.
Interesting.

287
00:17:06,200 --> 00:17:07,640
Thanks for sharing your story,
Chip.

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00:17:07,880 --> 00:17:11,520
When you were recounting it, you
made it sound very streamlined

289
00:17:11,520 --> 00:17:14,000
and almost quite matter of fact,
getting fired.

290
00:17:14,000 --> 00:17:17,599
No one likes fat.
And then kind of deciding how

291
00:17:17,599 --> 00:17:20,359
you're going to re enter the
workforce after getting $5.00.

292
00:17:20,359 --> 00:17:23,400
So it's really difficult for any
of our audience members who

293
00:17:23,400 --> 00:17:25,079
might be going through a similar
thing.

294
00:17:25,920 --> 00:17:29,560
What advice would you give them?
I actually found a job honestly

295
00:17:29,560 --> 00:17:33,280
after that, like very quickly.
I think the bigger question was,

296
00:17:33,480 --> 00:17:36,640
was that the right job after
that or should I have, you know,

297
00:17:36,640 --> 00:17:39,240
started Gimme earlier?
I think I would have liked to

298
00:17:39,360 --> 00:17:41,240
start Gimme earlier than I did
now.

299
00:17:41,240 --> 00:17:44,280
I was thinking about it at that
time, but I just didn't see

300
00:17:44,640 --> 00:17:48,040
commercial path to actually kind
of making it something that pays

301
00:17:48,040 --> 00:17:51,440
the bills and that you can make
actual make a living off of.

302
00:17:51,960 --> 00:17:54,840
I went back into the finance
world after that.

303
00:17:55,400 --> 00:17:58,320
I would tell people if you're
going through a tough time like

304
00:17:58,320 --> 00:18:03,560
that, I would really take the
opportunity to reconsider what

305
00:18:03,560 --> 00:18:07,160
you want to do and what you
really want to do because this

306
00:18:07,160 --> 00:18:12,520
could be a gift of some time and
space to rethink what you want

307
00:18:12,520 --> 00:18:16,600
to do.
Really use that gift of

308
00:18:16,600 --> 00:18:19,960
redirection.
Sometimes it's like, oh, you're

309
00:18:19,960 --> 00:18:22,880
doing exactly what you want to
do and then you get fired.

310
00:18:22,880 --> 00:18:25,160
That's one thing.
But if you're, you know, not

311
00:18:25,160 --> 00:18:28,600
totally aligned with what you're
doing, you're leaving energy on

312
00:18:28,600 --> 00:18:30,560
the table.
There's a lot of friction and

313
00:18:30,560 --> 00:18:34,880
energy loss through doing
something you don't really want

314
00:18:34,880 --> 00:18:39,520
to do.
I like that earlier when you

315
00:18:39,520 --> 00:18:42,120
mentioned the bigger question
for you was should you have

316
00:18:42,120 --> 00:18:45,120
started can be earlier?
For how long was can be your

317
00:18:45,120 --> 00:18:48,600
mind before you actually started
actioning and building it?

318
00:18:49,240 --> 00:18:51,680
Probably way too long, around
three years.

319
00:18:51,720 --> 00:18:55,520
I don't know why it was an idea.
And then I'm just taking more

320
00:18:55,520 --> 00:18:58,480
seriously than I was actually
thinking about a business model.

321
00:18:58,480 --> 00:19:02,680
So I started to study for the
psychology GRE because I was

322
00:19:03,000 --> 00:19:06,960
thinking about going to master's
and PhD program in psychology

323
00:19:07,000 --> 00:19:09,200
after I got fired.
So basically that, yeah, that's

324
00:19:09,200 --> 00:19:12,040
something I started to do.
So maybe it wasn't the idea of

325
00:19:12,040 --> 00:19:15,320
Gimme specifically, but it was
in the world of mental health

326
00:19:15,320 --> 00:19:17,240
innovation.
OK, interesting.

327
00:19:17,360 --> 00:19:20,160
And could you explain a bit more
about about, you know, exactly

328
00:19:20,160 --> 00:19:23,640
what Gimby does at the moment?
We're the global Institute of

329
00:19:23,640 --> 00:19:25,200
mental and brain health
investment.

330
00:19:25,600 --> 00:19:31,640
Our mission is to drive more
capital and resources into

331
00:19:31,680 --> 00:19:33,880
mental health, mental health
innovation.

332
00:19:34,280 --> 00:19:39,640
My diagnosis of the problem that
like, wait a second, why are why

333
00:19:39,640 --> 00:19:44,800
don't we have enough treatments?
Why do we, why has this, this

334
00:19:44,800 --> 00:19:48,280
therapeutic area been
significantly underfunded for

335
00:19:48,280 --> 00:19:51,040
decades?
So I started to look, look into

336
00:19:51,040 --> 00:19:53,360
these problem.
I found that it's not that a lot

337
00:19:53,360 --> 00:19:55,200
of people say, oh, it's so
complex.

338
00:19:55,200 --> 00:19:59,080
It's I think it was less that
and more of that as a society,

339
00:19:59,080 --> 00:20:01,960
we didn't really prioritize
mental health.

340
00:20:02,080 --> 00:20:05,480
There's a lot of stigma.
I think humans in general

341
00:20:05,480 --> 00:20:10,480
prioritize things they can see.
You could see a tumor you can't

342
00:20:10,480 --> 00:20:14,680
totally see.
A mental illness that you can

343
00:20:14,680 --> 00:20:17,440
see, oh wow, this brain looks
differently than the spring, but

344
00:20:17,520 --> 00:20:20,920
it's it's just harder to see.
So I think that in a sense was

345
00:20:21,000 --> 00:20:23,520
de prioritized.
Then you have stigma, a huge

346
00:20:23,520 --> 00:20:25,920
amounts of stigma amount mental
illness.

347
00:20:26,200 --> 00:20:30,360
We track the entire mental
health innovation ecosystem.

348
00:20:30,360 --> 00:20:33,040
We track funding and basically
trends.

349
00:20:33,040 --> 00:20:36,760
It's how we started and from
there, investors, investment

350
00:20:36,760 --> 00:20:41,640
funds, Angel investors,
nonprofits, anybody that had any

351
00:20:41,640 --> 00:20:45,120
interest in mental health
innovation started hiring us as

352
00:20:45,120 --> 00:20:48,480
a Consulting Group.
He would work on different

353
00:20:48,480 --> 00:20:53,280
engagements, everything from
strategy to standing up in the

354
00:20:53,280 --> 00:20:58,040
innovation arm for nonprofits to
investment work and due

355
00:20:58,040 --> 00:21:00,960
diligence on startups.
So basically anything that

356
00:21:01,040 --> 00:21:04,120
involves mental health
innovation specifically, say the

357
00:21:04,120 --> 00:21:10,040
functional areas we get hired
for, our fundraising strategy,

358
00:21:10,080 --> 00:21:12,840
business development and
recruiting, people want to know

359
00:21:12,840 --> 00:21:15,960
what's happening in the mental
health innovation landscape.

360
00:21:16,240 --> 00:21:19,600
It's changing very quickly.
I'm curious when you first

361
00:21:19,600 --> 00:21:23,120
started Gimbie, what about
operation look like was it just

362
00:21:23,120 --> 00:21:25,600
you or did you have you know
other founding partners that you

363
00:21:25,600 --> 00:21:28,200
put on from the very?
Beginning I was the main

364
00:21:28,200 --> 00:21:30,280
founding partner.
We, it was just me at the

365
00:21:30,280 --> 00:21:33,080
beginning, but then we, when we
started to get consulting

366
00:21:33,080 --> 00:21:36,960
engagements and, and have
revenue, then we started to hire

367
00:21:36,960 --> 00:21:38,800
folks.
But yeah, at the beginning it

368
00:21:38,800 --> 00:21:42,240
was just me.
Before AI scouring the Internet,

369
00:21:42,240 --> 00:21:46,440
making a big database of every
single company, doing countless

370
00:21:46,440 --> 00:21:49,520
calls.
I was doing over 20, sometimes

371
00:21:49,520 --> 00:21:53,560
30 calls per week with founders,
investors in the space.

372
00:21:53,560 --> 00:21:57,080
It was a really busy time and
it's cool to be here today.

373
00:21:58,040 --> 00:21:59,760
For me, it's really, yeah, cool
to see.

374
00:21:59,760 --> 00:22:02,960
You probably can be into almost
like a international

375
00:22:02,960 --> 00:22:05,600
organization.
So I know you do kind of events

376
00:22:05,600 --> 00:22:08,040
and those activities in the US
as well as in the UK.

377
00:22:08,440 --> 00:22:12,640
Quite curious if you had to
summarize the biggest change in

378
00:22:12,640 --> 00:22:15,240
mental health related funding
that happened over the past

379
00:22:15,240 --> 00:22:18,000
year, what would it be?
A few things.

380
00:22:18,080 --> 00:22:23,000
The exuberance from 2020 to 2022
is significantly subdued.

381
00:22:23,520 --> 00:22:29,120
There was this real euphoria and
leading to a lot of investments

382
00:22:29,120 --> 00:22:31,240
in the space and some
investments that probably

383
00:22:31,240 --> 00:22:34,160
shouldn't have been made.
That's a, you know, a large

384
00:22:34,160 --> 00:22:37,240
trend.
AI advancements are basically

385
00:22:37,760 --> 00:22:42,360
rocking and transforming every
single industry and mental

386
00:22:42,360 --> 00:22:45,320
health is no exception.
They're just interest in AI, but

387
00:22:45,680 --> 00:22:48,680
we're seeing a little less
precede funding.

388
00:22:48,800 --> 00:22:52,880
And that's where as a partner at
Evio Venture Capital, that's

389
00:22:53,000 --> 00:22:56,920
that's really a privilege to be
funding precede companies.

390
00:22:57,000 --> 00:22:59,760
There's a lot more trends.
We'll be putting out a report

391
00:22:59,760 --> 00:23:02,240
probably in a few months.
That's kind of what I see in a

392
00:23:02,240 --> 00:23:04,280
nutshell for the broader
audience.

393
00:23:04,960 --> 00:23:05,880
Thank you.
That's interesting.

394
00:23:05,880 --> 00:23:08,160
And I know it was a difficult
question because it's such a

395
00:23:08,160 --> 00:23:10,960
broad category.
You mentioned your work with EVO

396
00:23:11,200 --> 00:23:13,440
VC.
If you had to pick one of your

397
00:23:13,440 --> 00:23:16,360
current portfolio companies that
is really, really exciting for

398
00:23:16,360 --> 00:23:17,760
you, which one would it be and
why?

399
00:23:19,120 --> 00:23:21,640
It's a really good question.
I mean, it's like kind of

400
00:23:21,640 --> 00:23:24,200
picking your favorite child.
It's tough.

401
00:23:24,600 --> 00:23:28,320
This is an interesting one.
It's called Third Space Therapy.

402
00:23:28,800 --> 00:23:33,800
Third Space delivers therapy and
mental health care for Medicaid

403
00:23:33,800 --> 00:23:37,440
patients.
On first look, this doesn't seem

404
00:23:37,440 --> 00:23:44,160
that novel or interesting, but
there is a severe shortage.

405
00:23:44,160 --> 00:23:48,280
If there's a general provider
shortage for mental health care

406
00:23:48,720 --> 00:23:51,520
that's significantly more
pronounced in the Medicaid

407
00:23:51,520 --> 00:23:54,800
population.
And the reason is Medicaid

408
00:23:54,800 --> 00:23:57,480
reimbursement for mental health
care is relatively low and

409
00:23:57,480 --> 00:24:01,120
operational complexity, cost of
compliance are high.

410
00:24:01,160 --> 00:24:05,760
It's just operationally harder
to serve Medicaid patients

411
00:24:06,280 --> 00:24:10,000
because of all the government
requirements and reimbursements

412
00:24:10,000 --> 00:24:11,560
law.
You have a bunch of providers

413
00:24:11,560 --> 00:24:14,040
who say I don't take Medicaid, I
don't take Medicaid, I don't

414
00:24:14,040 --> 00:24:17,960
take Medicaid.
And that's a shame because there

415
00:24:17,960 --> 00:24:21,080
are folks in that population who
really need mental health care,

416
00:24:21,080 --> 00:24:24,120
and it just doesn't really make
sense from a financial

417
00:24:24,120 --> 00:24:27,560
perspective for some providers
to take Medicaid.

418
00:24:28,160 --> 00:24:32,720
Search space is basically
expanding this access and making

419
00:24:32,720 --> 00:24:38,240
the model work by streamlining a
lot of the compliance and

420
00:24:38,240 --> 00:24:41,680
operational complexity that
comes with serving Medicaid.

421
00:24:41,800 --> 00:24:46,400
So a little less exciting.
You know, it's not like a robot

422
00:24:46,480 --> 00:24:49,600
that can talk to you, but it's
really having a positive impact

423
00:24:49,600 --> 00:24:53,160
on the world.
And this goes back to what you

424
00:24:53,160 --> 00:24:55,920
were saying at the beginning of
our conversation, which is the

425
00:24:55,920 --> 00:24:58,840
companies might not look very
exciting on the outside, but

426
00:24:58,840 --> 00:25:01,920
they're doing the core almost
like bread and butter work, but

427
00:25:01,920 --> 00:25:04,040
as needed in order to make
mental health care more

428
00:25:04,040 --> 00:25:06,400
accessible to more people.
Yeah.

429
00:25:06,400 --> 00:25:09,240
And I think, I think there are
definitely exciting companies as

430
00:25:09,240 --> 00:25:11,720
well.
It's just that I think if you

431
00:25:11,720 --> 00:25:14,440
really want to make lasting
change in healthcare, you have

432
00:25:14,440 --> 00:25:17,360
to work with the system.
A lot of our portfolio companies

433
00:25:17,360 --> 00:25:22,560
do that extremely well.
Understood With your VC lens,

434
00:25:22,800 --> 00:25:26,880
what are some of the key things
that you look for in a startup

435
00:25:27,240 --> 00:25:29,520
that might come to you looking
for investment?

436
00:25:30,720 --> 00:25:33,640
That's a really good question.
There are so many things in

437
00:25:33,640 --> 00:25:36,800
terms of like the problem
they're solving in the solution,

438
00:25:36,800 --> 00:25:39,920
but like putting that aside,
because that's very industry

439
00:25:39,920 --> 00:25:42,000
specific, I would say for
founders.

440
00:25:42,000 --> 00:25:44,960
And we actually have a kind of
complex founder assessment

441
00:25:45,880 --> 00:25:49,720
process at EVO.
But something that we look for,

442
00:25:49,720 --> 00:25:53,560
and I specifically look for is
problem obsession.

443
00:25:53,800 --> 00:25:57,640
Founders who know the problem in
and out, like very, very

444
00:25:57,640 --> 00:26:00,120
obsessed.
They know every groove and it's

445
00:26:00,120 --> 00:26:03,000
like knowing every secret way
into the castle.

446
00:26:03,000 --> 00:26:06,800
Like you really studied it and
you, you, it's, it comes across

447
00:26:06,840 --> 00:26:10,400
that your obsession is not just
like mission obsession being

448
00:26:10,400 --> 00:26:13,760
like, Oh, I hate this, this,
that this exists and I really

449
00:26:13,760 --> 00:26:16,720
want to solve it.
It's that passion gets

450
00:26:16,920 --> 00:26:21,760
alchemized into real knowledge
or attempts at gain gaining

451
00:26:21,760 --> 00:26:24,840
knowledge to like just mental
obsession with the problem.

452
00:26:24,840 --> 00:26:27,960
And I think that's always pretty
palpable.

453
00:26:28,240 --> 00:26:30,520
You know, see a lot of lot of
founders who aren't.

454
00:26:30,520 --> 00:26:33,360
And I'm like, well, this is
going to be a long journey.

455
00:26:33,360 --> 00:26:36,920
And if you're not obsessed with
the problem and not emotionally

456
00:26:36,920 --> 00:26:40,160
obsessed, I think that's the
first step of like, actually,

457
00:26:40,160 --> 00:26:42,480
you know, being driven and
passionate about the issue.

458
00:26:42,480 --> 00:26:47,720
But does that crystallize into
action and like learning about

459
00:26:47,720 --> 00:26:50,400
in every way you can.
If I, you know, I want, I want

460
00:26:50,400 --> 00:26:53,960
to see people who find ways to
get information where there is

461
00:26:53,960 --> 00:26:56,200
no information.
If you're really obsessed with

462
00:26:56,200 --> 00:26:57,600
the problem, you're going to
find the info.

463
00:26:57,600 --> 00:26:59,960
You're going to figure it out.
Oh, I talked to 8 people.

464
00:26:59,960 --> 00:27:04,040
No, I, I found them.
I got introductions, referrals

465
00:27:04,040 --> 00:27:06,360
to these people who introduced
me to them.

466
00:27:06,360 --> 00:27:09,360
And then I taught there, you
know, just just when I see that

467
00:27:09,360 --> 00:27:12,200
resourcefulness and kind of
intensity about the problem,

468
00:27:12,200 --> 00:27:15,280
that's, that's a good thing.
If you had to give an estimate,

469
00:27:15,280 --> 00:27:17,680
what percentage of founders that
you do come across to hear

470
00:27:17,680 --> 00:27:20,760
pictures from actually have that
founder obsession?

471
00:27:22,200 --> 00:27:26,840
But I think the bar of probably
like one out of 10.

472
00:27:28,280 --> 00:27:30,680
Interesting because the first
thing that came into my head was

473
00:27:30,680 --> 00:27:34,040
the start, which is AC funds
generally expect one out of 10

474
00:27:34,040 --> 00:27:35,880
of the investments to become a
Unicorn.

475
00:27:36,160 --> 00:27:38,920
So I think it's interesting
that's the same start there as

476
00:27:38,920 --> 00:27:40,600
well.
Yeah.

477
00:27:40,880 --> 00:27:44,680
And you know, that's one aspect,
right, If you could be really

478
00:27:44,680 --> 00:27:48,280
obsessed with the problem.
But we know let's say this

479
00:27:48,280 --> 00:27:52,040
industry and we're like that,
that solution doesn't, we don't

480
00:27:52,040 --> 00:27:56,000
think that that approach is
correct for that problem or we

481
00:27:56,120 --> 00:27:59,320
think that this is not totally
scalable to won't achieve

482
00:27:59,320 --> 00:28:02,520
venture scale.
So there there's a hundred other

483
00:28:02,520 --> 00:28:05,280
reasons and investment might not
be a fit for a fund.

484
00:28:06,240 --> 00:28:09,840
But in terms of that kind of
like more behavioral problem

485
00:28:09,840 --> 00:28:13,040
obsession, yeah, I would say
maybe one out of 10.

486
00:28:14,800 --> 00:28:18,800
And either you have a specific
type of founder analysis.

487
00:28:19,080 --> 00:28:22,520
I read somewhere online that
either you assess how well

488
00:28:22,520 --> 00:28:25,800
founders know themselves, which
is a big factor in whether or

489
00:28:25,800 --> 00:28:29,040
not the firm decides to invest.
Could you expand a bit about

490
00:28:29,040 --> 00:28:33,120
what that actually means?
Our founder assessment process

491
00:28:33,120 --> 00:28:36,560
is pretty, pretty long and
complex.

492
00:28:36,560 --> 00:28:39,680
But yeah, self-awareness is
something that I think we, we

493
00:28:39,680 --> 00:28:42,320
definitely look for.
What do we mean by self

494
00:28:42,320 --> 00:28:45,520
worthiness?
My take is that it's important

495
00:28:45,520 --> 00:28:50,200
as a founder to know, like this
is a cliche, but it's true to

496
00:28:50,200 --> 00:28:53,120
know what you're good at, know
what you're bad at, to basically

497
00:28:53,120 --> 00:28:57,720
have a really clear idea of your
own strengths and weaknesses.

498
00:28:57,720 --> 00:29:02,440
Because only if you understand
and acknowledge what you're bad

499
00:29:02,440 --> 00:29:04,840
at can you plug the holes.
But if you, if there's no

500
00:29:04,840 --> 00:29:09,000
awareness of that, it's very
tough to to do that.

501
00:29:09,120 --> 00:29:14,520
It's self-awareness with respect
to 1's strengths and weaknesses

502
00:29:14,520 --> 00:29:19,640
when it comes to operating.
Thanks so much, going to move on

503
00:29:19,640 --> 00:29:23,360
to our podcast staple.
What is one thing that you

504
00:29:23,360 --> 00:29:26,320
believe will allow more people
to have better mental health?

505
00:29:27,320 --> 00:29:30,880
I might break the rules here and
say two things because I can't

506
00:29:30,880 --> 00:29:34,120
choose between these.
I think 1 is just sleep.

507
00:29:34,400 --> 00:29:38,800
Sounds so obvious, but, you
know, for years I would have

508
00:29:38,800 --> 00:29:42,120
ambient light in my bedroom that
totally just destroys your

509
00:29:42,120 --> 00:29:45,960
sleep, like blackout curtains.
It's got to be, you know, it's

510
00:29:45,960 --> 00:29:47,880
really got to be pitch black if
you can.

511
00:29:47,880 --> 00:29:51,000
And I mean, maybe that's.
Yeah, I think that's important.

512
00:29:52,240 --> 00:29:56,560
So good sleep for me.
What disturbed it was light and

513
00:29:56,560 --> 00:29:58,720
temperature.
It's like, you know, it's got to

514
00:29:58,720 --> 00:30:03,360
be cold and dark to sleep well.
So I'd say that and then, you

515
00:30:03,360 --> 00:30:07,000
know, mental health, and I'm,
I'm talking about just generally

516
00:30:07,000 --> 00:30:09,960
staying mentally healthy is not
just kind of reflecting in your

517
00:30:09,960 --> 00:30:14,520
mind, but running that self
reflection via verbalizing it,

518
00:30:14,520 --> 00:30:18,680
by writing it or even recording
a journal, doing some type of

519
00:30:18,680 --> 00:30:22,480
structured self reflection.
Be like, why did I do that?

520
00:30:22,520 --> 00:30:25,160
Why did I think that?
Why did I feel that and ask

521
00:30:25,160 --> 00:30:28,600
those questions and get answers
versus just running towards the

522
00:30:28,600 --> 00:30:33,800
next thing in your life?
Chip, it's been a pleasure to

523
00:30:33,800 --> 00:30:35,440
have you on the Low to Grow
podcast.

524
00:30:36,400 --> 00:30:39,080
Yeah, it's been a pleasure being
here, so thank you, Annie.

525
00:30:39,360 --> 00:30:42,120
That's a wrap for today's
episode of the Low to Grow

526
00:30:42,120 --> 00:30:45,160
podcast.
If it resonated with you, leave

527
00:30:45,160 --> 00:30:48,840
a review and hit follow to help
more people to find important

528
00:30:48,840 --> 00:30:52,040
conversations.
Keep growing and see you next

529
00:30:52,040 --> 00:30:52,280
time.